Abstract
Introduction:
Patients with functional dependence have poorer outcomes after surgery for colon cancer than those who are independent. We sought to determine how much the use of minimally invasive surgery (MIS) would reduce the impact of functional dependence on discharge home, 30-day readmission, and 30-day mortality.
Methods:
We used the 2012–2020 American College of Surgeons’ National Surgical Quality improvement Program data on patients who underwent colectomies for colon cancer. Functional dependence was either independent, partially/totally dependent, or unknown. Surgical approaches were either MIS or open. We constructed logistic regression models to analyze the data and used a counterfactual approach to assess the differences in predicted rates of outcome for open vs. MIS surgery.
Results:
2.7% of 115,897 patients were partially/totally dependent. While 64.5% of all patients received MIS, among those who were partially/totally dependent only 49.7% received MIS. No difference existed in discharge destination or readmission rate by surgical approach among patients who were partially/totally dependent (p = 0.384 and p = 0.168, respectively). Using the counterfactual approach, performing MIS rather than open surgery among patients who were partially/totally dependent would lower 30-day mortality by 27.3% (relative reduction).
Discussion:
Optimizing MIS in patients with functional limitations should be a priority in colon cancer resection.
Keywords: Readmission, colon cancer, quality improvement, laparoscopy, minimally invasive surgery, mortality
1. Introduction
Colorectal cancer (CRC) is one of the most common cancers worldwide. Nearly 150,000 patients were newly diagnosed with CRC in the US in 2020 [1]. Surgery is an important component of the management of CRC. however, patient frailty negatively impacts postoperative outcomes, such as readmission, discharge destination, and mortality [2–4]. Frailty is defined as a state of increased vulnerability to stressors, due to decreased physiologic reserves, giving rise to a vulnerability that is separate from the normal aging process [5]. Frailty is increasingly being described in both the geriatric and oncologic literature as a clinical syndrome that may provide insight into risk stratification as part of shared decision-making [6]. More than half of CRC patients are estimated to be frail or prefrail or have a least one comorbid condition [7]. Frailty often leads to functional dependence and limitations in the performance of Activities of Daily Living (ADL) [8]. how to improve surgical outcomes in patients with functional dependence is unclear [9], but if achieved, it could improve their quality of life, prognosis, and quality of care, and reduce cost.
Minimally invasive surgery (MIS), including laparoscopic and robotic surgery, has become increasingly popular as a surgical approach in recent years due to its benefits on patient outcomes, including lower blood loss, earlier return of bowel function, improved patient comfort, faster recovery times, shorter hospital stay, and reduced readmissions, including in the elderly [10]. Utilization of MIS for CRC has increased over time, although barriers remain, including institutional constraints and surgeon experience [11]. Prior literature showed that patients with functional dependence have worse surgical outcomes compared to those who were independent [12]. To identify modifiable risk factors that can improve a patient’s perioperative risk, we sought to examine the extent to which increasing the utilization of MIS for functionally dependent patients could mitigate the adverse impact of limitations in ADLs on these outcomes using a counterfactual approach. Such a counterfactual approach offers the advantage of evaluating the potential impact of specific changes or interventions on outcomes, providing more actionable insights compared to traditional regression, which focuses primarily on modeling associations. Unlike traditional regression, the counterfactual results would facilitate tailoring surgical strategies through shared decision-making, taking into account individual patient characteristics, including functional status, to optimize outcomes. it would also help identify patients more likely to benefit from MIS and those who may require alternative surgical approaches. By incorporating functional assessment into the preoperative evaluation, healthcare providers can better anticipate and manage potential challenges, optimize perioperative care, and ultimately improve patient outcomes.
Our purpose was to determine if the use of MIS reduces the impact of functional status on early outcomes (discharge home, 30-day readmission, and 30-day mortality) after colon cancer surgery.
2. Materials and methods
2.1. Data source and patient selection
We utilized the Participant Use File and Targeted Colectomy File from the American College of Surgeons’ National Surgical Quality improvement Program (ACS-NSQIP) from 2012 to 2020. Trained reviewers extracted information from medical records at participating hospitals, including preoperative patient characteristics, laboratory results, procedure details, surgical complications, and patient outcomes up to 30 days after surgery. Patients had to have undergone colectomy for colorectal cancer. We excluded patients who died during their hospital stay (when analyzing readmissions), those with an ASA physical status of V (not expected to survive without surgery) or missing [13], and those who had not undergone colectomy using an open or laparoscopic/robotic approach. The University of Arkansas for Medical Sciences institutional Review Board determined that this study was exempt from oversight.
2.2. Functional health status/activities of daily living (ADL)
NSQIP captures functional frailty by collecting data about the best physical functional status/level of self-care within the 30 days prior to the primary procedure or at the time the patient is being considered a candidate for surgery. We define functional status, our key independent variable of interest, using the following categories:
Independent: The patient does not require assistance from another person for any activities of daily living. This includes a person who functions independently with prosthetics, equipment, or devices;
Partially dependent: The patient requires some assistance from another person for activities of daily living. This includes a person who utilizes prosthetics, equipment, or devices but still requires some assistance from another person for ADLs;
Totally dependent: The patient requires total assistance for all activities of daily living; or
Unknown: if unable to ascertain the functional status prior to surgery.
Based on the distribution of the four categories, patients were classified as (1) independent, (2) Partially or Totally Dependent, or (3) Unknown. Patients with unknown functional status were excluded.
2.3. Type of surgery
The type of surgery was classified as MIS, which included laparoscopic (including hand assistance, robotic approach, and single-incision laparoscopic surgery) or open surgery, based on the initial operative approach. Patients who received open surgery following conversion from laparoscopy were classified as laparoscopic. Patients with other approaches, including NOTES, were excluded from the analysis (<1% of the patient population).
2.4. Patient outcomes
The outcomes of interest were 30-day readmission, discharge home, and 30-day mortality. Readmission was defined as any hospital readmission within 30 days of the resection, regardless of the reason, at the same or a different hospital. To be counted as a readmission, the patient must have been formally readmitted by a qualified practitioner as an inpatient to an acute care bed or had another hospital encounter that crossed at least two midnights, within 30 days of their primary procedure. A patient is readmitted if, within 30 days of the primary procedure, he/she has an inpatient stay of at least two midnights after being discharged from the index hospital stay/encounter. Because NSQIP captures readmission within 30 days of resection, rather than 30-day post-discharge, patients with a longer length of stay have less opportunity to be readmitted due to “immortal person-time bias” [14]. For example, a patient discharged on post-op day 25 will have only 5 days to be readmitted in the 30 days after resection. Therefore, we excluded patients with a length of stay longer than 20 days and those who died during their hospitalization for the analysis focused on readmission.
For the evaluation of discharge disposition, we excluded CRC patients who had unknown origin status. Discharge home is defined as a binary outcome of a patient being discharged to home or a facility that was home. Patients who were not discharged home included those who were discharged to hospice, a separate acute care, a skilled care facility that was not their home, or an unskilled care facility that was not their home after surgery. Patients who left against medical advice, died during initial hospitalization, or had an unknown discharge location were excluded. We defined all-cause mortality as any deaths that occurred within 30 days of the surgery, including those that occurred during the hospital stay.
2.5. Potential confounders
Potential confounders were selected based on previous studies [15–20] and included patient demographic characteristics, admission source, comorbidities, TNM stage at diagnosis, tumor location, types of treatment, behavior-related, and complications. hematocrit values were treated as a categorical variable [21,22]. Glomerular filtration rate (GFR) was calculated based on race, sex, age, and creatinine levels [23]. Abnormal white blood cell count included ≤4.5 or ≥11.0 × 103/μL. A wound infection included superficial or deep incisional surgical site infection or any other wound infection. Receipt of transfusion from the start of surgery to 72 hours post-surgery was used as a measure of extensive blood loss. Sepsis was defined by Systemic inflammatory Response Syndrome (SIRS) criteria and either positive blood culture/clinical documentation or a suspected preoperative clinical condition of infection. For 30-day readmission and 30-day mortality, we included all postoperative complications as predictors. For the discharge home outcome, we included only complications that occurred prior to discharge.
2.6. Statistical analysis
For each of the three binary outcomes, we used the following steps in the analysis. First, we assessed the associations of the binary outcome to the fixed effects of functional status, type of surgery, and their interaction using a logistical regression model (unadjusted model). Second, the associations were assessed after adjusting for confounders using the same logistical regression by adding the confounders as additional independent variables (adjusted model). A counterfactual approach has the advantage of evaluating the potential impact of changes in MIS on outcomes, providing more actionable insights compared to traditional logistic regression, which focuses primarily on modeling associations. in the third step, we used the adjusted model in Step 2 to predict the outcome of each patient, using both the actual surgery the patient underwent, and a “switched” MIS if the patient’s actual surgery was open surgery. Using this “counter-factual approach” [24], we obtained the predicted rates of the outcome under both open surgery and MIS for the same patient. Both the absolute and relative differences or reductions were calculated between the predicted rates. The confidence intervals of the absolute and relative reductions were constructed using bootstrapping resampling methods. Other categorical and numerical variables were summarized using frequency (in %) and median (min, max) respectively.
We performed a sensitivity analysis to determine the robustness of our findings by excluding the year 2020 because of the COVID-19 pandemic. All analyses were conducted using STATA version 17 (Stata Corp LP, College Station, TX).
3. Results
The analysis comprised 115,897 patients, 3,110 (2.7%) were partially or totally dependent. Table 1 illustrates those patients with partial or total dependence had a higher likelihood of being male, older, African American, receiving open surgery, being admitted from a nursing home, chronic care, intermediate care unit, being diagnosed with TNM stage 0–II, having their tumor located in the right colon, and experiencing a longer hospital stay (p < 0.05). While 64.5% of all patients received MIS, among those who were partially/totally dependent only 49.7% received MIS.
Table 1.
Study population characteristics by patient functional status among patients with colon cancer following surgical resection.
| Characteristic | Functional status | Total (n = 115,897)% | |
|---|---|---|---|
| Partially/totally dependent (n = 3,110)% | Independent (n = 112,787)% | ||
| Sex (male)* | 42.8 | 51.5 | 51.3 |
| Age group* | |||
| <45 | 1.5 | 6.3 | 6.2 |
| 45–54 | 4.5 | 15.8 | 15.5 |
| 55–64 | 10.5 | 23.4 | 23.0 |
| 65–74 | 20.2 | 27.0 | 26.8 |
| 75+ | 63.4 | 27.6 | 28.6 |
| Hispanic ethnicity | |||
| Yes | 4.6 | 5.0 | 5.0 |
| No | 80.8 | 79.0 | 79.1 |
| Unknown | 14.5 | 16.0 | 16.0 |
| Race* | |||
| White | 63.6 | 66.9 | 66.8 |
| African American | 13.8 | 9.3 | 9.4 |
| Other | 6.2 | 5.6 | 5.6 |
| Unknown | 16.4 | 18.2 | 18.2 |
| Type of surgery* | |||
| Open | 50.3 | 35.1 | 35.5 |
| Minimally invasive | 49.7 | 64.9 | 64.5 |
| Admission source* | |||
| From acute care as hospital inpatient | 5.4 | 1.7 | 1.8 |
| Admitted from home | 74.5 | 96.2 | 95.7 |
| Nursing home, chronic care, intermediate care | 16.0 | 0.4 | 0.8 |
| Outside emergency department | 2.8 | 1.3 | 1.3 |
| Other | 1.2 | 0.3 | 0.3 |
| Unknown | 0.2 | 0.1 | 0.1 |
| TNM stage* | |||
| 0 | 0.8 | 2.1 | 2.0 |
| I | 9.9 | 12.8 | 12.7 |
| II | 21.1 | 16.2 | 16.4 |
| III | 18.5 | 16.8 | 16.8 |
| IV | 5.3 | 7.0 | 6.9 |
| Unknown | 44.5 | 45.2 | 45.2 |
| Tumor location* | |||
| Left | 29.8 | 41.4 | 41.1 |
| Right | 46.2 | 36.5 | 36.7 |
| Transverse | 24.0 | 22.2 | 22.2 |
| Length of stay (mean, ST. error)* | 12.6 (0.18) | 6.7 (0.02) | 6.9 (0.02) |
| Reoperation* | 5.0 | 4.0 | 4.0 |
| Deep vein thrombosis* | 2.4 | 1.1 | 1.1 |
| Pulmonary embolism* | 1.1 | 0.7 | 0.7 |
| Myocardial infarction* | 2.0 | 0.7 | 0.7 |
| Stroke* | 1.0 | 0.2 | 0.3 |
| Wound infection* | 6.6 | 0.6 | 0.8 |
| Deep incisional surgical site infection* | 1.1 | 0.6 | 0.6 |
| Anastomotic leak | 2.7 | 2.9 | 2.0 |
| Prolonged ileus* | 23.7 | 13.7 | 13.9 |
| Sepsis* | 5.6 | 2.6 | 2.7 |
| C. Difficile* | 1.7 | 0.8 | 0.8 |
p < 0.05 Between patients who were partially/totally dependent and those who were functionally independent based on Chi-square test.
3.1. Discharge home
Overall, 90.6% of patients were discharged home (Table 2). Patients who received MIS were more likely to be discharged home, even among those who were partially/totally dependent, and among those who were independent (both p < 0.001 in Figure 1). in adjusted analysis (Table 3), independent patients who received MIS were more likely to discharged home (odds ratio [OR]: 1.55) than those who received open surgery (p < 0.001). however, there was no difference in discharge destination by surgical approach among patients who were partially/totally dependent (OR = 1.08, p = 0.361). Performing MIS rather than open surgery among patients who were partially/totally dependent would reduce the rate of non-home discharge by an absolute reduction of 2.55% (0.71; 4.39) and a relative reduction of 4.72% (95% CI: 1.32; 8.12).
Table 2.
Percentage of colon cancer patients who were discharged home, readmitted within 30 days, or died within 30 days by functional status and type of surgery.*
| Discharged home (n = 115,894) (%) | 30-Day readmission (n = 115,897) (%) | 30-Day mortality (n = 117,905) (%) | |
|---|---|---|---|
| Total | 90.6 | 9.9 | 1.9 |
| Functional status* | |||
| Independent | 91.6 | 9.8 | 1.7 |
| Partially/totally dependent | 54.1 | 15.9 | 8.3 |
| Type of surgery* | |||
| MIS | 94.1 | 8.4 | 0.8 |
| Open | 84.2 | 12.8 | 3.7 |
MIS: minimally invasive surgery.
p < 0.001 for comparisons by functional status and type of surgery.
Figure 1.
Percentage of colorectal cancer patients discharged home by functional status and type of surgery. Among functionally independent patients, those who underwent minimally invasive surgery were more likely to be discharged home (94.7%) compared to those who had open surgery (85.7%). Similarly, among functionally partially/totally dependent patients, discharge home was more common after minimally invasive surgery (61.5%) than open surgery (46.8%).
Table 3.
Adjusted associations (odds ratio, 95% confidence intervals) of functional status and type of surgery by patient outcome (discharged home, readmitted within 30 days, or died within 30 days) of colon cancer patients.*
| Discharged home (n = 115,894) | 30-Day readmission (n = 115,897) | 30-Day mortality (n = 117,905) | |
|---|---|---|---|
| Functional status | |||
| Independent | |||
| MIS | 1.55 (1.47; 1.63) | 0.76 (0.72; 0.80) | 0.71 (0.63; 0.80) |
| Open | 1.00 | 1.00 | 1.00 |
| Partially/totally dependent | |||
| MIS | 1.08 (0.91; 1.28) | 0.85 (0.67; 1.07) | 0.58 (0.42; 0.81) |
| Open | 1.00 | 1.00 | 1.00 |
MIS: minimally invasive surgery.
Adjusted for all confounders.
3.2. 30-Day readmission
Overall, 9.9% of patients were readmitted within 30 days of resection (Table 2). Patients who received MIS experienced a lower readmission rate among those who were partially/totally dependent and among those who were independent (both p < 0.001 in Figure 2). in adjusted analysis (Table 3), independent patients who received MIS were less likely to be readmitted within 30 days (OR: 0.76) than those who received open surgery (p < 0.001). however, there was no difference in readmission rate by surgical approach among patients who were partially/totally dependent (p = 0.168). Performing MIS rather than open surgery among patients who were partially/totally dependent would not reduce readmission (absolute reduction: 0.31%, 95% CI: −1.10; 1.73 and relative reduction: 2.00%, 95% CI: −7.51; 11.47).
Figure 2.
Percentage of colorectal cancer (CRC) patients readmitted within 30 days, by functional status and surgical approach. Among functionally independent patients, 30-day readmission was lower following minimally invasive surgery (8.3%) compared to open surgery (12.7%). Similarly, among functionally partially/totally dependent patients, those who underwent minimally invasive surgery had a lower readmission rate (13.7%) than those who had open surgery (18.2%).
3.3. 30-Day mortality
Overall, 1.9% of patients died within 30 days of resection (Table 2). Patients who received MIS experienced a lower mortality rate among those who were partially/totally dependent and among those who were independent (both p < 0.001 in Figure 3). The mortality rate was highest among partially/totally dependent patients who received open surgery (12.5%). in adjusted analysis (Table 3), independent patients who received MIS were less likely to die within 30 days (OR: 0.71) than those who received open surgery (p < 0.001). This was also true among partially/totally dependent patients (OR: 0.58). Performing MIS rather than open surgery among patients who were partially/totally dependent would reduce 30-day mortality by an absolute reduction of 2.27% (95% CI: 1.00; 3.54) and a relative reduction of 27.3% (95% CI: 12.4; 42.2).
Figure 3.
Percentage of colorectal cancer patients who died within 30 days, by functional status and surgical approach. Among functionally independent patients, 30-day mortality was significantly lower following minimally invasive surgery (0.8%) compared to open surgery (3.3%). For functionally partially/totally dependent patients, 30-day mortality was 3.8% after minimally invasive surgery and 12.5% after open surgery.
4. Discussion
As the population continues to grow older, there is an increasing number of patients requiring colon cancer surgery. These individuals present distinct challenges due to their comorbidities or impaired functional status. it has been shown that, more so than chronological age, functional status plays a large role in morbidity and patient outcomes after surgery [4,25,26].
While prior literature showed that patients with limitations in ADLs have worse surgical outcomes [12], the purpose of this study was to examine how much the use of MIS for colon cancer surgery can potentially mitigate the adverse impact of limitations in ADLs on three patient outcomes. The American Society of Colon and Rectal Surgeons recommends the use of MIS when expertise is available [27], including for frail older adults [6]. Some have even suggested that MIS should be aggressively used for elderly patients [28]. Our study found that in partially or totally dependent patients, the use of MIS would improve 30-day mortality after surgery but would have no effect on 30-day readmission rate or discharge destination. Gill et al. recently described that in community-living older adults in the USA, 1-year mortality after major surgery was 13.4%, and up to a staggering 28% in those who were frail [29]. Our study similarly showed that among CRC patients who were partially or totally dependent, 12.5% died within 30 days following resection. importantly, when comparing our rates of 30-day mortality, partially/totally dependent patients who underwent MIS (3.8%) had similar rates to independent patients who underwent open surgery (3.3%).
Improving the use of MIS among colon cancer patients with functional dependence could maximize patient outcomes since the current percentage of patients who received MIS is substantially lower (49.7%) compared to those without functional limitations (64.9%). While the NSQIP database does not provide the reason for choosing a particular surgical approach, it is important to note that the baseline characteristics of partially/totally dependent patients differed in many areas from the independent patients that were included in the regression models. in addition, the use of MIS is lower in hospitals with lower volume and those located in rural areas [30], and some patients, particularly those who are older or have functional limitations, may not have the means or abilities to seek out surgeons offering MIS [31].
This study’s use of a counterfactual modeling approach is a key strength, offering more actionable insights than traditional regression by estimating how outcomes might change under specific interventions (e.g., MIS). Unlike standard regression, which identifies associations, counterfactual models help tailor strategies to individual patients—such as by functional status—supporting shared decision-making and optimizing outcomes. These models provide valuable information for health system leaders, policymakers, quality improvement staff, and clinicians by quantifying the potential impact of evidence-based changes (e.g., MIS) on health outcomes in colon cancer patients.
We acknowledge the limitations of our study. We analyzed existing data available in the NSQIP database and therefore were limited to the data collected by NSQIP; characteristics about NSQIP participating hospitals and surgeons, and data about risk factors for adverse patient outcomes (e.g., depression, inflammation, physical activity, alcohol use) were not available. The NSQIP collects data about a patient’s functional status based on Activities of Daily Living. Results may be different based on the use of other measures such as instrumental Activities of Daily Living or sarcopenia. in addition, the NSQIP database typically includes data from larger hospitals limiting generalizability to smaller and rural hospitals. Our study’s strength included the identification of a specific opportunity for improving patient outcomes among patients who were partially or totally dependent, and our novel approach of quantifying the effect of changes from open surgery to MIS on three types of patient outcomes.
5. Conclusion
Oncologists, surgeons, and colon cancer patients should be aware of the excess postoperative risks related to functional status. Optimizing the use of MIS in a population with functional dependence should be an important priority for patients needing resection for colon cancer to reduce short-term mortality.
Article highlights.
Functionally dependent patients (those needing help with daily tasks) have worse outcomes after colon cancer surgery than independent patients.
This study analyzed over 115,000 colon cancer surgeries from 2012–2020 to assess whether minimally invasive surgery (MIS) improves outcomes in these patients.
Only about half (49.7%) of functionally dependent patients received MIS, compared to 64.5% of all patients.
Among functionally dependent patients, MIS did not significantly affect discharge home or 30-day readmission rates.
However, using MIS instead of open surgery in these patients was associated with a 27.3% relative reduction in 30-day mortality.
Optimizing the use of MIS in a population with functional dependence should be an important priority for patients needing resection for colon cancer to reduce short-term mortality.
Funding
This work was supported by the National Center for Advancing Translational Sciences of the National institutes of health under award number [1UM1TR004909]. Li is funded by American Cancer Society [RSGI-23-1039245-01-HOPS]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National institutes of health or American Cancer Society.
Disclosure statement
Chenghui Li received research support for unrelated projects sponsored by University of Utah/AstraZeneca. Other authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript. Mario Schootman is a member of the Colorectal Cancer Editorial Board. They were not involved in any editorial decisions related to the publication of this article, and author details were not made available to the article’s peer reviewers as per the journal’s double-anonymized peer review policy.
Footnotes
Ethical declaration
The University of Arkansas for Medical Sciences Institutional Review Board determined that this study was exempt from oversight.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Data availability statement
NSQIP data are available through the American College of Surgeons https://www.facs.org/quality-programs/data-and-registries/acs-nsqip/.
References
Papers of special note have been highlighted as either of interest (*) or of considerable interest (**) to readers.
- [1].Siegel RL, Miller KD, Fuchs hE, et al. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7–33. doi: 10.3322/caac.21708 [DOI] [PubMed] [Google Scholar]
- [2**].Vermillion SA, hsu FC, Dorrell RD, et al. Modified frailty index predicts postoperative outcomes in older gastrointestinal cancer patients. J Surg Oncol. 2017;115(8):997–1003. doi: 10.1002/jso.24617 [DOI] [PMC free article] [PubMed] [Google Scholar]; his study shows that the frailty index was associated with the incidence of postoperative complications and mortality in older surgical patients with gastrointestinal cancer.
- [3**].Shaw JF, Budiansky D, Sharif F, et al. The association of frailty with outcomes after cancer surgery. A systematic review and metaanalysis. Ann Surg Oncol. 2022;29(8):4690–4704. [DOI] [PubMed] [Google Scholar]; This study shows that frailty is strongly associated with adverse health outcomes and that preoperative frailty assessment should be considered in prognostication.
- [4].Michaud Maturana M, English WJ, Nandakumar M, et al. The impact of frailty on clinical outcomes in colorectal cancer surgery: a systematic literature review. ANZ J Surg. 2021;91(11):2322–2329. doi: 10.1111/ans.16941 [DOI] [PubMed] [Google Scholar]
- [5].Clegg A, Young J, iliffe S, et al. Frailty in elderly people. Lancet. 2013;381(9868):752–762. doi: 10.1016/S0140-6736(12)62167-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Saur NM, Davis BR, Montroni i, et al. The American Society of Colon and Rectal Surgeons clinical practice guidelines for the perioperative evaluation and management of frailty among older adults undergoing colorectal surgery. Dis Colon Rectum. 2022;65(4):473–488. doi: 10.1097/DCR.0000000000002410 [DOI] [PubMed] [Google Scholar]
- [7].Edwards BK, Noone A-M, Mariotto AB, et al. Annual Report to the Nation on the status of cancer, 1975–2010, featuring prevalence of comorbidity and impact on survival among persons with lung, colorectal, breast, or prostate cancer. Cancer. 2014;120(9):1290–1314. doi: 10.1002/cncr.28509 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8].Boyer S, Trimouillas J, Cardinaud N, et al. Frailty and functional dependence in older population: lessons from the FREEDOM Limousin – Nouvelle Aquitaine Cohort Study. BMC Geriatr. 2022;22(1):128. doi: 10.1186/s12877-022-02834-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9*].Mcisaac Di, Jen T, Mookerji N, et al. interventions to improve the outcomes of frail people having surgery: a systematic review. PLOS One. 2017;12(12):e0190071. doi: 10.1371/journal.pone.0190071 [DOI] [PMC free article] [PubMed] [Google Scholar]; This study shows that few interventions have been tested to improve the outcomes of frail surgical patients.
- [10].Hahn SJ, Sylla P. Technological advances in the surgical treatment of colorectal cancer. Surg Oncol Clin N Am. 2022;31(2):183–218. doi: 10.1016/j.soc.2022.01.001 [DOI] [PubMed] [Google Scholar]
- [11].Kolarsick PA, Sacchi M, Spinelli A, et al. Minimizing the impact of colorectal surgery in the older patient: the role of minimally invasive surgery in the geriatric population. Eur J Surg Oncol. 2020;46(3):333–337. doi: 10.1016/j.ejso.2019.12.019 [DOI] [PubMed] [Google Scholar]
- [12].Scarborough JE, Bennett KM, Englum BR, et al. The impact of functional dependency on outcomes after complex general and vascular surgery. Ann Surg. 2015;261(3):432–437. doi: 10.1097/SLA.0000000000000767 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].American Society of Anesthesiologists. ASA physical status classification system; 2017. November 28. Available from: https://www.asahq.org/standards-and-practice-parameters/statement-on-asa-physical-status-classification-system.
- [14].Lucas DJ, haut ER, hechenbleikner EM, et al. Avoiding immortal time bias in the American College of Surgeons national surgical quality improvement program readmission measure. JAMA Surg. 2014;149(8):875–877. doi: 10.1001/jamasurg.2014.115 [DOI] [PubMed] [Google Scholar]
- [15].Bilimoria KY, Liu Y, Paruch JL, et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013;217(5):833–842e3. doi: 10.1016/j.jamcollsurg.2013.07.385 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Dolejs SC, Waters JA, Ceppa EP, et al. Laparoscopic versus robotic colectomy: a national surgical quality improvement project analysis. Surg Endosc. 2017;31(6):2387–2396. doi: 10.1007/s00464-016-5239-5 [DOI] [PubMed] [Google Scholar]
- [17].Cohen ME, Bilimoria KY, Ko CY, et al. Development of an American College of Surgeons national surgery quality improvement program: morbidity and mortality risk calculator for colorectal surgery. J Am Coll Surg. 2009;208(6):1009–1016. doi: 10.1016/j.jamcollsurg.2009.01.043 [DOI] [PubMed] [Google Scholar]
- [18].Davila J, Rabeneck L, Berger D, et al. Postoperative 30-day mortality following surgical resection for colorectal cancer in veterans: changes in the right direction. Dig Dis Sci. 2005;50(9):1722–1728. doi: 10.1007/s10620-005-2925-x [DOI] [PubMed] [Google Scholar]
- [19].Egenvall M, Morner M, Martling A, et al. Prediction of outcome after curative surgery for colorectal cancer: preoperative haemoglobin, CRP and albumin. Colorectal disease; 2018; 20(1): 26–34 [DOI] [PubMed] [Google Scholar]
- [20].Sharp SP, Ata A, Chismark AD, et al. Racial disparities after stoma construction in colorectal surgery. Colorectal Dis. 2020;22(6):713–722. doi: 10.1111/codi.14943 [DOI] [PubMed] [Google Scholar]
- [21].Kwaan MR, Al-Refaie WB, Parsons HM, et al. Are right-sided colectomy outcomes different from left-sided colectomy outcomes? Study of patients with colon cancer in the ACS NSQIP database. JAMA Surg. 2013;148(6):504–510. doi: 10.1001/jamasurg.2013.1205 [DOI] [PubMed] [Google Scholar]
- [22].Sirany AM, Chow CJ, Kunitake H, et al. Colorectal surgery outcomes in chronic dialysis patients: An American College of Surgeons National Surgical Quality improvement Program Study. Dis Colon Rectum. 2016;59(7):662–669. doi: 10.1097/DCR.0000000000000609 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann intern Med. 2009;150(9):604–612. doi: 10.7326/0003-4819-150-9-200905050-00006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [24**].Fleischer NL, Fernald LCh, hubbard AE. Estimating the potential impacts of intervention from observational data: methods for estimating causal attributable risk in a cross-sectional analysis of depressive symptoms in Latin America. J Epidemiol Commun health. 2010; 64(1):26–34. [DOI] [PubMed] [Google Scholar]; This study shows that population intervention parameters are a valuable approach in studies for making causal inference from the data while also supplying information that is relevant for researchers, public health practitioners, and policy makers.
- [25].Makary MA, Segev DL, Pronovost PJ, et al. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg. 2010;210(6):901–908. doi: 10.1016/j.jamcollsurg.2010.01.028 [DOI] [PubMed] [Google Scholar]
- [26].Seib CD, Rochefort H, Chomsky-higgins K, et al. Association of patient frailty with increased morbidity after common ambulatory general surgery operations. JAMA Surg. 2018;153(2):160–168. doi: 10.1001/jamasurg.2017.4007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [27].Vogel JD, Felder Si, Bhama AR, et al. The American Society of Colon and Rectal Surgeons clinical practice guidelines for the management of colon cancer. Dis Colon Rectum. 2022;65(2):148–177. doi: 10.1097/DCR.0000000000002323 [DOI] [PubMed] [Google Scholar]
- [28*].Seishima R, Okabayashi K, hasegawa H, et al. is laparoscopic colorectal surgery beneficial for elderly patients? A systematic review and meta-analysis. J Gastrointest Surg. 2015;19(4):756–765. doi: 10.1007/s11605-015-2748-9 [DOI] [PubMed] [Google Scholar]; This study shows that aggressive application of laparoscopic colorectal surgery should be considered for the elderly population.
- [29*].Gill TM, Vander Wyk B, Leo-Summers L, et al. Population-based estimates of 1-year mortality after major surgery among community-living older US adults. JAMA Surg. 2022;157(12):e225155. doi: 10.1001/jamasurg.2022.5155 [DOI] [PMC free article] [PubMed] [Google Scholar]; This study shows that mortality after major surgery was elevated among older persons who are frail.
- [30].Moghadamyeghaneh Z, Carmichael JC, Mills S, et al. Variations in laparoscopic colectomy utilization in the United States. Dis Colon Rectum. 2015;58(10):950–956. doi: 10.1097/DCR.0000000000000448 [DOI] [PubMed] [Google Scholar]
- [31].Bühn S, Holstiege J, Pieper D. Are patients willing to accept longer travel times to decrease their risk associated with surgical procedures? A systematic review. BMC Public health. 2020;20(1):253. doi: 10.1186/s12889-020-8333-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
NSQIP data are available through the American College of Surgeons https://www.facs.org/quality-programs/data-and-registries/acs-nsqip/.