Skip to main content
NCBI home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2026 Mar 10;50(4):1017–1048. doi: 10.1002/wjs.70313

Mapping of Preoperative Screening Tools Reveals Urgent Need for Standardization in Gastrointestinal Cancer Surgery: A Scoping Review

Alexandria Paige Petridis 1,2, Jack Reeves 1,3,4, Cherry Koh 1,2,5, Michael Solomon 1,2,5, Sascha Karunaratne 1,2, Kate Alexander 1,2, Nicholas Hirst 1,2, Neil Pillinger 2,6, Linda Denehy 7,8, Bernhard Riedel 6,9, Chelsia Gillis 10, Sharon Carey 2,5, Kate McBride 1,5, Kate White 1,2, Haryana M Dhillon 11, Patrick Campbell 1,2, Raaj Kishore Biswas 12, Daniel Steffens 1,2,4,✉
PMCID: PMC13070451  PMID: 41806273

ABSTRACT

Background

Gastrointestinal (GI) cancers are a major global health challenge due to their high incidence, mortality, and surgical complication rates. Preoperative physical, nutritional, and psychological vulnerabilities increase the risk of adverse surgical outcomes. Despite this, there is currently no validated, self‐report screening tool integrating assessment across all three domains. This scoping review aims to identify and describe existing preoperative screening tools used to assess modifiable physical, nutritional, and psychological domains in adult patients undergoing elective GI cancer surgery.

Methods

We conducted this scoping review in accordance with Arksey and O'Malley's framework and PRISMA‐ScR guidelines. Searches were performed across MEDLINE, EMBASE, CINAHL, EBM, and PsycINFO date limited from January 2000 to March 2025. Studies were included if they evaluated preoperative screening tools for physical, nutritional, and/or psychological assessment in adult patients undergoing GI cancer surgery. Data on tool characteristics, domains assessed, administration time, and psychometric properties were extracted and synthesized descriptively.

Results

From 2825 initial records, 121 studies were included, encompassing 77 unique screening tools. These were categorized as physical (n = 21), nutritional (n = 16), and psychological (n = 40) tools. Most tools were brief (1–15 items).

Conclusions

Although most screening tools are brief, feasible for self‐administration, and freely accessible, none integrated all three domains. Substantial heterogeneity in tools highlights the need for a comprehensive, validated multidomain preoperative screening tool for this population.

Keywords: gastrointestinal cancer, multidisciplinary, scoping review, screening tools

Although most screening tools are brief, feasible for self‐administration, and freely accessible, none integrated all three domains. Substantial heterogeneity in tools highlights the need for a comprehensive, validated multidomain preoperative screening tool for this population.

graphic file with name WJS-50-1017-g001.jpg

1. Introduction

Gastrointestinal (GI) cancers represent a significant global health burden due to their high incidence and mortality rates. According to global cancer statistics from 2022, colorectal cancer ranked 3rd in incidence and 2nd in mortality, pancreatic cancer 6th in cancer‐related mortality, and esophageal cancer 11th in incidence and 7th in mortality [1]. Collectively, GI cancers comprised 24.6% of all new cancer diagnoses and were responsible for 34.2% of global cancer‐related deaths [1]. It is estimated that total annual cancer incidence could increase by 77% by 2050 [1].

The primary curative modality for many GI cancers remains surgical intervention; however, this carries a high risk of postoperative complications reported in up to one third of patients [2]. This delays recovery, prolongs hospitalization, reduces quality of life, and increases healthcare costs [2, 3]. Poorer preoperative physical, nutritional, and psychological health are well‐documented predictors of adverse surgical outcomes [4, 5]. This highlights the importance of improved strategies in early detection, perioperative management, and treatment optimization to address the growing burden of GI malignancies.

Prehabilitation has emerged as a useful approach to increase physiological reserve prior to surgery and has been introduced to surgical oncology evolved to encompass physical, nutritional and psychological factors [6]. Despite the growing recognition that preoperative physical, nutritional, and psychological status influences postoperative outcomes, there remains no standardized, validated, and self‐administered screening tool to objectively measure all three domains. This scoping review synthesizes the available screening tools encompassing physical, nutritional, and/or psychological domains with a specific focus on their application in GI cancer patients and forms part of a broader research program investigating preoperative screening tools for people undergoing GI cancer surgery [7].

The aim of this scoping review is to identify and describe preoperative screening tools used in adults undergoing GI cancer surgery.

2. Methods

2.1. Study Design

This scoping review follows the methodological framework outlined by Arksey and O'Malley and will be reported in accordance with the PRISMA Extension for Scoping Reviews (PRISMA‐ScR) guidelines [8, 9]. The protocol for this review has been prospectively registered on the Open Science Framework (OSF) platform (https://doi.org/10.17605/OSF.IO/RMSB6).

2.2. Eligibility Criteria

Studies were included if they were peer‐reviewed reports in English published between January 2000 and March 2025 (to ensure tool use reflects recent practice), involved adult patients aged 18 years or older undergoing surgery for GI cancers (including colon, rectum, pancreas, stomach, liver, spleen, and esophagus), and assessed or screened for physical capacity/function, nutritional status, or psychological health in the preoperative period. Eligible study designs included randomized controlled trials, cohort studies, cross‐sectional studies, case series with > 10 participants and published conference abstracts.

Studies were excluded if they involved mixed surgical populations with > 80% noncancer patients, did not involve GI cancer surgery or focused on cancer types not specified above, or were case‐control studies or case studies/series with ≤ 10 participants.

2.3. Information Sources and Search Strategy

A comprehensive search was conducted on MEDLINE, EMBASE, evidence‐based medicine (EBM), Cumulative Index to Nursing and Allied Health literature (CINAHL) and PsycINFO electronic databases. Search strategies were developed in collaboration with a senior librarian from The University of Sydney. A combination of Medical Subject Headings (MeSH) and keywords were used, including but not limited to: “screening tools,” “gastrointestinal neoplasms,” “preoperative,” “nutrition,” “psychological,” and “exercise” (Table S1).

2.4. Gray Literature

In addition to database searches, a gray literature search was conducted to identify relevant tools and studies not captured in searched databases. A process of “pearling” was employed, whereby the reference lists of all included articles were examined to identify additional studies of interest. Forward citation tracking was performed using Google Scholar to capture more recent studies, which cite the included works. This strategy ensured a comprehensive search by identifying unpublished or informally published materials that may contribute valuable insights into existing preoperative screening tools used in GI cancer surgery [10].

2.5. Selection of Included Studies

All identified citations were imported into systematic review software (Covidence) for de‐duplication and subsequent screening [11]. Two independent reviewers (AP and JR) conducted title and abstract screening against the predetermined eligibility criteria. Subsequently, full‐text articles were retrieved and assessed for final inclusion. The study selection process was documented at each stage, including the number of articles included and excluded, along with rational for exclusion. Inter‐reviewer disagreements were resolved through discussion or escalation to a third reviewer (DS) when consensus could not be achieved.

2.6. Data Extraction, Charting Process, and Synthesis of Results

Data extraction was performed independently by two reviewers (AP and JR) using a standardized extraction template in Covidence [11]. For each included study, information on study and participant characteristics were recorded, including, author(s), title, publication year, study design, GI cancer subtype, and sample size. Screening tool attributes were also captured in detail, including tool name, year of original development, recall period, number of items, domains assessed, scoring metric, scoring range, estimated completion time, response format, and accessibility (i.e., free vs. licensed).

Extracted data were synthesized descriptively and screening tools categorized by domain (physical, nutritional, and psychological). Findings were then presented in tabular and narrative formats.

3. Results

3.1. Study Selection

A total of 2825 records were identified through electronic database searches, including EMBASE (n = 1635), MEDLINE (n = 799), CINAHL (n = 260), evidence‐based medicine (n = 107), and PsycINFO (n = 24). After removal of 429 duplicates, 2396 records remained for title and abstract screening. A total of 332 full‐text articles were reviewed in detail, identifying 121 studies that met all eligibility criteria (see Figure 1 PRISMA diagram). Studies were excluded primarily due to: (i) not involving surgical populations; (ii) not using a screening tool preoperatively; or (iii) not including > 80% GI cancer patients (or lack of information regarding the specific patient population).

FIGURE 1.

FIGURE 1

Open in a new tab

PRISMA diagram for a scoping review to identify and describe existing preoperative screening tools used to assess modifiable physical, nutritional, and psychological domains in adult patients undergoing elective gastrointestinal cancer surgery.

3.2. Characteristics of Included Studies

Characteristics of included studies can be seen in Table 1. Most studies were prospective cohort designs (n = 63, 52%) followed by retrospective cohort designs (n = 10, 8%). Geographically, studies originated from 27 countries with the highest representation of studies being from China (n = 24, 20%), the United Kingdom (n = 13, 11%), the United States of America (n = 9, 7%), and Sweden (n = 9, 7%). All screening tools were applied between 48 h and 6 weeks preoperatively. Sample sizes ranged from 1712 to 1687 participants [95] with a median sample size of 140 participants. Cancer populations included were predominantly colorectal (n = 64, 41%), gastric (n = 26 17%), esophageal (n = 14, 10%) and pancreatic (n = 12, 8%) either exclusively or part of a mixed GI cohort.

TABLE 1.

Characteristics of studies included in the scoping review.

Author + year Study design Study duration Questionnaires Number of patients Mean age (± SD or range) Sex (%M:F) Cancer type
Nutritional
Agasi‐Idenburg 2020 [12] Prospective exploratory study 2016–2018 Lawton Brody scale, multidimensional fatigue inventory‐short version (MFI‐20), short nutritional assessment questionnaire (SNAQ) 56 67 (median) 64:36 Colorectal
Al‐Bayyari 2024 [13] Cross‐sectional 2018–2020 Malnutrition universal screening tool (MUST) 100 59.2 ± 9.8 60:40 Gastric, colorectal
Almasaudi 2019 [14] Prospective cohort study 2013–2016 Malnutrition universal screening tool (MUST) 363 66 ± 12 55:45 Colorectal
Andrew 2020 [15] Abstract—prospective cohort study 2019 Malnutrition screening tool (MST) 38 Not reported Not reported Gastrointestinal
Berstad 2013 [16] Observational study 2006–2009 Self‐administered food‐frequency questionnaire (FFQ) 100 67 57:43 Colorectal
Budzynski 2024 [17] Prospective cohort study 2016–2019 Barthel index [BI], lawton instrumental activities of daily living scale, mini nutritional assessment (MNA), nutritional risk screening (NRS‐2002), patient‐generated subjective global assessment (PG‐SGA) 84 66.7 ± 11.0 + 67.9 ± 12.2 66.7:33.3 + 52.4:47.6 Colorectal
Burden 2010 [18] Prospective cohort study N/A Malnutrition universal screening tool (MUST) 87 64 (range 23–90 years) 62:38 Colorectal
Casirati 2022 [19] Retrospective cohort study 2019–2020 Malnutrition universal screening tool (MUST) 100 61 (range 48.5–68) 48:52 Retroperitoneal sarcoma
Chen 2024 [20] Randomized control trial 2019–2023 3‐Day total food recall questionnaire, hospital anxiety & depression scale (HADS), nutritional risk screening (NRS‐2002) 115 Intervention: 73, control: 74 Intervention: 57.9:42.1. Control 51.7:42.1 Colorectal
Chi 2017 [21] Prospective cross‐sectional 2012 Nutritional risk screening (NRS‐2002) 280 62.9 ± 11.9 59.3:40.7 Gastrointestinal, colorectal
Chwesiuk 2023 [22] Abstract—prospective cohort study N/A Nutritional risk screening (NRS‐2002), self‐administered food‐frequency questionnaire (FFQ), short nutritional assessment questionnaire (SNAQ), the strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 32 66.0 ± 9.7 59:41 Colorectal
Dias Rodrigues 2017 [23] Prospective observational intervention study 2012–2014 Patient‐generated subjective global assessment (PG‐SGA) 37 60.2 ± 10 59.5:49.5 Gastric
Dou 2020 [24] Prospective observational cohort study 2015–2016 Nutritional risk screening (NRS‐2002) 201 64.7 ± 10.5 74.6:25.4 Gastrointestinal
Driessens 2022 [25] Prospective cohort study 2019–2021 Hospital anxiety & depression scale (HADS), patient‐generated subjective global assessment (PG‐SGA) 137 69.0 (63–74) 53.3:46.8 Hepato‐pancreato‐biliary (HPB)
Dubey 2024 [26] Prospective cross‐sectional study 2018–2019 Malnutrition universal screening tool (MUST) 24 N/A 47:53 Hepato‐pancreato‐biliary (HPB)
Elsherbini 2024 [27] Abstract—retrospective cohort study 2019–2020 Malnutrition screening tool (MST) 519 N/A N/A Upper gastrointestinal, lower gastrointestinal, thoracic
Fukuda 2016 [28] Prospective cohort study 2012–2015 Food frequency questionnaire 99 Sarcopenic: 78 (R 67–85) non‐sarcopenic: 75 (R 66–91) 66.7:33.3 Gastric
Fulop 2021 [29] Randomized control trial 2017–2019 Hospital anxiety & depression scale (HADS), malnutrition universal screening tool (MUST) 184 Intervention: 70 (IQR 60–75) control: 70 (IQR 64–75) Intervention: 43:57 control: 54:47 Colorectal
Gillis 2015 [30] Prospective observational study 2013 Patient‐generated subjective global assessment (PG‐SGA) 70 66.4 (± 12) 61:39 Colorectal
Gillis 2022 [31] Pooled analysis 2013–2019 Hospital anxiety & depression scale (HADS), patient‐generated subjective global assessment (PG‐SGA), community healthy activities model program for seniors questionnaire (CHAMPS) 266 Intervention: 69.6 ± 11.3 control: 74.6 ± 10.8 57.9:42.1 Colorectal
Guinan 2018 [32] Prospective observational cohort study N/A European prospective investigation of cancer food frequency questionnaire (EPIC FFQ), short nutritional assessment questionnaire (SNAQ) 28 62.9 ± 8.2 82:18 Esophageal
Guo 2010 [33] Prospective cohort study 2004–2007 Nutritional risk screening (NRS‐2002) 314 60 (R 24–94) 67.4:32.6 Gastric
Heckler 2021 [34] Prospective cohort study 2015–2017 Malnutrition universal screening tool (MUST), mini nutritional assessment (MNA), mini‐nutritional assessment‐short form (MNA‐SF), nutritional risk screening (NRS‐2002), nutritional risk screening score (NRS), short nutritional assessment questionnaire (SNAQ) 116 65 ± 11 46.6:53.4 Pancreatic
Hsueh 2020 [35] Retrospective cohort study 2007–2014 Malnutrition universal screening tool (MUST), nutritional risk screening (NRS‐2002), patient‐generated subjective global assessment (PG‐SGA) 272 65.7 (R 26.3–97.2) 64.7:35.3 Gastric
Hua 2022 [36] Prospective cohort study 2018–2019 Malnutrition universal screening tool (MUST), mini‐nutritional assessment‐short form (MNA‐SF), nutritional risk screening (NRS‐2002) 219 66 66.7:33.3 Esophageal
Huang 2020 [37] Prospective cohort study 2014–2018 Malnutrition screening tool (MST), malnutrition universal screening tool (MUST), nutritional risk screening (NRS‐2002), short nutritional assessment questionnaire (SNAQ) 880 64.5 (± 10.8) 73.8:26.1 Gastric
Karanikki 2024 [38] Prospective cross‐sectional observational study 2022–2023 Patient‐generated subjective global assessment (PG‐SGA) 480 CR: 69.2 ± 11.7. HPB 63.8 ± 12.4. Upper GI: 66.6 ± 11.2 CR: 62:38. HPB & upper GI: 67:33 Colorectal, hepato‐pancreato‐biliary (HPB), upper gastrointestinal
Karin 2020 [39] Prospective observational study 2013–2015 Malnutrition universal screening tool (MUST), patient‐generated subjective global assessment (PG‐SGA) 127 67 ± 11 71:37 Colorectal
Karlsson 2009 [40] Retrospective cohort study 2003–2005 Patient‐generated subjective global assessment (PG‐SGA) 153 70 (R 41–92) 50:50 Colorectal
Kim 2018 [41] Abstract—prospective cohort study 2008–2014 Mini nutritional assessment (MNA) 154 N/A N/A Periampullary
Klassen 2020 [42] Prospective cohort study 2016–2017 Patient‐generated subjective global assessment short form (PG‐SGA SF) 176 63.8 ± 12 52.3:47.7 Colorectal
Kollar 2022 [43] Prospective non‐randomized interventional study 2016–2018 Nutritional risk screening (NRS‐2002) 259 68.2 ± 10.7 58.7:41.3 Colorectal
Kopuz 2023 [44] Abstract—prospective observational study N/A Nutritional risk screening (NRS‐2002) 51 61.66 ± 11.9 years; 62.7:37.2 Colorectal
Lazaro 2023 [45] Abstract—prospective observational study 2019–2020 Malnutrition universal screening tool (MUST) Not reported N/A N/A Colorectal
Lewicka 2019 [46] Abstract—prospective control study N/A Nutritional risk screening (NRS‐2002) 143 N/A N/A Gastrointestinal
Lidoriki 2022 [47] Prospective cohort study 2015–2019 Patient‐generated subjective global assessment (PG‐SGA) 98 60.79 ± 10.19 80.6:19.4 Gastroesophageal
Loh 2012 [48] Prospective cohort study 2011 Malnutrition universal screening tool (MUST) 104 64.7 ± 10.8 60.6:39.4 Esophageal, gastric, pancreatic
Lu 2022 [49] Prospective cohort study 2020 Mini sarcopenia risk assessment (MSRA‐5), mini sarcopenia risk assessment (MSRA‐7), nutritional risk screening (NRS‐2002), the strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 263 62.38 ± 11.21 75.4:24.6 Gastric
Lu 2022 [50] Prospective cross‐sectional 2020 Nutritional risk screening (NRS‐2002), the strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 260 62.38 ± 11.21 75.4:24.6 Gastric
Niemelainen 2022 [51] Multicentre observational study 2019–2020 Mini‐nutritional assessment‐short form (MNA‐SF), onco‐geriatric screening tool (G8) 167 84.5 (R 80–97) 59.3:40.7 Colon
Noh 2022 [52] Retrospective cohort study 2012–2016 Nutritional risk screening (NRS‐2002) 274 63 (IQR 58–70) 94.5:5.5 Esophageal
Oikonomou 2024 [53] Abstract—prospective cohort study 2022–2023 Duke activity status index (DASI), patient‐generated subjective global assessment (PG‐SGA) 50 Not reported 54:46 Hepato‐pancreato‐biliary (HPB)
Pellegrinelli 2024 [54] Retrospective cohort study 2015–2022 Malnutrition universal screening tool (MUST) 79 G1: 63.1 ± 11.5. G2: 67.3 ± 8.5 G1: 50:50. G2: 60.7:39.3 Pancreatic
Reisinger 2015 [55] Retrospective cohort study 2010–2012 Short nutritional assessment questionnaire (SNAQ) 210 69 50:50 Colorectal
Ryu 2010 [56] Prospective cohort study 2005–2006 Nutritional risk screening (NRS‐2002) 80 G1: 58.5 ± 11.9 54:46 Gastric
G2: 56.5 ± 13.2
Tu 2012 [57] Prospective cohort study −2017–2019 Malnutrition universal screening tool (MUST) 45 62.1 ± 11.5 56:44 Colorectal
van der Kroft 2018 [58] Prospective cohort study 2012–2013 Malnutrition universal screening tool (MUST) 63 69 ± 10.5 64:36 Colorectal
Van Wijk 2021 [59] Prospective cohort study 2019–2021 Hospital anxiety & depression scale (HADS), patient‐generated subjective global assessment (PG‐SGA) 100 73 (IQR 66–76) 51:50 Hepato‐pancreato‐biliary (HPB)
Wang 2016 [60] Prospective cohort study 2014–2015 Nutritional risk screening (NRS‐2002) 255 65.14 ± 10.81 74.5:25.5 Gastric
Wang 2018 [61] Prospective cohort study 2016–2017 Nutritional risk screening (NRS‐2002) 60 N/A 90:10 Esophageal
Wang 2021 [62] Prospective cohort study 2018–2019 Malnutrition universal screening tool (MUST), mini‐nutritional assessment‐short form (MNA‐SF), nutritional risk screening (NRS‐2002) 189 65.1 ± 7.2 68.8:31.2 Esophageal
Wiljma 2024 [63] Prospective cohort study 2021–2023 Patient‐generated subjective global assessment (PG‐SGA) 30 G1: 60.5 (IQR 58–71.3) 15:85 Hepato‐pancreato‐biliary (HPB)
G2: 70 (IQR 59.8–74.5)
Wobith 2023 [64] Retrospective cohort study 2017–2019 Nutritional risk screening (NRS‐2002) 260 N/A N/A Gastrointestinal
Yang 2022 [65] Abstract ‐ prospective longitudinal study N/A Mini nutritional assessment (MNA) 112 N/A N/A Pancreatic
Yang 2024 [66] Randomized control trial 2021 Hospital anxiety & depression scale (HADS), nutritional risk screening (NRS‐2002) 95 G1l 60 ± 10 G2: 64 ± 12 61:39 Colorectal
Yeung 2017 [67] Prospective cohort study 2014–2015 Malnutrition screening tool (MST) 115 G1: 57 ± 13. G2: 61.6 14 58.3:41.7 Colorectal
Yong 2023 [68] Prospective cohort study 2018–2022 Nutritional risk screening (NRS‐2002) 312 72.7 69.6:30.7 Gastric
Yoon 2018 [69] Abstract—Prospective cohort study 2011–2012 Malnutrition screening tool for cancer patients (MSTC), malnutrition universal screening tool (MUST), nutritional risk screening (NRS‐2002), Seoul National University Bundang hospital nutritional screening tool (SNUBH‐NST) 170 N/A N/A Gastric, colorectal
Zhang 2022 [70] Cross‐sectional study 2020 Mini‐nutritional assessment‐short form (MNA‐SF), nutritional risk screening (NRS‐2002) 265 70 (IQR 66–74) 72.8:27.2 Gastric, colorectal
Zhang 2023 [71] Prospective cohort study 2021–2022 International physical activity questionnaire—short version (IPAQ‐SV) 359 G1: 63.90 ± 11.22 G2: 62.21 ± 11.17 64.3:35.7 Colorectal
Zhou 2025 [72] Retrospective study 2019–2021 Nutritional risk screening (NRS‐2002) 145 64 (IQR 55–69.5) 73.8:26.2 Gastric, colorectal
Physical
Ainsworth 2024 [73] Abstract—prospective cohort study 2021–2022 International physical activity questionnaire‐short form (IPAQ‐SF) 50 63 58:42 Colorectal
Bae 2023 [74] Abstract—retrospective cohort study 2019–2022 The strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 285 Not reported Not reported Colorectal
Cassini 2019 [75] Abstract—prospective cohort study 2018–2019 Frailty index test questionnaire, the strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 24 74 ± 5.8 N/A Colorectal
Chen 2017 [76] Re‐analysis of preoperative data from two randomized control trials N/A Community healthy activities model program for seniors questionnaire (CHAMPS) 116 Intervention: 67.9 (± 1.5) control: 67.3 ± 1.2 63:37 Colorectal
Chwesiuk 2023 [22] Abstract—prospective cohort study N/A Nutritional risk screening (NRS‐2002), self‐administered food‐frequency questionnaire (FFQ), short nutritional assessment questionnaire (SNAQ), the strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 32 66.0 ± 9.8 59:42 Colorectal
Dronkers 2010 [77] Randomized control trial N/A LASA physical activity questionnaire 42 Intervention: 65.5 (± 6.4) control: 71.1 (± 6.3) Intervention: 80:20 control: 68:32 Abdominal
Gillis 2022 [31] Pooled analysis 2013–2019 Hospital anxiety & depression scale (HADS), patient‐generated subjective global assessment (PG‐SGA), community healthy activities model program for seniors questionnaire (CHAMPS) 266 Intervention: 69.6 (± 11.3) control: 74.6 (± 10.8) 57.9:42.2 Colorectal
Gray 2020 [78] Observational cohort study N/A The patient reported outcome measurement information System‐10 (PROMIS‐10) 66 65 (± 12.5 49:51 Colorectal
Hernon 2021 [79] Multicentre randomized control trial 2016–2018 Godin leisure time physical activity questionnaire 200 67.8 (R 35–86) 68:32 Colorectal, abdominal
Iwakura 2023 [80] Prospective cohort study 2020–2021 International physical activity questionnaire‐short form (IPAQ‐SF), lowton instrumental activities of daily living scale, mini‐cog 97 74.4 ± 6.3 37.1:62.9 Gastric, colorectal, Gallbladder, bile duct, pancreatic
Karlsson 2019 [81] Prospective observational cohort study 2015–2017 The physical activity scale for the elderly (PASE) 140 76 ± 4.6 62.9:37.1 Colorectal, bile duct, pancreatic
Kim 2025 [82] Retrospective cohort study 2019–2022 The strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 285 High SARC‐F: 76.9 ± 8.5. Low SARC‐F: 64.5 ± 11.4 68.4:31.6 Colon
Komatsu 2018 [83] Prospective cohort study 2013–2014 International physical activity questionnaire—short version (IPAQ‐SV), Kessler 6 (K6) 29 65.9 (R44.9–78.7) 93.1:6.9 Esophageal
Le Quang 2023 [84] Re‐analysis of data from 6 RCTs and 1 cohort study 2011–2020 Community healthy activities model program for seniors questionnaire (CHAMPS) 459 G1: 72 (IQR 16). G2 (75 IQR 14) 56.6:43.4 Colorectal
Lin 2018 [85] Prospective observational study 2013–2015 Hospital anxiety & depression scale (HADS), international physical activity questionnaire‐short form (IPAQ‐SF) 30 56.0 ± 15.2 53.3:46.7 Colorectal
Lu 2022 [49] Prospective cohort study 2020 Mini sarcopenia risk assessment (MSRA‐5), mini sarcopenia risk assessment (MSRA‐7), nutritional risk screening (NRS‐2002), the strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 263 62.4 ± 11.2 75.4:24.7 Gastric
Lu 2022 [50] Prospective cross‐sectional 2020 Nutritional risk screening (NRS‐2002), the strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 260 62.4 ± 11.2 75.4:24.7 Gastric
Meyers 2019 [86] Prospective cohort study 2017–2018 Alcohol use disorder test‐clinician (AUDIT‐C), brief resillience scale, patient health questionnaire 2 (PHQ‐2), trauma survivors network recovery assessment Survey 143 65 (IQR 55–71) 55.9:44.1 Colorectal, hepato‐pancreato‐biliary (HPB)
Ngo‐Huang 2016 [87] Abstract ‐ prospective observational study N/A PROMIS 12a Physical function short form 20 64 55:45 Pancreatic
Ngo‐Huang 2019 [88] Prospective observational study 2015–2017 International physical activity questionnaire‐short form (IPAQ‐SF), PROMIS 12a Physical function short form 50 66 ± 8 years 52:48:00 Pancreatic
Oikonomou 2024 [53] Abstract—prospective cohort study 2022–2023 Duke activity status index (DASI), patient‐generated subjective global assessment (PG‐SGA) 50 Not reported 54:47 Hepato‐pancreato‐biliary (HPB)
Olsson 2007 [89] Prospective cohort study N/A Eating dysfunction scale (EDS), gastrointestinal symptom rating scale (GSRS) 24 Females: 60 (R 47–75). Males: 65 (R 51–83) 62.5:37.5 Gastric, pancreatic, GI cardiac, esophageal, bile duct
Onerup 2019 [90] Prospective cohort study 2014–2015 Self‐reported four‐level Saltin‐Grimby physical activity scale 115 1: 74.5 (IQR 15). 2: 71 (IQR 11). 3: 67 (IQR 20) 55:45 Colorectal
Parker 2019 [91] Mixed methods study N/A PROMIS 12a Physical function short form, physical activity readiness questionnaire (PAR‐Q), social support for exercise Survey (SSES) 50 66 ± 8 52:48 Pancreatic
Pecorelli 2016 [92] Analysis of randomized control trials 2011–2014 Community healthy activities model program for seniors questionnaire (CHAMPS) 151 67 (IQR 65–69) 65:35 Colorectal
Pecorelli 2024 [93] Prospective observational study 2020–2022 Duke activity status index (DASI), the patient reported outcome measurement information System‐10 (PROMIS‐10) 528 68 (IQR 59–75) 48.6:51.1 Pancreatic
PREPARE‐ABC Trial Collaborative 2021 [94] Pilot randomized control trial 2016–2018 Godin leisure time physical activity questionnaire 200 IG1: 67.6 (35–86). IG2: 66.7 (39–84). IG3: 69.1 (53–85) 68:32 Colorectal
Reinwalds 2024 [95] Prospective cohort study 2015–2019 Self‐reported four‐level Saltin‐Grimby physical activity scale 1687 71 ± 10 51.9:48.1 Colon
St‐Pierre 2022 [96] Abstract ‐ retrospective study 2011–2020 Hospital anxiety & depression scale (HADS), community healthy activities model program for seniors questionnaire (CHAMPS) 459 M: 64. F: 68 56.6:43.5 Colorectal
van Zutphen 2017 [97] Prospective cohort study 2010–2013 Short questionnaire to assess health enhancing physical activity (SQUASH) 515 65 ± 10 51:39 Colorectal
Yanagisawa 2022 [98] Prospective cohort study 2016–2020 International physical activity questionnaire‐short form (IPAQ‐SF) 101 63 (IQR 63–77) 61.4:38.6 Gastrointestinal
Zhang 2013 [99] Prospective cohort study 2008 Symptom checklist‐90 (SCL‐90) 60 59 ± 7 81.7:18.3 Esophageal
Zhang 2023 [71] Prospective cohort study 2021–2022 International physical activity questionnaire—short version (IPAQ‐SV) 359 G1: 63.90 ± 11.22 G2: 62.21 ± 11.18 64.3:35.8 Colorectal
Psychological
Acher 2020 [100] Abstract—Prospective cohort study N/A National comprehensive cancer network distress thermometer 34 Not reported Not reported Gastrointestinal
Antoniadis 2024 [101] Prospective cohort study N/A Hospital anxiety & depression scale (HADS), National comprehensive cancer network distress thermometer 118 70.5 ± 8.5 70:30 Colorectal
Baoyindeligeer 2020 [102] Randomized control trial N/A The self‐rating depression scale (SDS), visual analog scale (VAS), the self‐rating anxiety scale (SAS) 130 55 ± 6.31 36:64 Esophageal
Bott 2025 [103] Prospective non‐randomized trial N/A Shortened Warwick‐Edinburgh mental Well‐being scale (SWEMWBS) 41 Intervention: 63 + control: 65 Intervention: 81:19. Control 90:10 Esophageal
Calman 2021 [104] Prospective longitudinal cohort study 5 Years Centre of epidemiologic studies depression scale (CES‐D) 872 N/A N/A Colorectal
Chen 2024 [20] Randomized control trial 2019–2023 3‐Day total food recall questionnaire, hospital anxiety & depression scale (HADS), nutritional risk screening (NRS‐2002) 115 Intervention: 73, control: 74 Intervention: 57.9:42.1. Control 51.7:42.1 Colorectal
Ding 2023 [105] Prospective observational cohort study 2020–2021 Experiences in close relationship scale (ECR), family APGAR, frailty phenotype (FP), hospital anxiety & depression scale (HADS), international physical activity questionnaire‐short form (IPAQ‐SF), nutritional risk screening (NRS‐2002), social support rating scale (SSRS) 406 68.5 (IQR 65–73) 78.6:21.4 Gastric
Driessens 2022 [25] Prospective cohort study 2019–2020 Hospital anxiety & depression scale (HADS), patient‐generated subjective global assessment (PG‐SGA) 137 69.0 (63–74) 53.3:46.7 Hepato‐pancreato‐biliary (HPB)
Foster 2016 [106] Prospective cohort study 2010–2012 Centre of epidemiologic studies depression scale (CES‐D), medical outcome study (MOS), personal Wellbeing index‐audit (PWI‐A), positive & negative affect Schedule short form (PANAS), self‐efficacy for managing chronic disease scale, State‐trait anxiety inventory (STAI) 857 68.2 ± 10.7 59.6:40.4 Colorectal
Fujita 2003 [107] Prospective cohort study 1999–2000 Hospital anxiety & depression scale (HADS) 36 61:39 Abdominal
Fulop 2021 [29] Randomized control trial 2017–2019 Hospital anxiety & depression scale (HADS), malnutrition universal screening tool (MUST) 184 Intervention: 70 (IQR 60–75) control: 70 (IQR 64–75) Intervention: 43:57 control: 54:46 Colorectal
Gillis 2022 [31] Pooled analysis 2013–2019 Hospital anxiety & depression scale (HADS), patient‐generated subjective global assessment (PG‐SGA), community healthy activities model program for seniors questionnaire (CHAMPS) 266 Intervention: 69.6 (± 11.3) control: 74.6 (± 10.8) 57.9:42.3 Colorectal
Glass 2022 [108] Quasi‐experimental study N/A Generalized anxiety Disorder‐7 (GAD‐7), National comprehensive cancer network distress thermometer 18 60 (R 40–79) Not reported Colorectal
Gonzalez‐Saenzde Tejada 2017 [109] Multicentre cohort study 2010–2012 Barthel index [BI], Duke‐UNC functional social support questionnaire [FSSQ], hospital anxiety & depression scale (HADS) 972 67.5 (10.4) 62.3:37.8 Colorectal
Hao Law 2022 [110] Prospective cohort study 2018–2021 Hospital anxiety & depression scale (HADS) 78 66 (R 45–89) 56.4:43.6 Colorectal
Hong 2015 [111] Multicentre prospective cohort study N/A Cancer coping modes questionnaire (CCMQ), National comprehensive cancer network distress thermometer 165 62.2 (± 8.8) 77:33 Gastric
Iwakura 2024 [80] Prospective cohort study 2020–2021 International physical activity questionnaire‐short form (IPAQ‐SF), lowton instrumental activities of daily living scale, mini‐cog 97 74.4 ± 6.4 37.1:62.10 Gastric, colorectal, gallbladder, bile duct, pancreatic
Jakobsson 2016 [112] Prospective cohort study 2011–2013 State‐trait anxiety inventory (STAI) 105 68.5 49.5:50.5 Colorectal
Komatsu 2018 [83] Prospective cohort study 2013–2015 International physical activity questionnaire—short version (IPAQ‐SV), Kessler 6 (K6) 29 65.9 (R44.9–78.7) 93.1:6.10 Esophageal
Law 2023 [113] Prospective cohort study 2018–2021 Hospital anxiety & depression scale (HADS) 78 66 (R45–89) 56.4:43.6 Colorectal
Li 2021 [114] Abstract—prospective cohort study 2018–2019 Hospital anxiety & depression scale (HADS) 70 N/A N/A Colorectal
Liedman 2001 [115] Prospective cohort study 1984–1991 Body symptom scale (BSS), gastric Symptom rating scale (GSRS), Karnofsky performance status scale (KPS), mood adjective check list (MACL), Sickness impact profile (SIP) 33 66 (R 41–82) 65.6:34.4 Gastrointestinal
Lin 2018 [85] Prospective observational 2013–2015 Hospital anxiety & depression scale (HADS), international physical activity questionnaire‐short form (IPAQ‐SF) 30 56.0 ± 15.3 53.3:46.8 Colorectal
Liu 2021 [116] Prospective cohort study 2019–2020 Hospital anxiety & depression scale (HADS), surgical fear questionnaire (SFQ) 282 65.8 ± 12.0 61:39 Colorectal, gastric
Masui 2010 [117] Prospective cohort study 2008 Hospital anxiety & depression scale (HADS) 17 63 ± 5.7 88:12 Esophageal
Mei 2022 [118] Prospective cohort study 2015–2019 Hospital anxiety & depression scale (HADS) 125 1. 64.73 ± 8.83 Group 2. 63.37 ± 8.81 51.5:48.5 Rectal
Mesquita Garcia 2018 [119] Randomized control trial N/A State‐trait anxiety inventory (STAI) 50 IG: 58 ± 11, CG: 57 ± 15 44:56 Colorectal
Olsson 2007 [89] Prospective cohort study N/A Eating dysfunction scale (EDS), gastrointestinal symptom rating scale (GSRS) 24 Females: 60 (R 47–75). Males: 65 (R 51–83) 62.5:37.4
Ono 2021 [120] Prospective cohort study 2015–2020 Social frailty questionnaire, onco‐geriatric screening tool (G8), 15‐item geriatric depression scale 181 72 76.8:23.2 Gastric, esophageal, colorectal
Penning 2022 [121] Retrospective study 2016–2019 Onco‐geriatric screening tool (G8) 112 74 (70–92) 41.1:58.9 Colorectal, gastric, Small bowel, esophageal
Piraux 2020 [122] Prospective cohort study 2018–2019 Hospital anxiety & depression scale (HADS) 23 61.7 ± 10.6 69.6:30.4 Esophageal, gastric
Sarenmalm 2018 [123] Prospective cohort study N/A National comprehensive cancer network distress thermometer, problem list 488 68 (R 32–93) 45:55 Colorectal
Sawatzky 2023 [124] Prospective longitudinal study 2012–2015 Longitudinal preparedness for colorectal cancer surgery questionnaire (PCSQ), national comprehensive cancer network distress thermometer, sense of coherence short‐version scale 488 68 ± 11 56:44 Colorectal
Sharma 2007 [125] Prospective cohort study 2003 Hospital anxiety & depression scale (HADS), positive & negative affect schedule short form (PANAS), the mood rating scale (MRS) 104 67.6 ± 10.4 67.3: 32.7 Rectal
Sharma 2013 [126] Prospective cohort study 2003 Hospital anxiety & depression scale (HADS), positive & negative affect schedule short form (PANAS), the mood rating scale (MRS) 97 70 (39–86) 67:33 Rectal
Soler‐Silva 2022 [127] Abstract ‐ randomized control trial N/A Hospital anxiety & depression scale (HADS) 25 N/A N/A Colorectal
St‐Pierre 2022 [96] Abstract ‐ retrospective study 2011–2020 Hospital anxiety & depression scale (HADS), community healthy activities model program for seniors questionnaire (CHAMPS) 459 M: 64. F: 67 56.6:43.4 Colorectal
Sun 2020 [128] Cross‐sectional study 2013–2017 10‐Item rosenberg self‐esteem scale 434 62.6 ± 11 58.5:41.5 Colorectal
Turner 2019 [129] Prospective cohort study N/A Centre of epidemiologic studies depression scale (CES‐D) 857 N/A N/A Colorectal
Van Wijk 2021 [59] Prospective cohort study 2019–2020 Hospital anxiety & depression scale (HADS), patient‐generated subjective global assessment (PG‐SGA) 100 72 (IQR 66–76) 51:49 Hepato‐pancreato‐biliary (HPB)
Xu 2016 [130] Cross‐sectional study 2014–2015 Hospital anxiety & depression scale (HADS), medical coping modes questionnaire (MCMQ), social support rating scale (SSRS), the type D scale‐14 (DS‐14) 53 G1: 59.0 ± 10.4 G2: 58.1 ± 10.9 66:44 Gastric
Xu 2021 [131] Prospective cohort study 2018 Brief illness perception questionnaire (BIPQ), hospital anxiety & depression scale (HADS), identity‐consequence fatigue scale (ICFS) 463 G1: 60.45 ± 10.35. G2: 56.16 ± 11.72 55.7:44.3 Esophageal, gastric, colorectal
Yang 2024 [66] Randomized control trial 2021–2022 Hospital anxiety & depression scale (HADS), nutritional risk screening (NRS‐2002) 95 G1l 60 ± 10 G2: 64 ± 13 61:40 Colorectal
Open in a new tab

3.3. Characteristics of Identified Tools

Characteristics of tools identified can be seen in Table 2. A total of 77 unique screening tools were found. Most tools were concise with 71 (92%) of tools contained ≤ 15 items and requiring ≤ 10 min to complete. No self‐administered questionnaires that simultaneously assessed physical, nutritional, and psychological domains were found.

TABLE 2.

Characteristics of screening tools identified in the scoping review.

Tool name Times identified in search Year developed Recall period Number of items Response format Score range Time to complete Tool availability Total number of patients
Nutritional
3‐Day total food recall 1 1947 3‐days Variable Open‐ended, detailed food diary N/A Variable (∼ 30–60 min) Freely available 115
Alcohol use disorder identification test (AUDIT) 1 1989 12‐months 10 Likert scale 0–40 < 5 min Freely available 143
Eating dysfunction scale (EDS) 1 2005 Past week 25 Likert scale Variable 10 min Restricted 24
European prospective investigation of cancer food frequency questionnaire (EPIC FFQ) 1 1989 Past year 130+ Multiple choice N/A 30–60 min Freely available for research use 28
Malnutrition screening tool (MST) 5 1999 6‐months 2 Yes/No 0–5 < 5 min Freely available 1722
Malnutrition screening tool for cancer patients (MSTC) 1 2011 Current 4 Yes/No 0–4 < 5 min Freely available 170
Malnutrition universal screening tool (MUST) 18 2003 Current 3 Scored components 0–2 < 5 min Freely available 3122
Mini nutritional assessment (MNA) 4 1994 Current 18 Yes/No + scored items 0–30 10–15 min Freely available for clinical use 466
Mini nutritional assessment short form (MNA‐SF) 5 2001 Current 6 Yes/No + scored items 0–14 10–15 min Freely available for clinical use 956
Nutritional risk screening (NRS‐2002) 26 2002 Current 4 Scored items + disease Severity 0–7 < 5 min Freely available 5660
Patient‐generated subjective global assessment (PG‐SGA) 12 2005 4‐week 4 Sections Mixed 0–35+ 10–15 min Freely available for clinical use 1874
Patient‐generated subjective global assessment short form (PG‐SGA SF)/abridged PG‐SGA 2 2015 Current 4 components Self‐reported checklist 0–36 5–10 min Freely available 206
Self‐administered food‐frequency questionnaire (FFQ) 3 1970s–1980s Past year (typically) Varies widely (∼60–150 items) Multiple choice Not typically scored 20–60 min Freely available 160
Seoul National University Bundang Hospital nutritional screening tool (SNUBH‐NST) 1 2012 Current 4 Checklist + score 0–8 < 5 min Freely available in publications 170
Short/simplified nutritional assessment questionnaire (SNAQ) 6 2005 Past month 3 or 4 Yes/No 0–3 or 0–4 < 5 min Freely available 1322
Physical
Barthel index (BI) 2 1965 Current 10 Yes/No or scale 0–100 5 min Freely available 2028
Body Symptom scale 1 N/A 1‐week 28 item or 17‐item short version Likert scale Variable 5–10 min Restricted access 33
Community healthy activities model program for seniors questionnaire (CHAMPS) 5 2001 4‐week 41 Yes/No, frequency + duration MET‐min/week 10‐20 min Freely available 267
Duke activity status index (DASI) 2 1989 Current 12 Yes/No 0–58.2 or MET‐min/Week 5 min Freely available 578
Gastric Symptom rating scale (GSRS) 1 1988 1‐week 15 Likert scale 1–7 per item (means score used) 5 min Freely available for research use 33
Gastrointestinal Symptom rating scale (GSRS) 2 1988 1‐week 15 Likert scale 1–7 per item (means score used) 5 min Freely available for research use 57
Godin leisure time physical activity questionnaire 2 1985 Typical week 4 Open‐ended frequency Godin index score 5 min Freely available 400
Groningen frailty indicator 3 1999 Current 15 Yes/No 0–15 5 min Freely available 612
International physical activity questionnaire ‐ short version (IPAQ‐SV) 2 2001 1‐week 7 Open‐ended frequency + duration MET‐min/week 5–10 min Freely available 388
International physical activity questionnaire‐short form (IPAQ‐SF) 7 2001 1‐week 7 Open‐ended frequency + duration MET‐min/week 5–10 min Freely available 684
Karnofsky performance status scale (KPS) 1 2002 Current 1 Ordinal (increments of 10) 0–100 < 5 min Freely available 33
LASA physical activity questionnaire (LAPAQ) 1 1991 2‐week 7 Likert scale Variable 5–10 min Freely available 42
Lawton Brody Scale/Lawton instrumental activities of daily living scale 3 1969 Current 8 3‐point scale (0,1,2) 0–8 or 0–16 5–10 min Freely available 231
Mini sarcopenia risk assessment (MSRA‐5) 1 2017 1‐year 5 Yes/No 0–50 < 5 min Freely available 263
Mini sarcopenia risk assessment (MSRA‐7) 1 2017 1‐year 7 Yes/No 0–70 < 5 min Freely available 263
Patient reported outcome measurement information System‐10 (PROMIS‐10) 2 2009 Current 10 Likert scale Raw score to T‐Score < 5 min Freely available from PROMIS initiative 593
Patient reported outcome measurement information System‐12a (PROMIS‐12a) 4 2010 1‐week 12 Likert scale T‐score metric < 5 min Freely available with registration 120
Physical activity readiness questionnaire (PAR‐Q) 1 1978 Current 7 Yes/No Binary clearance? < 5 min Freely available 50
Physical activity scale for the elderly (PASE) 1 1993 1‐week 12 Frequency + duration (weighted scoring) 0–309 10–15 min Licensed (health assessment lab) 140
Self‐reported four‐level Saltin‐Grimby physical activity scale 2 1968 (revised 1990s) Current 1 4 response levels 1–4 < 5 min Freely available 1802
Short questionnaire to assess health enhancing physical activity (SQUASH) 1 2003 Typical week ∼13 Open‐ended + frequency/duration MET‐min/week 5–10 min Freely available 515
Strength assistance in walking rise from a chair climb stairs and falls (SARC‐F) 6 2013 Current 5 Likert scale 0–10 5 min Freely available 1149
Psychological
10‐Item rosenberg self‐esteem scale (RSES) 1 1965 Current 10 Likert scale 0–30 < 5 min Freely available 434
15‐Item geriatric depression scale 1 1982 1‐week 15 Yes/No 0–15 5 min Freely available 181
Brief illness perception questionnaire (brief IPQ) 1 2006 Current 9 Likert scale a+ 1 open‐ended item 0–80 5 min Freely available 463
Brief resilience scale (BRS) 1 2008 Current 6 Likert scale 06–30 (Sum) or 1–5 (average) 5 min Freely available 143
Cancer coping modes questionnaire 1 2003 Current 21 Likert scale 5–10 min Restricted/academic use 165
Centre of epidemiologic studies depression scale (CES‐D) 3 1977 Past week 20 Likert scale 0–60 5–10 min Freely available 2586
Duke‐UNC functional social support questionnaire [FSSQ] 1 1988 Current 11 or 8‐item short version Likert scale 11‐Item: 11–55 or 8‐item: 8–40 < 5 min Freely available 1944
Experiences in close relationship scale (ECR) 1 1998 Current 12 Likert scale 6–42 10 min Freely available for academic use 406
Generalized anxiety Disorder‐7 (GAD‐7) 1 2006 2‐weeks 7 Likert scale 0–21 5 min Freely available 18
Hospital anxiety & depression scale (HADS) 24 1983 1‐week 14 Likert scale 0–21 per subscale 5–10 min Freely available for academic use 4333
Identity‐consequence fatigue scale (ICFS) 1 2006 1‐week 31 Likert Variable 10–15 min Academic use 463
Kessler psychological distress scale (K6) 1 2002 1‐month 6 Likert scale + frequency/duration 0–24 < 5 min Freely available 29
Longitudinal preparedness for colorectal cancer surgery questionnaire (PCSQ) 1 2016 Current 28, 24, 14 Likert scale 28 item: 0–112. 24 item: 0–96. 14 item: 0–56 5–10 min Research use only 488
Medical coping modes questionnaire (MCMQ) 1 1992 Current 20 Likert scale 20–80 5–10 min Freely available for academic use 53
Mood rating scale (MRS) 2 1989 Current 6 Visual analog 0–100 per item < 5 min Freely available for research use 201
Multidimensional fatigue inventory‐short version (MFI‐20) 1 1995 3‐days 20 Likert scale 20–100 10 min Freely available for academic use 56
National comprehensive cancer network distress thermometer 6 1998 Current 1 ± problem list 0–10 scale 0–10 < 5 min Freely available 1311
Onco‐geriatric screening tool (G8) 3 2012 3‐months 8 Scored items + disease severity 0–17 < 5 min Freely available 460
Patient health questionnaire 2 (PHQ‐2) 1 1999 2‐weeks 2 Likert scale 0–6 < 5 min Freely available 143
Personal wellbeing index‐audit (PWI‐A) 1 2001 Current 9 Likert scale 0–100 < 5 min Freely available with perission 857
Positive & negative affect schedule short form (PANAS) 3 1988 Past week 20 Likert scale 20–100 5 min Freely available 1058
Problem list 1 2001 Current ∼34 items Checklist Not scored alone < 5 min Used with NCCN distress thermometer 488
Psychological distress inventory (PDI) 1 2003 1‐month 10 Likert scale 10–50 5–10 min Freely available for research use 406
Rotterdam symptom checklist (RSCL) 1 1985 Past week 30 Likert scale 7–28 (Sum of 7 items) 10–15 min Freely available for research use 990
Self‐efficacy for managing chronic disease scale 1 2003 Current 6 Likert scale 06–60 < 5 min Freely available for non‐commercial use 857
Self‐rating anxiety scale (SAS) 1 1971 Past week 20 Likert scale 20–80 < 5 min Freely available 130
Self‐rating depression scale (SDS) 1 1965 Past week 20 Likert scale 20–80 5 min Licensed 130
Sense of coherence short‐version scale 1 1991 Current 13 Likert scale 13–91 5–10 min Freely available for academic use 488
Shortened Warwick‐Edinburgh mental Well‐being scale (SWEMWBS) 1 2008 2012 7 (of original 13) Likert scale 7–35 5–10 min Licensed through Warwick innovations 41
Sickness impact profile (SIP) 1 1970s Current 136 (short form: 68) Yes/No 0–100 20–30 min Licensed 33
Social frailty questionnaire 1 2017 Current 5–9 items Yes/No or likert Varies 5 min Freely available 181
Social support rating scale (SSRS) 2 1982 Current 10 3 subscales, likert/quantitative 12–66 5–10 min Freely available 459
State‐trait anxiety inventory (STAI) 3 1964 Current 20 Likert scale 20–80 10–15 min Licensed (mind Garden inc.) 1012
Symptom checklist‐90 (SCL‐90) 1 1973 1‐week 90 Likert scale 0–360 OR 0–90 10–15 min Licensed 60
The type D scale‐14 (DS‐14) 1 2005 Current 14 Likert scale 0–56 5–10 min Freely available for research 53
Visual analog scale (VAS) 1 1921 Current 1 Numerical/scale 0–10 < 5 min Freely available 130
Open in a new tab

3.4. Nutritional Screening Tools

There were 16 (21%) nutritional screening tools identified. Nutritional screening tools were often brief (1–18 items). However, the more comprehensive screening tools, such as food diaries (30–60 items), required longer to complete.

3.5. Physical Screening Tools

There were 21 (27%) physical screening tools identified. Physical function tools assessed patients' mobility, strength, endurance, and functional independence. These tools varied in administration method and completion time.

3.6. Psychological Screening Tools

Psychological tools made up the largest proportion of single domain tools with 40 (52%) tools identified. Psychological screening tools captured anxiety, depression, resilience, coping, and broader mental health parameters. Anxiety and depression tools were the most common psychological measures with the Hospital Anxiety and Depression Scale (HADS) appearing in 24 studies (60% of psychological domain). However, these tools were rarely the focus of the study and were included in studies evaluating quality of life.

3.7. Format, Administration, and Psychometrics

Screening tools exhibited substantial heterogeneity with respect to development period, format, and administration parameters. Although their initial publication dates span from 1921 (Visual analog scale; VAS) to 2017 (Mini‐Sarcopenia Risk Assessment; MSRA), the majority were introduced between the 1980s and early 2000s. Many have subsequently undergone modification often to create abbreviated versions or to facilitate patient self‐administration (e.g., the Patient‐Generated Subjective Global Assessment short form; PG‐SGA‐SF).

Scoring approaches varied with most tools generating either a continuous numeric score or categorical risk classification, whereas several incorporate domain‐specific subscale scoring. Completion times range from under 5 minutes for concise tools to 60 min for more elaborate assessments. With respect to accessibility, many tools are available without charge; however, a subset required formal licensing agreements or academic permissions. Item counts also demonstrated considerable variability from single‐item scales (e.g., visual analog scale (VAS); National Comprehensive Cancer Network Distress Thermometer; NCCN DT) to extensive questionnaires exceeding one hundred items (e.g., European Prospective Investigation of Cancer food frequency questionnaire; EPIC FFQ).

Notably, only 17 (14%) studies integrated assessments across multiple (i.e., at least two) domains (physical, nutritional, and psychological). Most tools (n = 71, 92%) comprised ≤ 15 questions and required less than 10 minutes to complete. Recall periods varied widely from “point‐in‐time” assessments (e.g., the Malnutrition Universal Screening Tool) to extended dietary recalls of up to 12 months (e.g., European Prospective Investigation of Cancer food frequency questionnaire; EPIC FFQ). However, most tools used a one‐week (46%) or one‐month (28%) recall period. Response formats were predominantly Likert scales (63%) or dichotomous yes/no items (21%) with open‐ended diary formats constituting fewer than 5% of tools. Accessibility was high with 84% of screening tools freely available and 16% requiring licensing or restricted permission.

4. Discussion

This review identifies 77 unique tools from 121 studies. These tools evaluated physical (n = 21), nutritional (n = 16), and psychological (n = 40) domains. Studies originated from 27 countries and were mostly prospective observational cohort studies by design (n = 63, 52%). Although most tools were brief, feasible to self‐administer, and freely accessible, none integrated all three domains within a single tool.

This review demonstrated a wide array of tools but an absence of validated, multidomain, and self‐reported tools for GI cancer surgery. Multidomain screening tools offer several advantages over single‐domain tools. By consolidating assessment across multiple domains into a single screening encounter, these tools may reduce the time and resource burden for both clinicians and patients. Rather than requiring multiple discipline‐specific assessments to be arranged preoperatively, multidomain tools can enable a single point of contact with targeted, discipline‐specific follow‐up initiated only when indicated by screening results. Furthermore, embedding a multidomain screening tool within a hospital model of care facilitates streamlined referral pathways, thereby improving workflow efficiency and optimizing use of healthcare resources. Existing single‐domain tools are typically short, feasible for self‐administration, and often freely available, yet heterogeneously applied and infrequently linked to standardized referral pathways or targeted prehabilitation programs or services.

The predominance of single‐domain screening may reflect the historical separation of perioperative assessment streams. Prehabilitation has matured largely within physical conditioning paradigms with nutrition and psychological care increasingly recognized but unevenly integrated into preoperative pathways [132]. The lack of psychological screening is noteworthy given the well‐described relationships between distress, mood disorders, treatment adherence, and postoperative recovery trajectories [109, 133]. Under‐recognition of psychological distress may adversely affect patients' engagement with prehabilitation and perioperative care contributing to poorer treatment adherence and recovery outcomes [134, 135]. Psychological distress can also impair information processing and participation in shared decision‐making potentially influencing treatment choices and expectations of surgical risk and recovery. Systematic psychological screening may therefore enable earlier identification and targeted referral, mitigating downstream impacts on perioperative outcomes. Similarly, nutritional risk remains highly prevalent in GI cancer and is modifiable, yet screening and referral is not uniformly embedded into models of care [18].

Several clinical implications arise from this study. First, clinicians involved in gastrointestinal cancer surgery should be aware of the fragmented approach to preoperative screening across physical, nutritional, and psychological domains. Although no validated multidomain screening tools comprehensively assess all domains in this population, surgeons, anesthetists, and allied health professionals should ensure that each domain is considered within preoperative assessment pathways given their independent associations with postoperative outcomes. This scoping review may assist multidisciplinary teams in selecting screening tools suited to their local clinical context, considering factors such as tool availability, recall period, time to complete, and response format (Table 2), especially important as prehabilitation is variably implemented as a standard of care and institutions face unique barriers globally [136]. In the absence of prospective evidence supporting specific multidomain tools, flexible and pragmatic screening strategies embedded within surgical models of care are warranted allowing tool selection and referral pathways to evolve as new evidence emerges.

This scoping review comprehensively mapped preoperative screening tools used in adult GI cancer surgery with a pragmatic focus on feasibility and real‐world application. The use of a comprehensive, multi‐database search and inclusion of multiple domains is a strength. However, heterogeneity in outcomes and populations (tumor sites, staging, neoadjuvant therapy), timing of assessment, and outcome definitions prevented pooled analysis and complicates direct comparisons across tools.

Restricting inclusion to English‐language publications and limited timeframes (2000–2025) may have missed tools in languages other than English or those published earlier, although this is unlikely as our search strategy was designed to capture tools used in recent practice (21st century) even if developed previously. Additionally, this study aimed to identify and describe screening tools rather than evaluate tools based on their clinimetric properties. To ensure screening tools effectively identify those at risk, they need to be prospectively tested in the population and setting of interest (i.e., gastrointestinal cancer surgery). To address this limitation, the next phase of this research program involves development of a self‐reported, online screening tool to be assessed through an international cohort study based on findings from this scoping review.

Future studies should validate screening tools to gastrointestinal cancer surgery populations and assess responsiveness and minimal clinically important differences so that clinicians can interpret change scores during prehabilitation. Future work should also examine whether combining domain scores meaningfully improves risk stratification beyond single domains and whether the addition of patient‐reported outcomes enhances the performance of existing clinical risk models. Although multidomain screening tools may improve efficiency by consolidating assessment, the relative contribution of individual domains for identifying high‐risk patients undergoing gastrointestinal cancer surgery remains unclear. This scoping review was not designed to determine the comparative value or weighting of specific screening domains.

In addition, future prospective studies should seek to clarify the relative importance of individual screening domains and identify the minimum essential components required to balance clinical utility with feasibility in routine practice. Consideration should also be given to local service capacity, as longer and more complex tools may require additional time, staffing, digital infrastructure, and patient support, potentially limiting uptake in resource‐constrained settings. Tailoring tool length and mode of administration to center capabilities may therefore be critical for successful implementation.

Implementation research is required to determine how best to integrate screening into surgical pathways, including workflow mapping, role delineation, electronic health record integration, and automated prompts that convert scores to referrals. Given the widespread use of neoadjuvant therapy in GI cancer, studies should determine optimal timing and frequency of screening across treatment and the preoperative period to ensure evolving risks are identified and addressed.

5. Conclusions

This scoping review identified and mapped 77 self‐reported preoperative screening tools spanning physical, nutritional, and psychological domains in adult GI cancer surgical patients. Although most tools were brief, feasible to self‐administer, and freely accessible, none integrated all three domains within a single tool. The absence of a multidomain, psychometrically robust screening tool represents a clear gap. Future research could prioritize the development, validation, and implementation of a concise, multidomain tool to support personalized prehabilitation pathways and optimize surgical outcomes.

Author Contributions

Alexandria Paige Petridis: conceptualization, methodology, formal analysis, data curation, project administration, writing – original draft, writing – review and editing. Jack Reeves: conceptualization, methodology, formal analysis, data curation, project administration, writing – review and editing. Cherry Koh: conceptualization, methodology, writing – review and editing. Michael Solomon: conceptualization, methodology, writing – review and editing. Sascha Karunaratne: conceptualization, methodology, writing – review and editing. Kate Alexander: conceptualization, methodology, writing – review and editing. Nicholas Hirst: conceptualization, methodology, writing – review and editing. Neil Pillinger: conceptualization, methodology, writing – review and editing. Linda Denehy: conceptualization, methodology, writing – review and editing. Bernhard Riedel: conceptualization, methodology, writing – review and editing. Chelsia Gillis: conceptualization, methodology, writing – review and editing. Sharon Carey: conceptualization, methodology, writing – review and editing. Kate McBride: conceptualization, methodology, writing – review and editing. Kate White: conceptualization, methodology, writing – review and editing. Haryana M. Dhillon: conceptualization, methodology, writing – review and editing. Patrick Campbell: conceptualization, methodology, writing – review and editing. Raaj Kishore Biswas: conceptualization, methodology, writing – review and editing. Daniel Steffens: conceptualization, methodology, writing – review and editing.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1

WJS-50-1017-s001.docx (18.1KB, docx)

Acknowledgements

Professor Daniel Steffens is supported by a Cancer Institute of NSW Career Development Fellowship. Open access publishing facilitated by The University of Sydney, as part of the Wiley ‐ The University of Sydney agreement via the Council of Australasian University Librarians.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

  • 1. Bray F., Laversanne M., Sung H., et al., “Global Cancer Statistics 2022: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries,” CA: A Cancer Journal for Clinicians 74, no. 3 (2024): 229–263, 10.3322/caac.21834. [DOI] [PubMed] [Google Scholar]
  • 2. Berkel A. E. M., Bongers B. C., Kotte H., et al., “Effects of Community‐Based Exercise Prehabilitation for Patients Scheduled for Colorectal Surgery With High Risk for Postoperative Complications: Results of a Randomized Clinical Trial,” Annals of Surgery 275, no. 2 (2022): e299–e306, 10.1097/sla.0000000000004702. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Van Kooten R. T., Bahadoer R. R., Peeters K. C. M. J., et al., “Preoperative Risk Factors for Major Postoperative Complications After Complex Gastrointestinal Cancer Surgery: A Systematic Review,” European Journal of Surgical Oncology 47, no. 12 (2021): 3049–3058, 10.1016/j.ejso.2021.07.021. [DOI] [PubMed] [Google Scholar]
  • 4. Schiesser M., Muller S., Kirchhoff P., Breitenstein S., Schäfer M., and Clavien P.‐A., “Assessment of a Novel Screening Score for Nutritional Risk in Predicting Complications in Gastro‐Intestinal Surgery,” Clinical Nutrition 27, no. 4 (2008): 565–570, 10.1016/j.clnu.2008.01.010. [DOI] [PubMed] [Google Scholar]
  • 5. Van Rooijen S., Carli F., Dalton S., et al., “Multimodal Prehabilitation in Colorectal Cancer Patients to Improve Functional Capacity and Reduce Postoperative Complications: The First International Randomized Controlled Trial for Multimodal Prehabilitation,” BMC Cancer 19, no. 1 (2019): 98, 10.1186/s12885-018-5232-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Mizrahi D., Lai J. K. L., Wareing H., et al., “Effect of Exercise Interventions on Hospital Length of Stay and Admissions During Cancer Treatment: A Systematic Review and Meta‐Analysis,” British Journal of Sports Medicine 58, no. 2 (2024): 97–109, 10.1136/bjsports-2023-107372. [DOI] [PubMed] [Google Scholar]
  • 7. Petridis A. P., Koh C., Solomon M., et al., “An Online Preoperative Screening Tool to Optimize Care for Patients Undergoing Cancer Surgery: A Mixed‐Method Study Protocol,” Cancers 17, no. 5 (2025): 861, 10.3390/cancers17050861. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Tricco A. C., Lillie E., Zarin W., et al., “PRISMA Extension for Scoping Reviews (PRISMA‐ScR): Checklist and Explanation,” Annals of Internal Medicine 169, no. 7 (2018): 467–473, 10.7326/m18-0850. [DOI] [PubMed] [Google Scholar]
  • 9. Arksey H. and O'Malley L., “Scoping Studies: Towards a Methodological Framework,” International Journal of Social Research Methodology 8, no. 1 (2005): 19–32, 10.1080/1364557032000119616. [DOI] [Google Scholar]
  • 10. Paez A., “Gray Literature: An Important Resource in Systematic Reviews,” Journal of Evidence‐Based Medicine 10, no. 3 (2017): 233–240, 10.1111/jebm.12266. [DOI] [PubMed] [Google Scholar]
  • 11. Covidence Systematic Review Software, Veritas Health Innovation, www.covidence.org. [Google Scholar]
  • 12. Agasi‐Idenburg S. C., Punt C. J. A., Aaronson N. K., and Stuiver M. M., “The Association Between Preoperative Fatigue and Instrumental Activities in Daily Living With Complications and Length of Hospital Stay in Patients Undergoing Colorectal Surgery,” Aging Clinical and Experimental Research 32, no. 2 (2020): 257EP–264, 10.1007/s40520-019-01199-2. [DOI] [PubMed] [Google Scholar]
  • 13. Al‐Bayyari N., Hailat M., and Baylin A., “Gender‐Specific Malnutrition and Muscle Depletion in Gastric and Colorectal Cancer: Role of Dietary Intake in a Jordanian Cohort,” Nutrients 16, no. 23 (2024): 4000, 10.3390/nu16234000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Almasaudi A. S., McSorley S. T., Dolan R. D., Edwards C. A., and McMillan D. C., “The Relation Between Malnutrition Universal Screening Tool (MUST), Computed Tomography‐Derived Body Composition, Systemic Inflammation, and Clinical Outcomes in Patients Undergoing Surgery for Colorectal Cancer,” American Journal of Clinical Nutrition 110, no. 6 (2019): 1327–1334, 10.1093/ajcn/nqz230. [DOI] [PubMed] [Google Scholar]
  • 15. Andrew E., Bhimani N., Smith G., et al., “Preoperative Nutrition: How Well Are We Screening? An Audit of Preoperative Nutritional Screening Practices in High‐Risk Gastrointestinal Surgical Patients,” Journal of Gastroenterology and Hepatology 37 (2022): 222EP–223, 10.1111/jgh.15957. [DOI] [Google Scholar]
  • 16. Berstad P., Haugum B., Helgeland M., Bukholm I., and Almendingen K., “Preoperative Body Size and Composition, Habitual Diet, and Post‐Operative Complications in Elective Colorectal Cancer Patients in Norway,” Journal of Human Nutrition and Dietetics: The Official Journal of the British Dietetic Association 26, no. 4 (2013): 359–368, 10.1111/jhn.12002. [DOI] [PubMed] [Google Scholar]
  • 17. Budzynski J., Czarnecki D., Ziolkowski M., et al., “Higher Preoperative Serum Neuropeptide Y Concentration May Be Associated With a Better Prognosis After Surgery for Colorectal Cancer,” Nutrients 16, no. 22 (2024): 3825, 10.3390/nu16223825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Burden S. T., Hill J., Shaffer J. L., and Todd C., “Nutritional Status of Preoperative Colorectal Cancer Patients,” Journal of Human Nutrition and Dietetics: The Official Journal of the British Dietetic Association 23, no. 4 (2010): 402–407, 10.1111/j.1365-277X.2010.01070.x. [DOI] [PubMed] [Google Scholar]
  • 19. Casirati A., Baia M., Vandoni G., et al., “Risk of Misclassification During Diagnosis of Malnutrition in Retroperitoneal Sarcoma Patients,” Clinical Nutrition ESPEN 49 (2022): 459–465, 10.1016/j.clnesp.2022.02.125. [DOI] [PubMed] [Google Scholar]
  • 20. Chen J., Hong C., Chen R., Zhou M., and Lin S., “Prognostic Impact of a 3‐week Multimodal Prehabilitation Program on Frail Elderly Patients Undergoing Elective Gastric Cancer Surgery: A Randomized Trial,” BMC Gastroenterology 24, no. 1 (2024): 403, 10.1186/s12876-024-03490-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Chi J., Yin S., Zhu Y., et al., “A Comparison of the Nutritional Risk Screening 2002 Tool With the Subjective Global Assessment Tool to Detect Nutritional Status in Chinese Patients Undergoing Surgery With Gastrointestinal Cancer,” Gastroenterology Nursing: The Official Journal of the Society of Gastroenterology Nurses and Associates 40, no. 1 (2017): 19–25, 10.1097/SGA.0000000000000157. [DOI] [PubMed] [Google Scholar]
  • 22. Chwesiuk M., Kimilu N., Kulesza A., et al., “Disturbances in Nutritional Status and Poor Eating Habits in Patients With Colorectal Cancer Qualified for Surgical Treatment,” Clinical Nutrition ESPEN 58 (2023): 533, 10.1016/j.clnesp.2023.09.319. [DOI] [Google Scholar]
  • 23. Dias Rodrigues V., Barroso De Pinho N., Abdelhay E., Viola J. P. B., Correia M. I., and Brum Martucci R., “Nutrition and Immune‐Modulatory Intervention in Surgical Patients With Gastric Cancer,” Nutrition in Clinical Practice 32, no. 1 (2017): 122EP–129, 10.1177/0884533616653807. [DOI] [PubMed] [Google Scholar]
  • 24. Dou L., Wang X., Cao Y., Hu A., and Li Li, “Relationship Between Postoperative Recovery and Nutrition Risk Screened by NRS 2002 and Nutrition Support Status in Patients With Gastrointestinal Cancer,” Nutrition and Cancer 72, no. 1 (2020): 33–40, 10.1080/01635581.2019.1612927. [DOI] [PubMed] [Google Scholar]
  • 25. Driessens H., van Wijk L., Buis C. I., and Klaase J. M., “Low Health Literacy Is Associated With Worse Postoperative Outcomes Following Hepato‐Pancreato‐Biliary Cancer Surgery,” HPB 24, no. 11 (2022): 1869EP–1877, 10.1016/j.hpb.2022.07.006. [DOI] [PubMed] [Google Scholar]
  • 26. Dubey H. K., Thumma V. M., Gunturi S. R. V., et al., “To Assess the Effect of Preoperative Nutritional Status on Early Post‐Operative Outcomes After Surgery for Hepato‐Pancreato‐Biliary Malignancy,” International Journal of Medicine and Public Health 14 (2024): 526EP–537, 10.70034/ijmedph.2024.3.95. [DOI] [Google Scholar]
  • 27. Elsherbini N., Tahasildar B., Sangarapillai T., et al., “Under‐ Not Over‐Nutrition Is Associated With Adverse Outcomes in Cancer Surgery,” Clinical Nutrition ESPEN 63 (2024): 1143, 10.1016/j.clnesp.2024.07.523. [DOI] [Google Scholar]
  • 28. Fukuda Y., Yamamoto K., Hirao M., et al., “Sarcopenia Is Associated With Severe Postoperative Complications in Elderly Gastric Cancer Patients Undergoing Gastrectomy,” Gastric Cancer: Official Journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association 19, no. 3 (2016): 986–993, 10.1007/s10120-015-0546-4. [DOI] [PubMed] [Google Scholar]
  • 29. Fulop A., Lakatos L., Susztak N., Szijarto A., and Banky B., “The Effect of Trimodal Prehabilitation on the Physical and Psychological Health of Patients Undergoing Colorectal Surgery: A Randomised Clinical Trial,” Anaesthesia 76, no. 1 (2021): 82–90, 10.1111/anae.15215. [DOI] [PubMed] [Google Scholar]
  • 30. Gillis C., Nguyen T. H., Liberman A. S., and Carli F., “Nutrition Adequacy in Enhanced Recovery After Surgery: A Single Academic Center Experience,” Nutrition in Clinical Practice 30, no. 3 (2015): 414EP–419, 10.1177/0884533614562840. [DOI] [PubMed] [Google Scholar]
  • 31. Gillis C., Fenton T. R., Gramlich L., et al., “Malnutrition Modifies the Response to Multimodal Prehabilitation: A Pooled Analysis of Prehabilitation Trials,” Applied Physiology, Nutrition, and Metabolism = Physiologie Appliquee, Nutrition et Metabolisme 47, no. 2 (2022): 141–150, 10.1139/apnm-2021-0299. [DOI] [PubMed] [Google Scholar]
  • 32. Guinan E. M., Doyle S. L., Bennett A. E., et al., “Sarcopenia During Neoadjuvant Therapy for Oesophageal Cancer: Characterising the Impact on Muscle Strength and Physical Performance,” Supportive Care in Cancer 26 (2018): 1569EP–1576, 10.1007/s00520-017-3993-0. [DOI] [PubMed] [Google Scholar]
  • 33. Guo W., Ou G., Li X., Huang J., Liu J., and Wei H., “Screening of the Nutritional Risk of Patients With Gastric Carcinoma Before Operation by NRS 2002 and Its Relationship With Postoperative Results,” Journal of Gastroenterology and Hepatology 25, no. 4 (2010): 800–803, 10.1111/j.1440-1746.2009.06198.x. [DOI] [PubMed] [Google Scholar]
  • 34. Heckler M., Klaiber U., Huttner F. J., et al., “Prospective Trial to Evaluate the Prognostic Value of Different Nutritional Assessment Scores for Survival in Pancreatic Ductal Adenocarcinoma (NURIMAS Pancreas SURVIVAL),” Journal of Cachexia, Sarcopenia and Muscle 12, no. 6 (2021): 1940EP–1947, 10.1002/jcsm.12796. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Hsueh S. W., Liu K. H., Hung C. Y., et al., “Predicting Postoperative Events in Patients With Gastric Cancer: A Comparison of Five Nutrition Assessment Tools,” In Vivo 34, no. 5 (2020): 2803EP–2809, 10.21873/invivo.12106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Hua X. H., Shi K. F., Yu Y. K., et al., “Nutritional Assessment in Esophageal Fast‐Track Surgery: Comparisons of 4 Objective Malnutrition Screening Tools,” Annals of Translational Medicine 10, no. 1 (2022): 20, 10.21037/atm-21-6383. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Huang D. D., Cai H. Y., Chen X. Y., et al., “Research Paper Value of Sarcopenia Defined by the New EWGSOP2 Consensus for the Prediction of Postoperative Complications and Long‐Term Survival After Radical Gastrectomy for Gastric Cancer: A Comparison With Four Common Nutritional Screening Tools,” Journal of Cancer 11 (2020): 5852EP–5860, 10.7150/jca.49815. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Karanikki E., Frountzas M., Lidoriki I., et al., “The Predictive Role of Preoperative Malnutrition Assessment in Postoperative Outcomes of Patients Undergoing Surgery Due to Gastrointestinal Cancer: A Cross‐Sectional Observational Study,” Journal of Clinical Medicine 13, no. 23 (2024): 7479, 10.3390/jcm13237479. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Karin M., Bogut A., Hojsak I., Babić E., Volarić M., and Bevanda M., “Nutritional Status and Its Effect on Complications in Patients With Colorectal Cancer,” Wiener Klinische Wochenschrift 132, no. 15–16 (2020): 431EP–437, 10.1007/s00508-020-01671-4. [DOI] [PubMed] [Google Scholar]
  • 40. Karlsson S., Andersson L., and Berglund B., “Early Assessment of Nutritional Status in Patients Scheduled for Colorectal Cancer Surgery,” Gastroenterology Nursing: The Official Journal of the Society of Gastroenterology Nurses and Associates 32, no. 4 (2009): 265–270, 10.1097/SGA.0b013e3181aead68. [DOI] [PubMed] [Google Scholar]
  • 41. Kim E., Jang J. Y., Han Y., Kim J., Kwon W., and Kim S.‐W., “Effects of Nutritional Status on Function and Clinical Outcomes in Elderly Patients With Periampullary Neoplasm,” HPB 20 (2018): S612, 10.1016/j.hpb.2018.06.2162. [DOI] [Google Scholar]
  • 42. Klassen P., Baracos V., Gramlich L., Nelson G., Mazurak V., and Martin L., “Computed‐Tomography Body Composition Analysis Complements Pre‐Operative Nutrition Screening in Colorectal Cancer Patients on an Enhanced Recovery After Surgery Pathway,” Nutrients 12 (2020): 3745, 10.3390/nu12123745. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Kollar D., Benedek‐Toth Z., Drozgyik A., Molnár T. F., and Oláh A., “To Feed or Not to Feed—Nutritional Risk Assessment and Support in Elective Colorectal Surgery. A Prospective Study on the Effect of Screening,” Nutrition and Cancer 74, no. 10 (2022): 3509–3517, 10.1080/01635581.2022.2077384. [DOI] [PubMed] [Google Scholar]
  • 44. Kopuz T. N. Y., Er S., Yildiz H. F., and Fisunoğlu M., “The Effect of Preoperative Nutritional Status on Postoperative Complications in Colorectal Cancer,” Clinical Nutrition ESPEN 58 (2023): 500EP–501, 10.1016/j.clnesp.2023.09.224. [DOI] [Google Scholar]
  • 45. Lazaro L., Diaz L., Monge P., et al., “A Nutrition Program Implemented Within the Enhanced Recovery After Surgery (ERAS) Program for Colorectal Surgery Has Been Shown to Equalize Postoperative Outcomes and Hospital Stay Between Malnourished and Well‐Nourished Patients,” Clinical Nutrition ESPEN 58 (2023): 749EP–750, 10.1016/j.clnesp.2023.09.913. [DOI] [Google Scholar]
  • 46. Lewicka M., Nartowicz M., Soban?ska A., et al., “The Impact of Preoperative Nutritional Support in Patients With Gastrointestinal Cancer Qualified for Surgery for Early Treatment Results,” Clinical Nutrition 38 (2019): S87, 10.1016/S0261-5614(19)32710-4. [DOI] [Google Scholar]
  • 47. Lidoriki I., Schizas D., Mylonas K. S., et al., “Postoperative Changes in Nutritional and Functional Status of Gastroesophageal Cancer Patients,” Journal of the American Nutrition Association 41, no. 3 (2022): 301EP–309, 10.1080/07315724.2021.1880986. [DOI] [PubMed] [Google Scholar]
  • 48. Loh K. W., Vriens M. R., Gerritsen A., et al., “Unintentional Weight Loss Is the Most Important Indicator of Malnutrition Among Surgical Cancer Patients,” Netherlands Journal of Medicine 70, no. 8 (2012): 365–369. [PubMed] [Google Scholar]
  • 49. Lu J. L., Xu X. Y., Chen L., et al., “The Predictive Values of Five Sarcopenia Screening Tools on Clinical Outcomes Following Surgery in Patients With Gastric Cancer: A Prospective Cohort Study,” Journal of Nutrition, Health & Aging 26, no. 3 (2022): 259–265, 10.1007/s12603-022-1751-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Lu J.‐L., Xu Q., Zhu S.‐Q., et al., “Comparison of Five Sarcopenia Screening Tools in Preoperative Patients With Gastric Cancer Using the Diagnostic Criteria of the European Working Group on Sarcopenia in Older People 2,” Nutrition 95 (2022): 111553, 10.1016/j.nut.2021.111553. [DOI] [PubMed] [Google Scholar]
  • 51. Niemelainen S., Huhtala H., Jamsen E., et al., “One‐Year Functional Outcomes of Patients Aged 80 Years or More Undergoing Colonic Cancer Surgery: Prospective, Multicentre Observational Study,” BJS Open 6, no. 4 (2022): zrac094, 10.1093/bjsopen/zrac094. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Noh J. H., Na H. K., Kim Y.‐H., et al., “Influence of Preoperative Nutritional Status on Patients Who Undergo Upfront Surgery for Esophageal Squamous Cell Carcinoma,” Nutrition and Cancer 74, no. 8 (2022): 2910–2919, 10.1080/01635581.2022.2042573. [DOI] [PubMed] [Google Scholar]
  • 53. Oikonomou D., Florou E., Prassas E., Srinivasan P., Prachalias A., and Amoako D., “New Technologies for Prehabilitation Prior to Major Hepatopancreatobiliary Resections,” HPB 26 (2024): S515, 10.1016/j.hpb.2024.03.1092. [DOI] [Google Scholar]
  • 54. Pellegrinelli A., Mancin S., Brolese A., et al., “Impact of Preoperative Malnutrition on Patients With Pancreatic Neoplasms Post‐duodenopancreatectomy: A Retrospective Cohort Study,” Nutrients 16, no. 12 (2024): 1839, 10.3390/nu16121839. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Reisinger K. W., van Vugt J. L. A., Tegels J. J. W., et al., “Functional Compromise Reflected by Sarcopenia, Frailty, and Nutritional Depletion Predicts Adverse Postoperative Outcome After Colorectal Cancer Surgery,” Annals of Surgery 261, no. 2 (2015): 345–352, 10.1097/SLA.0000000000000628. [DOI] [PubMed] [Google Scholar]
  • 56. Ryu S. W. and Kim I. H., “Comparison of Different Nutritional Assessments in Detecting Malnutrition Among Gastric Cancer Patients,” World Journal of Gastroenterology 16, no. 26 (2010): 3310–3317, 10.3748/wjg.v16.i26.3310. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Tu M.‐Y., Chien T.‐W., and Chou M.‐T., “Using a Nutritional Screening Tool to Evaluate the Nutritional Status of Patients With Colorectal Cancer,” Nutrition and Cancer 64, no. 2 (2012): 323–330, 10.1080/01635581.2012.650778. [DOI] [PubMed] [Google Scholar]
  • 58. van der Kroft G., Bours D. M. J. L., Janssen‐Heijnen D. M., van Berlo Dr C. L. H., and Konsten Dr J. L. M., “Value of Sarcopenia Assessed by Computed Tomography for the Prediction of Postoperative Morbidity Following Oncological Colorectal Resection: A Comparison With the Malnutrition Screening Tool,” Clinical Nutrition ESPEN 24 (2018): 114–119, 10.1016/j.clnesp.2018.01.003. [DOI] [PubMed] [Google Scholar]
  • 59. van Wijk L., van der Snee L., Buis C. I., Hentzen J. E. K. R., Haveman M. E., and Klaase J. M., “A Prospective Cohort Study Evaluating Screening and Assessment of Six Modifiable Risk Factors in HPB Cancer Patients and Compliance to Recommended Prehabilitation Interventions,” Perioperative Medicine 10, no. 1 (2021): 5, 10.1186/s13741-020-00175-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60. Wang S.‐L., Zhuang C.‐L., Huang D.‐D., et al., “Sarcopenia Adversely Impacts Postoperative Clinical Outcomes Following Gastrectomy in Patients With Gastric Cancer: A Prospective Study,” Annals of Surgical Oncology 23, no. 2 (2016): 556–564, 10.1245/s10434-015-4887-3. [DOI] [PubMed] [Google Scholar]
  • 61. Wang R., Cai H., Li Y., Chen C., and Cui Y., “Impact Exerted by Nutritional Risk Screening on Clinical Outcome of Patients With Esophageal Cancer,” BioMed Research International 2018 (2018): 1–5, 10.1155/2018/7894084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. Wang P., Chen X., Liu Q., and Li Y., “Good Performance of the Global Leadership Initiative on Malnutrition Criteria for Diagnosing and Classifying Malnutrition in People With Esophageal Cancer Undergoing Esophagectomy,” Nutrition 91–92 (2021): 111420, 10.1016/j.nut.2021.111420. [DOI] [PubMed] [Google Scholar]
  • 63. Wijma A. G., Hogenbirk R. N. M., Driessens H., et al., “Nutritional Support in Pancreatic Cancer Patients and Its Effect on Nutritional Status: An Observational Regional HPB Network Study Investigating Current Practice,” Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer 32, no. 7 (2024): 487, 10.1007/s00520-024-08683-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Wobith M. and Weimann A., “Malnutrition Screening With NRS‐2002 Prior to Assessment as Part of Glim Criteria in Patients Undergoing Major Abdominal Surgery for Gastrointestinal Cancer,” Clinical Nutrition ESPEN 58 (2023): 446, 10.1016/j.clnesp.2023.09.066. [DOI] [PubMed] [Google Scholar]
  • 65. Yang H. Y., Shun S. C., Chou Y. J., et al., “Trajectories of Perioperative Nutritional Status and Related Factors in Individuals With Pancreatic Tumor Receiving Surgery,” Supportive Care in Cancer 30 (2022): S85, 10.1007/s00520-022-07099-y. [DOI] [Google Scholar]
  • 66. Yang F., Yuan Y., Liu W., et al., “Effect of Prehabilitation Exercises on Postoperative Frailty in Patients Undergoing Laparoscopic Colorectal Cancer Surgery,” Frontiers in Oncology 14 (2024): 1411353, 10.3389/fonc.2024.1411353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67. Yeung S. E., Hilkewich L., Gillis C., Heine J. A., and Fenton T. R., “Protein Intakes Are Associated With Reduced Length of Stay: A Comparison Between Enhanced Recovery After Surgery (ERAS) and Conventional Care After Elective Colorectal Surgery,” American Journal of Clinical Nutrition 106, no. 1 (2017): 44–51, 10.3945/ajcn.116.148619. [DOI] [PubMed] [Google Scholar]
  • 68. Yong R. and Jiang L., “Predicative Factors and Development of a Nomogram for Postoperative Delayed Neurocognitive Recovery in Elderly Patients With Gastric Cancer,” Aging Clinical and Experimental Research 35, no. 7 (2023): 1497EP–1504, 10.1007/s40520-023-02422-x. [DOI] [PubMed] [Google Scholar]
  • 69. Yoon S., “A Comparison of Perioperative Nutritional Status Among Patients With Surgically Curable Gastric or Colorectal Cancer: A Propensity Score‐Matched Analysis,” Diseases of the Colon & Rectum 61 (2018): e247EP–e248, 10.1097/DCR.0000000000001104. [DOI] [Google Scholar]
  • 70. Zhang Q., Yu S., Li Q., Zhang M., Meng L., and Hu S., “Preoperative Nutritional Status in Elderly Inpatients With Gastrointestinal Cancer and Its Linear Association With Frailty,” Nutrition and Cancer 74, no. 4 (2022): 1376–1387, 10.1080/01635581.2021.1955284. [DOI] [PubMed] [Google Scholar]
  • 71. Zhang Y. and Zhu Y., “Development and Validation of Risk Prediction Model for Sarcopenia in Patients With Colorectal Cancer,” Frontiers in Oncology 13 (2023): 1172096, 10.3389/fonc.2023.1172096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72. Zhou B., Song Y., Chen C., Chen X., and Tao T., “Preoperative Prediction of Sarcopenia in Patients Scheduled for Gastric and Colorectal Cancer Surgery,” Journal of Gastrointestinal Cancer 56, no. 1 (2025): 82, 10.1007/s12029-025-01206-y. [DOI] [PubMed] [Google Scholar]
  • 73. Ainsworth H., Veal I., Peat N., Wills A., Ralston C., and Bidd H., “Evaluating the Effects of a Multi‐Modal Prehabilitation Service, on Functional and Patient Reported Outcomes Prior to Surgery for Colorectal Cancer,” Physiotherapy 123 (2024): e29EP–e30, 10.1016/j.physio.2024.04.037. [DOI] [Google Scholar]
  • 74. Bae S. U., Jeong W. K., and Baek S. K., “Impact of the Preoperative SARC‐F Score on Clinical Outcomes Following Curative Resection for Colorectal Cancer,” Clinical Nutrition ESPEN 58 (2023): 703, 10.1016/j.clnesp.2023.09.806. [DOI] [Google Scholar]
  • 75. Cassini D., Clementi S., Colletti G., Cortellazzi P., and Baldazzi G., “ERAS Prehabilitation in ‘Low Budget’ Era. ‘Where There's a Well, There's a Way,” Clinical Nutrition ESPEN 31 (2019): 140EP–141, 10.1016/j.clnesp.2019.03.124. [DOI] [Google Scholar]
  • 76. Chen B. P., Awasthi R., Sweet S. N., et al., “Four‐Week Prehabilitation Program Is Sufficient to Modify Exercise Behaviors and Improve Preoperative Functional Walking Capacity in Patients With Colorectal Cancer,” Supportive Care in Cancer 25, no. 1 (2017): 33EP–40, 10.1007/s00520-016-3379-8. [DOI] [PubMed] [Google Scholar]
  • 77. Dronkers J. J., Lamberts H., Reutelingsperger I. M. M., et al., “Preoperative Therapeutic Programme for Elderly Patients Scheduled for Elective Abdominal Oncological Surgery: A Randomized Controlled Pilot Study,” Clinical Rehabilitation 24, no. 7 (2010): 614–622, 10.1177/0269215509358941. [DOI] [PubMed] [Google Scholar]
  • 78. Gray P. J., Goldwag J., Eid M., et al., “Does Long‐Term Bowel Function Change After Colectomy for Colon Malignancy?,” Diseases of the Colon & Rectum 63 (2020): e440, 10.1016/j.jss.2023.06.041. [DOI] [Google Scholar]
  • 79. Hernon J., Saxton J., Jones M., et al., “Supportive Exercise Programmes for Accelerating Recovery After Major Abdominal Cancer Surgery Trial (PREPARE‐ABC): Pilot Phase of a Multicentre Randomised Controlled Trial,” Colorectal Disease 23 (2021): 3008EP–3022, 10.1111/codi.15856. [DOI] [PubMed] [Google Scholar]
  • 80. Iwakura M., Kawagoshi A., Furukawa Y., et al., “Association of Health Literacy With Short‐Term Postoperative Outcomes in Older Adult Patients With Abdominal Tumors Undergoing Surgery and Perioperative Rehabilitation Program: A Prospective Cohort Study,” Journal of Geriatric Oncology 14, no. 2 (2023): 101422, 10.1016/j.jgo.2022.101422. [DOI] [PubMed] [Google Scholar]
  • 81. Karlsson E., Franzen E., Nygren‐Bonnier M., Bergenmar M., and Rydwik E., “Short‐Term Postoperative Physical Decline and Patient‐Reported Recovery in People Aged 70 or Older Undergoing Abdominal Cancer Resection‐ A Prospective Cohort Study,” Journal of Geriatric Oncology 10, no. 4 (2019): 610–617, 10.1016/j.jgo.2019.01.004. [DOI] [PubMed] [Google Scholar]
  • 82. Kim Y. J., Bae S. U., Kim K. E., Jeong W. K., and Baek S. K., “Effects of the Strength, Assistance in Walking, Rise From a Chair, Climb Stairs, and Falls Score on Postoperative Clinical Outcomes Following Colorectal Cancer Surgery: A Retrospective Study,” European Journal of Clinical Nutrition 79, no. 4 (2025): 358–364, 10.1038/s41430-024-01509-6. [DOI] [PubMed] [Google Scholar]
  • 83. Komatsu H., Watanuki S., Koyama Y., et al., “Nurse Counseling for Physical Activity in Patients Undergoing Esophagectomy,” Gastroenterology Nursing 41, no. 3 (2018): 233–239, 10.1097/SGA.0000000000000252. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84. Le Quang A. T., Carli F., and Prince F., “Is Preoperative Physical Function Testing Predictive of Length of Stay in Patients With Colorectal Cancer? A Retrospective Study,” European Journal of Surgical Oncology: the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology 49, no. 10 (2023): 106956, 10.1016/j.ejso.2023.06.008. [DOI] [PubMed] [Google Scholar]
  • 85. Lin K.‐Y., Denehy L., Frawley H. C., Wilson L., and Granger C. L., “Pelvic Floor Symptoms, Physical, and Psychological Outcomes of Patients Following Surgery for Colorectal Cancer,” Physiotherapy Theory and Practice 34, no. 6 (2018): 442–452, 10.1080/09593985.2017.1422165. [DOI] [PubMed] [Google Scholar]
  • 86. Meyers P. M., Leeds I. L., Enumah Z. O., et al., “Missed Psychosocial Risk Factors During Routine Preoperative Evaluations Are Associated With Increased Complications After Elective Cancer Surgery,” Surgery 166, no. 2 (2019): 177EP–183, 10.1016/j.surg.2019.04.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87. Ngo‐Huang A., Parker N., Martinez V. A., et al., “Feasibility of a Prehabilitation Program for Patients With Potentially Resectable Pancreatic Cancer: Pilot Study,” supplement, PM and R 8, no. 9S (2016): S183, 10.1016/j.pmrj.2016.07.111. [DOI] [PubMed] [Google Scholar]
  • 88. Ngo‐Huang A., Parker N. H., Bruera E., et al., “Home‐Based Exercise Prehabilitation During Preoperative Treatment for Pancreatic Cancer is Associated With Improvement in Physical Function and Quality of Life,” Integrative Cancer Therapies 18 (2019): 1534735419894061, 10.1177/1534735419894061. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 89. Olsson U., Bosaeus I., Svedlund J., and Bergbom I., “Patients' Subjective Symptoms, Quality of Life and Intake of Food During the Recovery Period 3 and 12 Months After Upper Gastrointestinal Surgery,” European Journal of Cancer Care 16, no. 1 (2007): 74–85, 10.1111/j.1365-2354.2006.00709.x. [DOI] [PubMed] [Google Scholar]
  • 90. Onerup A., Angenete E., Bonfre P., et al., “Self‐Assessed Preoperative Level of Habitual Physical Activity Predicted Postoperative Complications After Colorectal Cancer Surgery: A Prospective Observational Cohort Study,” European Journal of Surgical Oncology: The Journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology 45, no. 11 (2019): 2045–2051, 10.1016/j.ejso.2019.06.019. [DOI] [PubMed] [Google Scholar]
  • 91. Parker N. H., Lee R. E., O'Connor D. P., et al., “Supports and Barriers to Home‐Based Physical Activity During Preoperative Treatment of Pancreatic Cancer: A Mixed‐Methods Study,” Journal of Physical Activity and Health 16, no. 12 (2019): 1113–1122, 10.1123/jpah.2019-0027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92. Pecorelli N., Fiore J. F. Jr., Gillis C., et al., “The Six‐Minute Walk Test as a Measure of Postoperative Recovery After Colorectal Resection: Further Examination of Its Measurement Properties,” Surgical Endoscopy 30, no. 6 (2016): 2199–2206, 10.1007/s00464-015-4478-1. [DOI] [PubMed] [Google Scholar]
  • 93. Pecorelli N., Guarneri G., Di Salvo F., et al., “The Impact of Postoperative Complications on Recovery of Health‐Related Quality of Life and Functional Capacity After Pancreatectomy: Findings From a Prospective Observational Study,” Annals of Surgery 280, no. 5 (2024): 719–727, 10.1097/SLA.0000000000006472. [DOI] [PubMed] [Google Scholar]
  • 94. Collaborative P.‐A. T., “Supportive Exercise Programmes for Accelerating Recovery After Major Abdominal Cancer Surgery Trial (PREPARE‐ABC): Pilot Phase of a Multicentre Randomised Controlled Trial,” Colorectal Disease 23, no. 11 (2021): 3008–3022, 10.1111/codi.15856. [DOI] [PubMed] [Google Scholar]
  • 95. Reinwalds M., Larsson C., Gronkvist R., and Angenete E., “Patient Reported Experiences of Health Care, Quality of Life and Preoperative Information in Colon Cancer,” Acta Oncologica 63 (2024): 893EP–900, 10.2340/1651-226X.2024.40933. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96. St‐Pierre J., Carli F., and Scheede‐Bergdahl C., “Should Colorectal Cancer Prehabilitation Be Personalized Based on Sex?,” European Journal of Surgical Oncology 48, no. 2 (2022): e113, 10.1016/j.ejso.2021.12.188. [DOI] [Google Scholar]
  • 97. van Zutphen M., Winkels R. M., van Duijnhoven F. J. B., et al., “An Increase in Physical Activity After Colorectal Cancer Surgery Is Associated With Improved Recovery of Physical Functioning: A Prospective Cohort Study,” BMC Cancer 17, no. 1 (2017): 74, 10.1186/s12885-017-3066-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 98. Yanagisawa T., Tatematsu N., Horiuchi M., et al., “Preoperative Physical Activity Predicts Postoperative Functional Recovery in Gastrointestinal Cancer Patients,” Disability & Rehabilitation 44, no. 19 (2022): 5557–5562, 10.1080/09638288.2021.1939447. [DOI] [PubMed] [Google Scholar]
  • 99. Zhang X.‐D., Zhao Q.‐Y., Fang Y., et al., “Perioperative Comprehensive Supportive Care Interventions for Chinese Patients With Esophageal Carcinoma: A Prospective Study,” Asian Pacific Journal of Cancer Prevention: Asian Pacific Journal of Cancer Prevention 14, no. 12 (2013): 7359–7366, 10.7314/apjcp.2013.14.12.7359. [DOI] [PubMed] [Google Scholar]
  • 100. Acher A., Genrich T., Dautermann K., et al., “Gi Cancer Patient Distress: How Does It Change Throughout the Perioperative Period?,” Gastroenterology 158 (2020): SEP–1562, 10.1016/S0016-5085(20)34587-X. [DOI] [Google Scholar]
  • 101. Antoniadis D., Giakoustidis A., Paramythiotis D., Michalopoulos A., Mandanas Z. N., and Papadopoulos V. N., “Mental Health Well‐Being and Functional Adjustment in Colorectal Cancer Patients: A Prospective Cohort Study,” Acta Chirurgica Belgica 124, no. 1 (2024): 20–27, 10.1080/00015458.2022.2145725. [DOI] [PubMed] [Google Scholar]
  • 102. Baoyindeligeer Z. L., “Rehabilitation and Quality of Life Improvement of Patients With Esophageal Carcinoma Surgery by Psychological Intervention,” International Journal of Clinical and Experimental Medicine 13 (2020): 1299EP–1306. [Google Scholar]
  • 103. Bott R., Zylstra J., Knight W., et al., “Prehabilitation of Patients With Oesophageal Malignancy Undergoing Peri‐Operative Treatment (Pre‐EMPT): Outcomes From a Prospective Controlled Trial,” Journal of Surgical Oncology 131, no. 8 (2025): 1508–1520, 10.1002/jso.28079. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104. Calman L., Turner J., Permyakova N. V., et al., “Prevalence and Determinants of Depression up to 5 Years After Colorectal Cancer Surgery: Results From the Colorectal Wellbeing (CREW) Study,” Colorectal Disease 23 (2021): 3234EP–3250, 10.1111/codi.15949. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 105. Ding L., Miao X., Jiang X., et al., “Adverse Outcomes and Health‐Ecological Influencing Factors of Preoperative Frailty Among Elderly Patients With Gastric Cancer,” Journal of Cancer Research and Clinical Oncology 149, no. 10 (2023): 7043EP–7051, 10.1007/s00432-023-04651-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 106. Foster C., Haviland J., Winter J., et al., “Pre‐Surgery Depression and Confidence to Manage Problems Predict Recovery Trajectories of Health and Wellbeing in the First Two Years Following Colorectal Cancer: Results From the CREW Cohort Study,” PLoS One 11, no. 5 (2016): e0155434, 10.1371/journal.pone.0155434. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 107. Fujita T., Nagayama A., and Anazawa S., “Circulating Alpha‐2‐Macroglobulin Levels and Depression Scores in Patients Who Underwent Abdominal Cancer Surgery,” Journal of Surgical Research 114, no. 1 (2003): 90–94, 10.1016/s0022-4804(03)00194-x. [DOI] [PubMed] [Google Scholar]
  • 108. Glass A., Monroe M., and Davies C., “The Effect of a Multidisciplinary Stoma Team on Anxiety and Distress in Patients Undergoing Colorectal Stoma Surgery,” Journal of Oncology Navigation & Survivorship 13 (2022): 212–215. [Google Scholar]
  • 109. Gonzalez‐Saenz de Tejada M., Bilbao A., Bare M., et al., “Association Between Social Support, Functional Status, and Change in Health‐Related Quality of Life and Changes in Anxiety and Depression in Colorectal Cancer Patients,” Psycho‐Oncology 26, no. 9 (2017): 1263–1269, 10.1002/pon.4303. [DOI] [PubMed] [Google Scholar]
  • 110. Hao Law J., Lau J., Pang N. Q., et al., “Preoperative Quality of Life and Mental Health Can Predict Postoperative Outcomes and Quality of Life After Colorectal Cancer Surgery,” Gut and Liver 16, no. 6 (2022): 123, 10.3390/medicina59061129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 111. Hong J., Wei Z., and Wang W., “Preoperative Psychological Distress, Coping and Quality of Life in Chinese Patients With Newly Diagnosed Gastric Cancer,” Journal of Clinical Nursing 24, no. 17–18 (2015): 2439–2447, 10.1111/jocn.12816. [DOI] [PubMed] [Google Scholar]
  • 112. Jakobsson J., Idvall E., and Wann‐Hansson C., “General Health and State Anxiety in Patients Recovering From Colorectal Cancer Surgery,” Journal of Advanced Nursing 72, no. 2 (2016): 328–338: John Wiley & Sons, Inc, 10.1111/jan.12841. [DOI] [PubMed] [Google Scholar]
  • 113. Law J.‐H., Lau J., Pang N.‐Q., et al., “Preoperative Quality of Life and Mental Health Can Predict Postoperative Outcomes and Quality of Life After Colorectal Cancer Surgery,” Medicina (Kaunas, Lithuania) 59, no. 6 (2023): 1129, 10.3390/medicina59061129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 114. Li Y., Liu B., and Zhou Z., “Trimodal Prehabilitation Program Improves the Physical and Psychological Status for Elderly Patients Underwent Colorectal Surgery for Cancer,” Journal of Parenteral and Enteral Nutrition 45 (2021): S16, 10.1002/jpen.2095. [DOI] [Google Scholar]
  • 115. Liedman B., Svedlund J., Sullivan M., Larsson L., and Lundell L., “Symptom Control May Improve Food Intake, Body Composition, and Aspects of Quality of Life After Gastrectomy in Cancer Patients,” Digestive Diseases and Sciences 46, no. 12 (2001): 2673–2680, 10.1023/a:1012719211349. [DOI] [PubMed] [Google Scholar]
  • 116. Liu Q. R., Ji M. H., Dai Y. C., et al., “Predictors of Acute Postsurgical Pain Following Gastrointestinal Surgery: A Prospective Cohort Study,” Pain Research and Management 2021 2021 (2021): 6668152–6668158, 10.1155/2021/6668152. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 117. Masui Y., Watanabe M., Suehara N., et al., “Introduction of Preoperative Instruction Video Orientation in the Intensive Care Unit: Changes in Preoperative Anxiety Levels Before and After the Introduction of the Videos,” Esophagus 7, no. 1 (2010): 45EP–47, 10.1007/s10388-010-0223-y. [DOI] [Google Scholar]
  • 118. Mei F., Yang X., Na L., and Yang L., “Anal Preservation on the Psychology and Quality of Life of Low Rectal Cancer,” Journal of Surgical Oncology 125, no. 3 (2022): 484EP–492, 10.1002/jso.26741. [DOI] [PubMed] [Google Scholar]
  • 119. Mesquita Garcia A. C., Simão‐Miranda T. P., Pimenta Carvalho A. M., Elias P. C. L., Pereira M. D. G., and de Carvalho E. C., “The Effect of Therapeutic Listening on Anxiety and Fear Among Surgical Patients: Randomized Controlled Trial,” Revista Latino‐Americana de Enfermagem 26, (2018): 1–10, 10.1590/1518-8345.2438.3027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 120. Ono R., Makiura D., Nakamura T., et al., “Impact of Preoperative Social Frailty on Overall Survival and Cancer‐Specific Survival Among Older Patients With Gastrointestinal Cancer,” Journal of the American Medical Directors Association 22, no. 9 (2021): 1825, 10.1016/j.jamda.2021.03.025. [DOI] [PubMed] [Google Scholar]
  • 121. Penning Y., El Asmar A., Moreau M., et al., “Evaluation of the Comprehensive Geriatric Assessment (CGA) Tool as a Predictor of Postoperative Complications Following Major Oncological Abdominal Surgery in Geriatric Patients,” PLoS One 17, no. 3 (2022): e0264790, 10.1371/journal.pone.0264790. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 122. Piraux E., Caty G., Reychler G., Forget P., and Deswysen Y., “Feasibility and Preliminary Effectiveness of a Tele‐Prehabilitation Program in Esophagogastric Cancer Patients,” Journal of Clinical Medicine 9, no. 7 (2020): 1EP–14, 10.3390/jcm9072176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 123. Sarenmalm E. K., Nasic S., Hakanson C., et al., “Swedish Version of the Distress Thermometer: Validity Evidence in Patients With Colorectal Cancer,” Journal of the National Comprehensive Cancer Network: Journal of the National Comprehensive Cancer Network 16, no. 8 (2018): 959–966, 10.6004/jnccn.2018.7027. [DOI] [PubMed] [Google Scholar]
  • 124. Sawatzky R., Larsdotter C., Carlssson E., et al., “Predictors of Preparedness for Recovery Following Colorectal Cancer Surgery: A Latent Class Trajectory Analysis,” Acta Oncologica 62, no. 12 (2023): 1625–1634, 10.1080/0284186X.2023.2269303. [DOI] [PubMed] [Google Scholar]
  • 125. Sharma A., Sharp D. M., Walker L. G., and Monson J. R. T., “Predictors of Early Postoperative Quality of Life After Elective Resection for Colorectal Cancer,” Annals of Surgical Oncology 14, no. 12 (2007): 3435–3442, 10.1245/s10434-007-9554-x. [DOI] [PubMed] [Google Scholar]
  • 126. Sharma A., Walker L. G., and Monson J. R. T., “Baseline Quality of Life Factors Predict Long Term Survival After Elective Resection for Colorectal Cancer,” International Journal of Surgical Oncology 2013 (2013): 269510–269516, 10.1155/2013/269510. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 127. Soler‐Silva A., Triguero D., Sanchis‐Lopez A., et al., “Does the Performance of a Multimodal Pre‐Habilitation Protocol Gives Patients With Colorectal Cancer Better Quality Life After Surgery?,” Surgical Endoscopy 36 (2022): S358EP–S359, 10.1007/s00464-022-09337-0. [DOI] [Google Scholar]
  • 128. Sun G.‐W., Yang Y.‐L., Yang X.‐B., et al., “Preoperative Insomnia and Its Association With Psychological Factors, Pain and Anxiety in Chinese Colorectal Cancer Patients,” Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer 28, no. 6 (2020): 2911–2919, 10.1007/s00520-019-05151-y. [DOI] [PubMed] [Google Scholar]
  • 129. Turner J., Calman L., Fenlon D., et al., “Prevalence and Risk Factors of Depression in Colorectal Cancer Five Years After Surgery: Findings From the Color Ectal Wellbeing (CREW) Study,” Psycho‐Oncology 28 (2019): 7, 10.1002/pon.4993. [DOI] [Google Scholar]
  • 130. Xu L., Pan Q., and Lin R., “Prevalence Rate and Influencing Factors of Preoperative Anxiety and Depression in Gastric Cancer Patients in China: Preliminary Study,” Journal of International Medical Research 44, no. 2 (2016): 377–388, 10.1177/0300060515616722. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 131. Xu X.‐Y., Lu J.‐L., Xu Q., Hua H.‐X., and Chen Li, “Risk Factors and the Utility of Three Different Kinds of Prediction Models for Postoperative Fatigue After Gastrointestinal Tumor Surgery,” Supportive Care in Cancer: Official Journal of the Multinational Association of Supportive Care in Cancer 29, no. 1 (2021): 203–211, 10.1007/s00520-020-05483-0. [DOI] [PubMed] [Google Scholar]
  • 132. Scheede‐Bergdahl C., Minnella E., and Carli F., “Multi‐Modal Prehabilitation: Addressing the Why, When, What, How, Who and Where Next?,” supplement, Anaesthesia 74, no. S1 (2019): 20–26, 10.1111/anae.14505. [DOI] [PubMed] [Google Scholar]
  • 133. Leeds I. L., Meyers P. M., Enumah Z. O., et al., “Psychosocial Risks Are Independently Associated With Cancer Surgery Outcomes in Medically Comorbid Patients,” Annals of Surgical Oncology 26, no. 4 (2019): 936–944, 10.1245/s10434-018-07136-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 134. Levett D. and Grimmett C., “Psychological Factors, Prehabilitation and Surgical Outcomes: Evidence and Future Directions,” supplement, Anaesthesia 74, no. S1 (2019): 36–42, 10.1111/anae.14507. [DOI] [PubMed] [Google Scholar]
  • 135. Hirst N., McBride K., and Steffens D., “Psychological Interventions in Prehabilitation Randomized Controlled Trials for Patients Undergoing Cancer Surgery: Sufficient or Suboptimal?,” Annals of Surgical Oncology 31, no. 4 (2024): 2183–2186, 10.1245/s10434-023-14853-x. [DOI] [PubMed] [Google Scholar]
  • 136. Steffens D., Venter S., Makker P., et al., “Prehabilitation Practices for Patients Undergoing Cancer Surgery—An International Survey,” World Journal of Surgery 50, no. 1 (2026): 204–232, 10.1002/wjs.70180. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1

WJS-50-1017-s001.docx (18.1KB, docx)

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

Articles from World Journal of Surgery are provided here courtesy of Wiley

RESOURCES