Skip to main content
NCBI home page
Journal of Multidisciplinary Healthcare logoLink to Journal of Multidisciplinary Healthcare
. 2026 Aug 19;19:637270. doi: 10.2147/JMDH.S637270

Time-Toxicity Indicators and Mitigation Strategies in Cancer Care: A Scoping Review

Yingtong Sun 1, Jiaxin Guo 1, Wenna Sun 1, Jinrong Wei 1,2,✉
PMCID: PMC13500014  PMID: 42634796

Abstract

Objective

To map strategies for mitigating time toxicity in cancer care, summarize time-toxicity-related indicators, and identify implications for nursing and supportive care.

Methods

This scoping review was conducted in accordance with Joanna Briggs Institute guidance and reported using the PRISMA-ScR checklist. The PCC framework was used to define the population, concept, and context. PubMed, Embase, CINAHL, and Web of Science were searched from inception to June 1, 2026. Eligible studies were peer-reviewed empirical studies involving patients with cancer or cancer survivors and reporting time-toxicity-related indicators or strategies relevant to reducing time burden in cancer care. Two reviewers independently screened records and charted data using a standardized form.

Results

Fifteen studies published between 2017 and 2026 were included. Study populations covered breast, prostate, gynecologic, gastrointestinal, hepatocellular, hematologic, and mixed cancer populations. Indicators included travel distance, travel time, waiting time, total encounter time, health care contact days, days at home, hospital days, emergency department days, treatment visits, overall treatment time, and transfusion-related time burden. Four strategy domains were identified: decentralized and closer-to-home care, digital support and workflow optimization, individualized scheduling and logistical support, and optimization of treatment-related time burden. These strategies addressed time burden by reducing travel, shortening waiting or encounter time, improving logistical support, optimizing treatment pathways, or incorporating time costs into treatment decision-making.

Conclusion

Time toxicity arises from treatment and from how patients access, receive, coordinate, and manage cancer care. Current evidence identifies potential mitigation directions but does not establish comparative effectiveness. Future studies should develop consistent core measures and prospectively evaluate mitigation strategies. Nursing practice, education, and policy should recognize time burden as part of patient-centred cancer care and care pathway design.

Keywords: cancer, time toxicity, time burden, scoping review, oncology nursing

Introduction

Cancer remains a major global public health challenge. In 2022, an estimated 19.98 million new cancer cases and 9.74 million cancer deaths occurred worldwide, and the global cancer burden is expected to continue increasing in the coming decades.1 Recent estimates from the American Cancer Society projected 2,114,850 new cancer cases and 626,140 cancer deaths in the United States in 2026, while also reporting continued improvements in cancer survival, with the overall 5-year relative survival rate reaching 70% for cancers diagnosed during.2015–20212 With advances in diagnosis and treatment and improvements in survival, cancer care has become increasingly prolonged, continuous, and complex.3,4 In addition to the physical, psychological, and financial burdens associated with cancer and its treatment, patients must devote substantial time to diagnostic tests, treatment visits, follow-up appointments, symptom management, and ongoing communication with the health care system.5

In recent years, the time that patients spend receiving and managing cancer care has increasingly been conceptualized as “time toxicity”.6,7 Time toxicity commonly involves the time consumed by travel, waiting, diagnostic tests, treatment, hospitalization, care coordination, and post-treatment recovery. Previous studies have shown that cancer care may occupy a substantial proportion of patients’ time and affect their quality of life, family and social roles, and treatment choices.8,9 In addition, part of this time burden does not occur within health care facilities but extends into the home setting, including caregiver involvement in symptom monitoring, communication, appointment arrangement, and care coordination.10

Despite growing attention to time toxicity, several gaps remain in the existing literature. First, the conceptual boundaries and measurement approaches of time toxicity have not been standardized. Studies have used various indicators, such as health care contact days, days at home, travel time, waiting time, and number of treatment visits, which limits comparability and synthesis across studies.11 Second, the impact of time burden is heterogeneous.12 It is shaped not only by the treatment regimen itself, but also by residential distance, transportation access, work schedules, family responsibilities, and caregiving support.13 Therefore, patients differ in their capacity to absorb, manage, and adapt to the time demands imposed by cancer care.14 To date, much of the available evidence has focused on identifying, describing, or measuring time burden,15–17 whereas research on how to reduce time toxicity remains relatively limited.

Although some studies have begun to explore approaches for reducing the time burden of cancer care, the evidence is scattered across different cancer types, treatment phases, and care settings. A systematic synthesis of strategies for mitigating time toxicity in cancer care is still lacking.18–20 Therefore, this scoping review aims to map the strategies that have been proposed or evaluated to reduce time toxicity in cancer care, and to summarize the related evaluation indicators and care contexts. By clarifying the scope of existing evidence and identifying research gaps, this review may inform future time-toxicity measurement, patient-centred care process optimization, and nursing supportive interventions.

Methods

Design

This study adopted a scoping review design to systematically map strategies for reducing time toxicity in cancer care and the time-toxicity-related indicators used in existing studies. The review was informed by the methodological framework for scoping reviews proposed by Arksey and O’Malley21 and conducted in accordance with the Joanna Briggs Institute methodological guidance for scoping reviews.22 The review protocol was not prospectively registered in a public database. However, the review was guided by a predefined internal protocol that specified the eligibility criteria, search strategy, screening procedures, and data charting form. The review was conducted through sequential stages of question formulation, evidence identification, study selection, data charting, synthesis, and reporting. The completed PRISMA-ScR checklist and full search strategies are provided in Appendix A and Appendix B to support transparency and reproducibility.

Review Questions

The review addressed the following questions:

  1. Which indicators have been used to describe or measure time toxicity in oncology care?

  2. In which care contexts and time-burden dimensions has time toxicity been reported?

  3. Which strategies have been proposed or evaluated to mitigate time toxicity?

Eligibility Criteria

The selection of studies for this review was guided by predefined inclusion and exclusion criteria. Following the JBI methodological guidance for scoping reviews, the PCC framework was used to align the eligibility criteria with the review questions.

Inclusion Criteria

Population

Studies involving patients with cancer or cancer survivors were included. Studies involving care partners or health care professionals were also eligible when they provided evidence on time burden or mitigation strategies in cancer care.

Concept

Studies were included if they addressed time toxicity or time burden related to cancer care, including travel time, travel distance, waiting time, health care contact days, medical care days, days at home, treatment duration, number of treatment visits, or perceived time burden.

Context

Eligible studies were conducted in cancer care settings, including treatment, follow-up, survivorship care, supportive care, shared care, and palliative care.

Types of Evidence

Original peer-reviewed empirical studies were eligible, including quantitative, qualitative, mixed-methods, secondary, and post hoc analyses.

Language

Only full-text articles published in English were included to ensure consistency and accuracy in study screening, data charting, and interpretation.

Exclusion Criteria

Population

Studies were excluded if they did not involve patients with cancer or cancer survivors and did not provide evidence from care partners or health care professionals relevant to cancer care.

Concept

Studies were excluded if they reported only clinical time-to-event outcomes, such as survival, progression-free survival, disease progression, or time to recurrence, without addressing time toxicity or time burden. Studies that discussed time toxicity or time burden only conceptually, without empirical evidence related to mitigation strategies, care models, treatment pathways, or treatment decision-making, were also excluded.

Context

Studies were excluded if they were not conducted in, or directly relevant to, cancer care settings.

Types of Evidence

Reviews, editorials, commentaries, letters, protocols, conference abstracts, grey literature, and other non-empirical publications were excluded.

Data Availability

Studies were excluded if they did not provide extractable time-toxicity-related indicators or qualitative findings relevant to this review.

Search Strategy

The search strategy was developed using the three-step approach recommended by the JBI for scoping reviews. First, an initial limited search was conducted in PubMed and CINAHL to identify relevant keywords, subject headings, and index terms from the titles, abstracts, and indexing records of potentially relevant articles. Second, a comprehensive search was conducted in PubMed, Embase, CINAHL via EBSCOhost, and Web of Science from inception to June 1, 2026. These databases were selected to provide broad coverage of biomedical, oncology, nursing, supportive care, and interdisciplinary literature relevant to time toxicity in cancer care. PubMed and Embase were used to capture biomedical and oncology-related studies; CINAHL was included because of the nursing and supportive care focus of this review; and Web of Science was searched to broaden interdisciplinary coverage and support citation tracking.

The search strategy was structured around two broad search blocks derived from the PCC framework: the Population of interest (cancer) and the Concept of interest (time toxicity or time burden). Population-related terms included cancer, tumor/tumour, neoplasm, carcinoma, oncology, and relevant controlled vocabulary where available. Time-toxicity-related terms included time toxicity, time burden, travel burden, travel distance, travel time, healthcare days, health care days, medical care days, days at home, home days, and total encounter time. Synonymous terms within each block were combined using “OR”, and the two blocks were combined using “AND.” To maximize search sensitivity and avoid excluding potentially relevant studies, the Context component and mitigation-related terms were not used as separate restrictive search blocks. Instead, relevance to cancer care contexts and strategies for mitigating time toxicity was assessed during study selection according to the predefined eligibility criteria. The search syntax, field tags, and controlled vocabulary, where available, were adapted as appropriate for each database. Third, the reference lists of all included studies and relevant reviews were manually checked to identify additional eligible studies. Reference list checking did not identify any additional studies that met the eligibility criteria.

Grey literature was not included because this review focused on peer-reviewed empirical studies with sufficient methodological and outcome details for consistent data charting. Conference abstracts, reports, dissertations, protocols, and other unpublished or non-peer-revie in the United States in 2026wed materials were excluded because they often provide limited information on study design, participant characteristics, time-toxicity-related indicators, and mitigation strategies. The full search strategies are provided in Appendix B.

Evidence Screening and Selection

All records retrieved from the databases were imported into EndNote 20 for reference management. Duplicate records were removed using the duplicate detection function in EndNote 20, followed by manual checking. Before formal screening, the eligibility criteria were pilot-tested on a sample of records to ensure consistent interpretation among reviewers. After deduplication, two reviewers independently screened titles and abstracts according to the predefined eligibility criteria. Records considered potentially eligible by either reviewer were retrieved for full-text assessment.

Full-text screening was then conducted independently by the same two reviewers. Reasons for exclusion at the full-text stage were recorded and are summarized in the study selection flow diagram. Disagreements at either the title/abstract or full-text screening stage were resolved through discussion; if consensus could not be reached, a third reviewer was consulted. The reviewers involved in screening and selection had training in nursing research and evidence synthesis, and a senior reviewer with expertise in oncology nursing and review methodology provided methodological oversight.

Data Charting and Synthesis

After the final studies were identified, data were extracted using a standardized data charting form developed by the review team with reference to the JBI guidance for scoping reviews, the PCC framework, and the review questions. The form was pilot-tested on several included studies and refined before full data extraction. Extracted information included first author, year of publication, country or region, cancer type or study population, sample size, study design, care setting, mitigation strategy or care model, time-toxicity-related indicators, and key findings relevant to time-toxicity reduction. Data extraction was performed independently by two reviewers, and the extracted data were cross-checked. Any discrepancies were resolved through discussion.A descriptive and narrative synthesis was conducted. First, the basic characteristics of the included studies were summarized. Second, time-toxicity-related indicators were grouped according to the type of time burden measured. Finally, strategies to reduce time toxicity in cancer care were synthesized thematically according to the nature of the strategy and the care context in which it was applied. Direct mitigation strategies were distinguished from treatment decision-support approaches during synthesis.

Critical Appraisal

Consistent with the purpose of a scoping review, no formal methodological quality appraisal or risk-of-bias assessment was conducted. The aim of this review was to map the extent, characteristics, and nature of the available evidence rather than to determine intervention effectiveness or exclude studies based on methodological quality. However, the methodological characteristics of the included studies, including study design, care setting, sample size, population, strategy type, and reported time-toxicity-related indicators, were charted and described to support interpretation of the findings.

Results

Study Selection

A total of 5,098 records were identified from four electronic databases, including PubMed (n = 1,218), Embase (n = 1,916), CINAHL (n = 455), and Web of Science (n = 1,509). After removing 2,864 duplicate records, 2,234 records remained for title and abstract screening. Of these, 2,190 records were excluded because they were clearly irrelevant to the review question. Forty-four full-text reports were then retrieved and assessed for eligibility. Twenty-nine reports were excluded after full-text assessment, mainly because they did not report a relevant mitigation strategy or intervention, only measured or described time burden without strategy-related evidence, did not report relevant time-toxicity-related outcomes, or were not related to cancer care or the target population. Finally, 15 studies were included in this scoping review. The study selection process is presented in Figure 1.

Figure 1.

A PRISMA flowchart of study selection from databases to inclusion in a scoping review. The flowchart illustrates the study selection process via databases and registers. Initially, 5,098 records were identified from databases: PubMed (1,218), CINAHL (455), Embase (1,916) and Web of Science (1,509). After removing 2,864 duplicate records, 2,234 records remained for screening. During screening, 2,190 records were excluded based on title and abstract. Forty-four reports were sought for retrieval and all were assessed for eligibility. Of these, 29 reports were excluded for reasons such as no relevant mitigation strategy or intervention (12), only measuring or describing time burden (8), no relevant outcomes (5) and not being relevant to the target population (4). Finally, 15 studies were included in the scoping review.

Open in a new tab

PRISMA flow diagram of the study selection process. Adapted from the PRISMA 2020 flow diagram template: Page MJ, McKenzie JE, Bossuyt PM et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.

Characteristics of Included Studies

The 15 included studies were published between 2017 and 2026 and were mainly conducted in the United States (n=9),18,20,23–29 Canada (n=2),30,31 Italy (n=2),19,32 and China (n=2).33,34 The study populations covered breast cancer,27 prostate cancer,26 gynecologic cancer,24,34 gastrointestinal cancers,20,25,30 hematologic malignancies,29,31 hepatocellular carcinoma,33 and mixed cancer populations.18,19,23,28,32 As shown in Table 1, the included studies involved adult cancer populations or adult oncology care settings; no pediatric cancer studies were included in the final synthesis. Most studies used retrospective observational designs,19,23,24,26–28,31–34 while others involved secondary or post hoc analyses,25,29,30 a pilot randomized controlled trial,18 or qualitative research.20 The care settings included systemic therapy,25,29,30,33 radiotherapy,26,27,34 cancer surveillance,24 supportive care,23,31 shared or closer-to-home care,19,28,31,32 and palliative treatment decision-making.20,30 Study characteristics are presented in Table 1.

Table 1.

Characteristics of Included Studies (n=15)

Study REFERENCE Country Cancer Type/Population Sample size Study Design Care Setting
Agrawal 202325 United States Patients with metastatic esophageal and gastric cancers 18 Phase III trials Secondary analysis of 18 phase III trials Systemic therapy selection
Bai 202423 United States Patients treated at a comprehensive cancer center who received travel support 1063 Retrospective analysis Supportive care services in a comprehensive cancer center
Bange 202518 United States Patients with solid tumors receiving single-agent immune checkpoint inhibitors 31 Pilot randomized controlled trial Ambulatory immune checkpoint inhibitor infusion
Cavanna 202319 Italy Patients receiving active cancer treatment 546 Retrospective study Active anticancer treatment in territorial hospitals or health centres closer to patients’ residences
Cavanna 202532 Italy Patients receiving active cancer treatment 2132 Retrospective study Active anticancer treatment in rural hospitals and one health centre closer to patients’ residences
Gupta 202330 Canada Patients with advanced colorectal cancer in the CCTG CO.17 trial 572 Secondary analysis of randomized clinical trial Palliative oncology care
Hershenfeld 201731 Canada Patients with AML or acute promyelocytic leukemia receiving consolidation therapy 417 Retrospective cohort study Post-consolidation supportive care
Hui 202533 China Patients with hepatocellular carcinoma receiving systemic therapy 4677 Retrospective cohort study Systemic therapy for hepatocellular carcinoma
Johnson 202520 United States Advanced gastrointestinal cancer patients, care partners, and oncology clinicians 47 Qualitative study Cancer care delivery
Lee 202634 China Patients with stage III endometrial cancer 119 Retrospective study Adjuvant chemoradiation
Liu 202526 United States Men with localized prostate cancer 69 Retrospective cohort study Radiation therapy for localized prostate cancer
Masarova 202429 United States Patients with myelofibrosis and anemia 195 Post hoc analysis Systemic therapy and transfusion support
Scodari 202428 United States Rural breast, colorectal,and lung cancer patients 355139 Cross-sectional study Oncology workforce distribution and treatment delivery
Shridhar 202524 United States Patients with gynecologic cancer in remission in rural communities 63 Retrospective chart review Gynecologic cancer survivorship surveillance
Swanick 202127 United States Patients with early-stage breast cancer 35406 Database-based cohort study Local therapy for early-stage breast cancer
Open in a new tab

Time-Toxicity-Related Indicators

The measures of time toxicity varied across the included studies and mainly covered travel, care encounters, health care contact days, and treatment delivery. Travel-related measures included travel distance, travel time, and overall travel burden,19,23,28,31,32 whereas encounter-related measures included waiting time and total encounter time.18 Several studies used health care contact days, time-toxic days, home days, outpatient days, hospital days, and emergency department days to assess the amount of patients’ time consumed by cancer care.25,30,33

Strategies to Mitigate Time Toxicity

The mitigation strategies identified from the included studies were synthesized into four major domains: decentralized and care closer to home, digital technology-supported care and workflow optimization, individualized scheduling and logistical support, and treatment-related time burden optimization. The strategy domains and supporting studies are summarized in Table 2. A graphical summary of the time-toxicity-related indicators and the four mitigation strategy domains is presented in Figure 2.

Table 2.

Summary of Strategies to Reduce Time Toxicity in Cancer Care

Strategy Domain Specific Strategy and Operational Approach Supporting Study Targeted Time-Toxicity Indicators Main Evidence Relevant to Time-Toxicity Reduction
Decentralized and care closer to home Territorial Oncology Care: delivering anticancer treatment in community hospitals, rural hospitals, or health centres closer to patients’ residences. Cavanna 202319 Travel distance; travel time; caregiver accompaniment burden. The TOC model reduced the need for patients to travel repeatedly to central cancer centres by moving selected anticancer treatments closer to patients’ homes.
Territorial Oncology Care: expanding the TOC cohort to further evaluate reductions in travel burden and travel-related resource use. Cavanna 202532 Travel distance saved; travel-related burden. The expanded TOC evaluation further supported the role of territorial care in reducing travel distance and travel-related burden.
Oncology outreach care: providing oncology services to rural or underserved areas through a traveling oncology workforce. Scodari 202428 Travel time; travel burden among rural patients. Traveling oncology workforce models were associated with reduced travel burden for rural patients by bringing oncology services closer to underserved areas.
Local shared supportive care: providing part of post-consolidation supportive care through local centres. Hershenfeld 201731 Travel distance; travel time. Shared supportive care with local centres reduced travel distance and time for patients requiring post-consolidation supportive care.
Home-based or closer-to-home care proposals: providing home-based care when feasible and reducing long-distance travel. Johnson 202520 Perceived time burden; care delivery burden; patient and care partner time burden. Patients, care partners, and clinicians proposed home-based care and care closer to home as ways to reduce practical and perceived time burden.
Digital technology-supported care and workflow optimization Hybrid telehealth follow-up: using a hybrid shared-care model that combines local in-person assessment with remote gynecologic oncology consultation. Shridhar 202524 Travel distance; surveillance burden. The STEEL MAGNOLIAS hybrid shared telehealth model reduced travel burden during gynecologic cancer survivorship surveillance while maintaining specialist input.
Electronic triage and fast-track pathway: symptom reporting by text message before treatment, electronic triage, and fast-track infusion. Bange 202518 Waiting time; total encounter time. Text-message symptom reporting with e-triage and fast-track infusion reduced total encounter time and shortened waiting time during ambulatory immunotherapy infusion.
Individualized scheduling and logistical support Transportation and financial support: providing gas cards, rideshare services, taxi vouchers, or public transportation support. Bai 202423 Travel time; transportation and logistical burden. Transportation assistance and related support services addressed logistical barriers to accessing cancer care.
Individualized scheduling and administrative coordination: arranging appointments according to patients’ work, family responsibilities, and care needs; consolidating same-day tests and treatments. Johnson 202520 Repeated travel; appointment waiting time; patient and care partner time burden. Participants proposed tailored scheduling, appointment consolidation, and administrative support to reduce repeated trips and coordination burden.
Treatment-related time burden optimization Treatment delivery, sequencing, and course optimization: comparing sandwich chemoradiation with sequential chemoradiation to optimize treatment sequencing. Lee 202634 Overall treatment time; time to treatment initiation. Sandwich chemoradiation was associated with shorter treatment-related time burden compared with sequential chemoradiation in stage III endometrial cancer.
Treatment delivery, sequencing, and course optimization: comparing the number of treatments and total travel burden across HDR brachytherapy, EBRT, and SBRT. Liu 202526 Number of treatment visits; travel distance; total travel burden. HDR brachytherapy reduced travel burden compared with conventional EBRT, while SBRT could be less burdensome for patients living farther from the brachytherapy centre.
Time-toxicity-informed treatment selection and shared decision-making: comparing healthcare days and medical care days across systemic treatment regimens. Agrawal 202325 Healthcare days; medical care days. Systemic regimens for advanced esophageal and gastric cancers differed in healthcare days, indicating that treatment choice can affect time spent receiving medical care.
Treatment delivery, sequencing, and course optimization: comparing the time burden of different local therapy strategies and radiotherapy fractionation approaches for early-stage breast cancer. Swanick 202127 Inpatient days; outpatient days; radiation days; total time burden. Time burden differed across local therapy strategies; breast-conserving surgery with whole-breast irradiation had the highest time burden, while shorter radiotherapy schedules may reduce burden.
Treatment-related time burden optimization Time-toxicity-informed treatment selection and shared decision-making: comparing days at home, hospitalization days, and emergency department days between immunotherapy and tyrosine kinase inhibitors. Hui 202533 Days at home; hospitalization days; emergency department days. Immunotherapy and tyrosine kinase inhibitors differed in days at home and hospital-based care days, supporting time-toxicity-informed systemic therapy selection.
Time-toxicity-informed treatment selection and shared decision-making: comparing transfusion needs and transfusion-related time burden between momelotinib and danazol. Masarova 202429 Transfusion-related time; transfusion-related visits. Momelotinib was projected to reduce transfusion needs compared with danazol, thereby lowering transfusion-related time burden and related healthcare resource use.
Time-toxicity-informed treatment selection and shared decision-making: comparing time-toxic days and home days between cetuximab and best supportive care. Gupta 202330 Time-toxic days; home days. Cetuximab increased time-toxic days overall; in patients unlikely to benefit, such as KRAS-mutant disease, treatment may add time toxicity without increasing home days.
Time-toxicity-informed treatment selection and shared decision-making: transparently communicating the time required for treatment and incorporating patient and care partner time preferences. Johnson 202520 Perceived time burden; care partner burden; time costs in treatment decision-making. Participants emphasized transparent communication about time burden and incorporating patient and care partner time preferences into care planning and decision-making.
Open in a new tab

Figure 2.

A diagram of time-toxicity indicators and strategies to mitigate time toxicity in cancer care. The diagram highlights strategies to reduce time toxicity in cancer care across four areas: 1. Travel, focusing on distance and burden. 2. Care encounters, addressing waiting times. 3. Care contact and home time, including healthcare contact days and outpatient visits. 4. Treatment delivery, covering treatment visits and initiation time. Invisible burdens involve scheduling and transportation. No standard tool measures time toxicity. Strategies include: 1. Decentralized care to reduce travel. 2. Digital support to minimize travel and encounter time. 3. Individualized scheduling to ease access barriers. 4. Treatment time optimization, considering time costs beyond clinical outcomes.

Open in a new tab

Graphical summary of time-toxicity-related indicators and mitigation strategy domains in cancer care. The left panel summarizes the time-toxicity-related indicators identified across the included studies, including travel, care encounters, care contact and home time, treatment delivery, and perceived or less visible time burdens. The right panel summarizes the four mitigation strategy domains synthesized in this review: decentralized and closer-to-home care, digital support and workflow optimization, individualized scheduling and logistical support, and treatment-related time burden optimization.

Decentralized Care and Care Closer to Home

Travel burden received considerable attention across the included studies. Territorial oncology care enabled selected anticancer treatments to be delivered in community or rural hospitals and other local health facilities.19,32 Oncology outreach and shared-care models involved collaboration between specialist teams and local providers in delivering treatment or supportive care.28,31 Although these models differed in their organization, they generally reduced travel distance, travel time, and the need for caregiver accompaniment. These benefits were particularly relevant to patients living in rural or underserved areas. Building on these approaches, patients, care partners, and clinicians identified home-based care as a potential means of further reducing travel burden, although its implementation would need to consider safety, feasibility, and patient preferences.20

Digital Support and Workflow Optimization

Where further decentralization was not feasible, digital support and workflow redesign offered another means of reducing the need for in-person care. Hybrid telehealth combined remote specialist consultation with local assessment, allowing some follow-up care to take place without travel to a cancer center while maintaining high adherence to surveillance guidelines.24 Workflow changes addressed the time patients spent after arriving at the hospital. Text message-based symptom reporting combined with electronic triage and fast-track infusion was associated with shorter encounter time and reduced waiting during ambulatory immunotherapy infusion.18

Individualized Scheduling and Logistical Support

Time burden was also shaped by transportation, employment, family responsibilities, and caregiving demands. Transportation assistance, including gas cards, rideshare services, and public transport support, helped address practical barriers associated with travelling long distances for care.23 Patients and care partners also emphasized whether care arrangements could fit around their daily lives. Their priorities included flexible appointment times, combining tests and treatments on the same day, and reducing repeated communication and travel caused by administrative coordination. These findings illustrate that the same care pathway may impose different time burdens on different patients. Therefore, these approaches should be individualized.20

Optimization of Treatment-Related Time Burden

In contrast to service-level changes, other studies focused on the time required by treatment itself. Radiotherapy with fewer fractions, appropriate selection of radiotherapy modality, and changes in chemoradiotherapy sequencing may shorten treatment courses or reduce travel, although the effects vary by treatment regimen and the distance patients live from the treatment centre.26,27,34 Systemic treatment studies compared regimens using health care days, days at home, hospital days, emergency department days, and transfusion-related time, showing that treatment options may differ in their time costs beyond conventional clinical outcomes.25,30,33 Reducing transfusion requirements may also save time, although the available estimates were model-based.29 Qualitative findings further suggested that the time required by different treatments should be discussed with patients and that patient and care-partner time preferences should be considered when treatment options are selected.20

Discussion

This scoping review included 15 studies and identified four main approaches to reducing time toxicity in cancer care: decentralized and closer-to-home care, digital support and workflow optimization, individualized scheduling and logistical support, and optimization of treatment-related time burden. The measures used across the included studies covered travel, care encounters, health care contact days, and treatment delivery. However, the available evidence remains limited and is mainly based on retrospective observational studies. The findings therefore identify possible directions for reducing time toxicity but do not establish the comparative effectiveness of these strategies.

From Time-Burden Measurement to Care Redesign

The findings suggest that time toxicity arises not only from treatment itself, but also from the multiple activities required for patients to access, receive, and manage cancer care. This challenges a long-standing assumption in oncology care: that clinical benefit can be evaluated without fully accounting for the time patients must invest to obtain that benefit.35 Traditional oncology outcomes commonly emphasize survival, tumor response, adverse events, and quality of life, while the time patients spend traveling, waiting, coordinating care, receiving treatment, recovering, and being accompanied by caregivers is often treated as a background cost outside the core medical process.7,36 Emerging evidence suggests that this boundary is becoming increasingly difficult to maintain.37 Time is not merely a logistical issue surrounding cancer care; it is a valuable resource consumed by cancer care itself.6 This interpretation is consistent with previous conceptual and review work, which has described time toxicity as a multidimensional burden involving not only health care contact time, but also travel, waiting, coordination, recovery, and disruption to everyday life.6,11,12,35

Redistribution of Time Burden Across Care Settings

This perspective also changes the meaning of “mitigation.” Reducing time toxicity is not simply a matter of making services faster or more convenient; it also requires asking where the work of care is being located and whose time is being protected.14 Territorial oncology care, outreach services, shared-care models, and telehealth can reduce the time patients spend traveling to central cancer centers.24,28,31,32 However, these models may also depend on local health care resources, patients’ self-management capacity, caregiver involvement, and coordination across institutions. In other words, time may be saved, but it may also be redistributed.38 A strategy may reduce the time patients spend in hospital while shifting hidden time costs to patients and families through additional communication, technology use, symptom monitoring, or home-based coordination.39–41 Therefore, whether a strategy truly mitigates time toxicity should not be judged only by health system efficiency, but also by whether patients and caregivers actually gain more discretionary time.

Time-Toxicity-Informed Treatment Decision-Making

In addition to service-level modifications, the included studies comparing treatment approaches showed that different radiotherapy modalities, treatment sequencing strategies, systemic therapy regimens, and transfusion requirements may impose different time costs.25–27,29,30,33,34 These findings suggest that time toxicity is not only a consequence of inefficient care organization, but also an inherent burden associated with treatment itself. When treatment benefits are limited or when several clinically acceptable options are available, time cost should be considered alongside efficacy, safety, and quality of life in assessing treatment value.42,43

Studies suggest that the time required for treatment should be made visible to patients when they are trying to understand and compare treatment options. This is consistent with the principle of shared decision-making, which emphasizes the incorporation of patient values and preferences into treatment choices.44 If patients are not informed in advance about hospitalization days, travel frequency, waiting time, treatment duration, and potential care coordination demands, they are effectively making treatment decisions without key information about the costs of care. For patients with advanced cancer, previous studies have also shown that understanding of treatment goals and expected benefits is often incomplete, and that the quality of treatment communication can influence subsequent care choices.45,46 Incorporating time toxicity into shared decision-making may therefore help patients with advanced cancer more realistically weigh treatment benefits against the personal time required to obtain them.

Measurement Challenges and Equity Considerations

The measurement of time toxicity remains inconsistent, limiting comparability across studies. A previous scoping review of prospective oncology studies similarly found that time toxicity was infrequently reported and lacked standardized definitions, metrics, and methodological approaches.11 More recently, a systematic review and meta-analysis of cancer pharmacotherapy trials quantified time toxicity using health care contact days and further emphasized the need to prioritize the measurement and mitigation of time toxicity in oncology research.47 Different indicators capture different dimensions of time burden and, importantly, determine which burdens become visible. Previous work has shown that measurement instruments vary in the extent to which they capture physical, emotional, social, and functional aspects of patients’ everyday lives.48 Travel time and health care contact days are relatively easy to quantify, but they may underestimate less visible costs such as waiting, coordination, caregiver involvement, and recovery after treatment. Days at home may better reflect the time patients retain outside the health care system, but this measure still cannot fully capture the quality of that time.49–51 Future research should develop more consistent core measures while preserving attention to patients’ lived experience of time burden. These measurement choices also have equity implications, because travel distance, waiting time, caregiver involvement, and administrative burden may affect patients differently depending on residence, income, employment flexibility, transportation access, digital literacy, and available family support.

Implications for Nursing and Supportive Care

For nursing and supportive care, time toxicity offers a practical but still underdeveloped point of intervention. Nurses and patient navigators are often positioned at key points along the care pathway and are able to identify practical barriers to timely treatment, including transportation, appointment scheduling, financial difficulties, and communication problems.52 Incorporating time burden assessment into routine nursing evaluation may help identify patients who need appointment consolidation, transportation assistance, local follow-up, proactive symptom triage, or clearer communication about the time required for treatment. However, this process should not become another self-report task that patients are expected to manage alone. Previous research has shown that remote symptom monitoring based on patient-reported outcomes can improve symptom management and patient experience, and may reduce some forms of acute care use.53 This suggests that nurse-led or team-supported symptom triage may be an important pathway for reducing avoidable health care contacts. Time toxicity also involves caregiver time. Educational, psychological, and digital follow-up interventions may help reduce burden among family caregivers of patients with cancer.54 Therefore, time toxicity should be understood as a problem of care system design, rather than merely as an individual burden that patients must learn to adapt to.

Future Directions

Overall, research on time toxicity is moving beyond the description of patients’ time burden toward a broader reconsideration of how cancer care is organized and how treatment value is assessed. Future studies should not be limited to reporting isolated time-related indicators. Instead, they should work toward more consistent measurement approaches and use more prospective designs to evaluate the real-world effects of different mitigation strategies. More importantly, time toxicity should be considered at the stage of treatment planning and care pathway design, rather than being addressed only after patients have already been forced to reorganize their lives around treatment.

Limitations

This review has several limitations. First, only empirical studies available in English full text and reporting strategies related to time-toxicity mitigation were included, and grey literature was not searched. Relevant evidence published in other languages, unpublished sources, or locally implemented care models may therefore have been missed. Second, the review protocol was not prospectively registered. However, the review was conducted according to JBI methodological guidance and reported using the PRISMA-ScR checklist, and the complete search strategies are provided in Appendix B to support transparency and reproducibility. Third, the included studies varied substantially in sample size, cancer type, care setting, study design, and time-toxicity-related indicators, and most were retrospective or observational studies. These differences limited direct comparison across studies and may affect the generalizability of the findings to specific cancer populations, care settings, or health care systems. Finally, formal methodological quality appraisal or risk-of-bias assessment was not conducted, which is consistent with the purpose of a scoping review. Therefore, the findings should be used to describe the scope of existing evidence and identify future research directions, rather than as definitive conclusions about the effectiveness of specific strategies.

Conclusion

Time toxicity shifts the evaluation of cancer care from focusing only on what treatment patients receive to also considering how much personal time they must spend to receive it. Meaningful mitigation should not be limited to shortening clinic visits; it should also reduce avoidable time burden for patients and caregivers, while avoiding the transfer of care work from health care institutions to the home. Future efforts should proactively account for patient time during treatment planning and care pathway design, further define core measures of time toxicity, and incorporate expected time commitments into patient-clinician communication and shared decision-making. Protecting the discretionary time of patients and caregivers should be recognized as an essential component of patient-centred cancer care. These findings have implications for clinical practice, education, and policy. In clinical practice, time burden assessment may be incorporated into routine oncology nursing and supportive care to identify patients who need appointment consolidation, transportation support, local follow-up, proactive symptom triage, or clearer communication about treatment time. In education, oncology professionals should be trained to recognize time toxicity as part of patient-centred care, treatment burden, and shared decision-making. At the policy level, time-related indicators such as travel burden, waiting time, health care contact days, days at home, and caregiver time should be considered when evaluating oncology service models and allocating supportive care resources.

Funding Statement

No external funding was received for this study.

Data Sharing Statement

This scoping review is based on publicly available literature. All data analyzed in this study are available from the corresponding author upon reasonable request.

Disclosure

The authors declare no competing interests.

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 Cancer J Clin. 2024;74(3):229–15. doi: 10.3322/caac.21834 [DOI] [PubMed] [Google Scholar]
  • 2.Siegel RL, Kratzer TB, Wagle NS, et al. Cancer statistics, 2026. CA Cancer J Clin. 2026;76(1):e70043. doi: 10.3322/caac.70043 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Shapiro CL. Cancer Survivorship. New England J Med. 2018;379(25):2438–2450. doi: 10.1056/NEJMra1712502 [DOI] [PubMed] [Google Scholar]
  • 4.Miller KD, Nogueira L, Devasia T, et al. Cancer treatment and survivorship statistics. CA Cancer J Clin. 2022;72(5):409–436. doi: 10.3322/caac.21731 [DOI] [PubMed] [Google Scholar]
  • 5.Carrera PM, Kantarjian HM. Blinder vs The financial burden and distress of patients with cancer: understanding and stepping-up action on the financial toxicity of cancer treatment. CA Cancer J Clin. 2018;68(2):153–165. doi: 10.3322/caac.21443 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Nwozichi C, Omolabake S, Ojewale MO, et al. Time toxicity in cancer care: a concept analysis using Walker and Avant’s method. Asia Pac J Oncol Nurs. 2024;11(12):100610. doi: 10.1016/j.apjon.2024.100610 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Fundytus A, Prasad V, Booth CM. Has the Current Oncology Value Paradigm Forgotten Patients’ Time?: too Little of a Good Thing. JAMA Oncology. 2021;7(12):1757–1758. doi: 10.1001/jamaoncol.2021.3600 [DOI] [PubMed] [Google Scholar]
  • 8.Hall ET, Sridhar D, Singhal S, et al. Perceptions of time spent pursuing cancer care among patients, caregivers, and oncology professionals. Supportive Care Cancer. 2021;29(5):2493–2500. doi: 10.1007/s00520-020-05763-9 [DOI] [PubMed] [Google Scholar]
  • 9.Given BA, Given CW, Sherwood P. The challenge of quality cancer care for family caregivers. Seminars Oncol Nurs. 2012;28(4):205–212. doi: 10.1016/j.soncn.2012.09.002 [DOI] [PubMed] [Google Scholar]
  • 10.Sekar P, Johnson WV, George M, et al. “The biggest challenge is there’s never a routine”: a qualitative study of the time burdens of cancer care at home. Supportive Care Cancer. 2025;33(2):80. doi: 10.1007/s00520-024-09132-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Quinn PL, Saiyed S, Hannon C, et al. Reporting time toxicity in prospective cancer clinical trials: a scoping review. Support Care Cancer. 2024;32(5):275. doi: 10.1007/s00520-024-08487-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Li Z, Liu Y, Zhang J, et al. Cancer patients’ experiences of “time toxicity”: a qualitative meta-synthesis. Supportive Care Cancer. 2026;34(6):588. doi: 10.1007/s00520-026-10828-2 [DOI] [PubMed] [Google Scholar]
  • 13.Jing J, Li M, Rui Y, et al. The weight of time: experience of time toxicity among advanced cancer patients and their family caregivers-a qualitative study. Support Care Cancer. 2025;33(10):862. doi: 10.1007/s00520-025-09904-w [DOI] [PubMed] [Google Scholar]
  • 14.Johnson WV, Blaes AH, Booth CM, et al. The unequal burden of time toxicity. Trends Cancer. 2023;9(5):373–375. doi: 10.1016/j.trecan.2023.01.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Lin K, Kagalwalla S, Gupta A. Characterizing and addressing the financial, time, and administrative burdens of cancer and its car. Curr Treat Options Oncol. 2025;26(12):1078–1085. doi: 10.1007/s11864-025-01358-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Duffens AM, Zhu S, Shirazi A, et al. Telehealth and health care contact days among patients with advanced cancer after COVID-19. JAMA Netw Open. 2025;8(6):e2516762. doi: 10.1001/jamanetworkopen.2025.16762 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Gupta A, Nguyen P, Wilson BE, et al. Health care contact days and outcomes in clinical trials vs routine care among patients with non-small cell lung cancer. JAMA Netw Open. 2025;8(4):e255033. doi: 10.1001/jamanetworkopen.2025.5033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Bange EM, Coughlin KQ, Li W, et al. A text message intervention to minimize the time burden of cancer care. NEJM Catal Innov Care Deliv. 2025;6(3). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Cavanna L, Citterio C, Mordenti P, et al. Cancer treatment closer to the patient reduces travel burden, time toxicity, and improves patient satisfaction, results of 546 consecutive patients in a Northern Italian district. Medicina. 2023;59(12). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Johnson WV, Valisekka SS, Ogunleye OO, et al. Patient-, care partner-, and clinician-proposed solutions to address the time toxicity of cancer care. Support Care Cancer. 2025;33(11):965. doi: 10.1007/s00520-025-09954-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Arksey H, O’malley L. Scoping studies: towards a methodological framework. Int J Soci Res Methodol. 2005;8(1):19–32. doi: 10.1080/1364557032000119616 [DOI] [Google Scholar]
  • 22.Peters MDJ, Marnie C, Tricco AC, et al. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synth. 2020;18(10):2119–2126. doi: 10.11124/JBIES-20-00167 [DOI] [PubMed] [Google Scholar]
  • 23.Bai J, Barandouzi ZA, Yeager KA, et al. Analysis of travel burden and travel support among patients treated at a comprehensive cancer center in the Southeastern United States. Support Care Cancer. 2024;32(7):451. doi: 10.1007/s00520-024-08656-3 [DOI] [PubMed] [Google Scholar]
  • 24.Shridhar A, Viator S, Castellano T, et al. Minimizing travel burden of gynecologic cancer surveillance through a unique multidisciplinary telehealth program. O&G Open. 2025;2(5):e129–e. doi: 10.1097/og9.0000000000000129 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Agrawal NY, Thawani R, P EC, et al. Estimating the time toxicity of contemporary systemic treatment regimens for advanced esophageal and gastric cancers. Cancers. 2023;15(23):5677. doi: 10.3390/cancers15235677 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Liu C, Yang H, Bylund K, et al. High-dose-rate brachytherapy lowers travel burden for men with localized prostate cancer compared with external beam radiation. Front Urol. 2025;5:1598726. doi: 10.3389/fruro.2025.1598726 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Swanick CW, Jiang J, A MJ, et al. Differences in time burden across local therapy strategies for early-stage breast cancer. Plastic Reconstruct Surgery Global Open. 2021;9(11):e3904. doi: 10.1097/GOX.0000000000003904 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Scodari BT, P SA, S KN, et al. Characterizing the traveling oncology workforce and its influence on patient travel burden: a claims-based approach. Jco Oncol Prac. 2024;20(6):787–796. doi: 10.1200/OP.23.00690 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Masarova L, Verstovsek S, Liu T, et al. Transfusion-related cost offsets and time burden in patients with myelofibrosis on momelotinib vs danazol from MOMENTUM. Future Oncol. 2024;20(30):2259–2270. doi: 10.1080/14796694.2024.2368450 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Gupta A, O’callaghan CJ, Zhu L, et al. Evaluating the time toxicity of cancer treatment in the CCTG CO.17 trial. JCO Oncol Pract. 2023;19(6):e859–e66. doi: 10.1200/OP.22.00737 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Hershenfeld SA, Maki K, Rothfels L, et al. Sharing post-AML consolidation supportive therapy with local centers reduces patient travel burden without compromising outcomes. Leuk Res. 2017;59:93–96. doi: 10.1016/j.leukres.2017.05.023 [DOI] [PubMed] [Google Scholar]
  • 32.Cavanna L, Citterio C, Bosi C, et al. Travel burden and carbon dioxide emission reductions through a model of cancer care closer to the patient. Oncologist. 2025;30(2). doi: 10.1093/oncolo/oyaf021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Hui RW-H, Chung MS-H, Li L, et al. Disparate patterns of disease time burden in patients with HCC on immunotherapy or tyrosine kinase inhibitors. Jhep Reports. 2025;7(11):101578. doi: 10.1016/j.jhepr.2025.101578 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Lee K-Y, Tseng T-H, Chang W-C, et al. Survival outcomes and time toxicity of Sandwich versus Sequential chemoradiation in Stage III endometrial cancer: a real-world study stratified by molecular classification. Gynecologic Oncol. 2026;206:117–124. doi: 10.1016/j.ygyno.2026.02.007 [DOI] [PubMed] [Google Scholar]
  • 35.Gupta A, Eisenhauer EA, Booth CM. The time toxicity of cancer treatment. J Clin Oncol. 2022;40(15):1611–1615. doi: 10.1200/JCO.21.02810 [DOI] [PubMed] [Google Scholar]
  • 36.B RG, P WC, A IS, et al. Health care-related time costs in patients with metastatic breast cancer. Cancer Med. 2020;9(22):8423–8431. doi: 10.1002/cam4.3461 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.May C, Montori VM, Mair FS. We need minimally disruptive medicine. BMJ. 2009;339:b2803. doi: 10.1136/bmj.b2803 [DOI] [PubMed] [Google Scholar]
  • 38.Dona AC, Jewett PI, Hwee S, et al. Logistic burdens of cancer care: a qualitative study. PLoS One. 2024;19(4):e0300852. doi: 10.1371/journal.pone.0300852 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Kyle MA, Frakt AB. Patient administrative burden in the US health care system. Health Serv Res. 2021;56(5):755–765. doi: 10.1111/1475-6773.13861 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Parsons HM, Gupta A, Jewett P, et al. The intersecting time, administrative, and financial burdens of a cancer diagnosis. JNCI. 2025;117(4):595–600. doi: 10.1093/jnci/djae252 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Adam R, Nair R, F DL, et al. Treatment burden in individuals living with and beyond cancer: a systematic review of qualitative literature. PLoS One. 2023;18(5):e0286308. doi: 10.1371/journal.pone.0286308 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Schnipper LE, Davidson NE, Wollins DS, et al. American society of clinical oncology statement: a conceptual framework to assess the value of cancer treatment options. J Clin Oncol. 2015;33(23):2563–2577. doi: 10.1200/JCO.2015.61.6706 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Gupta A, D BM, Galica J, et al. Patients’ considerations of time toxicity when assessing cancer treatments with marginal benefit. Oncologist. 2024;29(11):978–985. doi: 10.1093/oncolo/oyae187 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Gilligan T, Coyle N, Frankel RM, et al. Patient-clinician communication: american society of clinical oncology consensus guideline. J Clin Oncol. 2017;35(31):3618–3632. doi: 10.1200/JCO.2017.75.2311 [DOI] [PubMed] [Google Scholar]
  • 45.Weeks Jane C, Catalano Paul J, Cronin A, et al. Patients’ expectations about effects of chemotherapy for advanced cancer. New England J Med. 2012;367(17):1616–1625. doi: 10.1056/NEJMoa1204410 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Bernacki RE, block SD. Communication about serious illness care goals: a review and synthesis of best practices. JAMA Intern Med. 2014;174(12):1994–2003. doi: 10.1001/jamainternmed.2014.5271 [DOI] [PubMed] [Google Scholar]
  • 47.Chow R, HB IJ, Richards GC, et al. Time toxicity of patients with cancer enrolled in clinical trials: a systematic review and meta-analysis. BMJ Support Palliat Care. 2026;16(4):787–795. doi: 10.1136/spcare-2025-006038 [DOI] [PubMed] [Google Scholar]
  • 48.Catt S, Starkings R, Shilling V, et al. Patient-reported outcome measures of the impact of cancer on patients’ everyday lives: a systematic review. J Cancer Surviv. 2017;11(2):211–232. doi: 10.1007/s11764-016-0580-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Gupta A, Jazowski SA, Vaidya AU, et al. Health care contact days in older adults with metastatic cancer. JAMA Network Open. 2025;8(12):e2547924–e. doi: 10.1001/jamanetworkopen.2025.47924 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Vogel RI, Jewett P, Parsons H, et al. Time burden in patients with metastatic breast and ovarian cancer from clinic and home demands. JAMA Network Open. 2025;8(12):e2549957–e. doi: 10.1001/jamanetworkopen.2025.49957 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Stevens SX, El-Katateny E, De Abreu Lourenço R, et al. “The cancer is my life”: patient and caregiver perceptions of the time toxicity of palliative systemic cancer treatments for advanced gastrointestinal cancers. Supportive Care Cancer. 2025;33(7):564. doi: 10.1007/s00520-025-09621-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Chen M, S WV, Falk D, et al. Patient navigation in cancer treatment: a systematic review. Curr Oncol Rep. 2024;26(5):504–537. doi: 10.1007/s11912-024-01514-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Basch E, Schrag D, Jansen J, et al. Symptom monitoring with electronic patient-reported outcomes during cancer treatment: final results of the PRO-TECT cluster-randomized trial. Nat Med. 2025;31(4):1225–1232. doi: 10.1038/s41591-025-03507-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Kako J, Kobayashi M, Kanno Y, et al. Nursing support for symptoms in patients with cancer and caregiver burdens: a scoping review protocol. BMJ Open. 2022;12(9):e061866. doi: 10.1136/bmjopen-2022-061866 [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

Studies were excluded if they did not provide extractable time-toxicity-related indicators or qualitative findings relevant to this review.

This scoping review is based on publicly available literature. All data analyzed in this study are available from the corresponding author upon reasonable request.

Articles from Journal of Multidisciplinary Healthcare are provided here courtesy of Dove Press

RESOURCES