Introduction
With the continuous rise in the global incidence and mortality of cancer, cancer has become a major public health issue ( 1 ). Statistics show that the total number of cancer cases in China and the United States accounts for 24.2 and 11.9% of the global total, respectively ( 1 , 2 ). Cancer imposes a heavy economic burden on patients and healthcare systems worldwide. Even with substantial investment in medical insurance, a considerable proportion of cancer patients still face severe financial hardship. From 2018 to 2025, China’s central fiscal investment in medical insurance exceeded 3 trillion yuan, yet 40% of patients still experienced financial toxicity ( 3 , 4 ). However, this problem is not unique to developing countries; developed countries are also affected. Total healthcare expenditure on cancer treatment in the United States is projected to increase by an additional 44.9 billion USD by 2030 ( 5 ).
Financial toxicity refers to the adverse economic impact of cancer on patients and their families, and it has received increasing attention as an important patient-reported outcome ( 6 ). It includes direct costs (e.g., out-of-pocket expenses for treatment and medications) and indirect costs (e.g., income loss and reduced working hours), and is closely associated with treatment adherence, quality of life, and clinical outcomes ( 6–8 ).
Although a growing number of cancer studies have focused on financial toxicity, the vast majority adopted a cross-sectional design. In a cross-sectional study of 198 cancer patients, Perni et al. ( 9 ) found that more severe financial toxicity was associated with greater physical symptom burden and increased depression and anxiety. Similarly, a national cross-sectional survey of 664 Chinese breast cancer patients also identified the impacts of treatment modalities and demographic factors on financial toxicity ( 10 ). Overall, while these studies have demonstrated significant associations between financial toxicity and various psychological and physical symptoms, cross-sectional studies can only reveal associations at a single time point. They cannot clarify temporal order or causal direction, nor can they distinguish whether symptoms are risk factors or consequences of financial toxicity ( 11 ). More importantly, existing longitudinal evidence remains limited and fragmented. High heterogeneity exists across studies in measurement tools, follow-up duration, and assessment time points, making it difficult to determine the optimal screening timing and limiting the development of subsequent intervention studies and health-related policies.
Compared with cross-sectional studies, longitudinal studies can clarify the dynamic trajectory, long-term patterns, and predictive factors of financial toxicity throughout the cancer continuum. This scoping review examines the measurement time points, assessment tools, developmental trends, and influencing factors of financial toxicity among cancer patients in longitudinal studies. It aims to provide a reference for future research and standardized management of financial toxicity in cancer patients, and to support the development of evidence-based policies to reduce disparities and promote health equity.
Methods
A scoping review aims to examine the scope and nature of existing research on a topic or issue, determine the value of conducting a full systematic review, and identify gaps in current research ( 12 ). The methodology of a scoping review is based on the framework proposed by Arksey and O’Malley ( 13 ). We conducted this review in accordance with the Joanna Briggs Institute (JBI) Reviewer’s Manual approach ( 14 ), which includes the following stages: (a) identifying the review question; (b) inclusion and exclusion criteria; (c) search strategy; (d) evidence screening and selection; (e) data extraction; (f) data analysis; and (g) presentation of results. This scoping review was registered in the Open Science Framework (OSF) prior to the literature search, with the registration number 10.17605/OSF.IO/T795E. According to the scoping review methodology proposed by Peters et al. ( 14 ), quality assessment of the included evidence is generally not required. Therefore, no quality assessment was included in this review.
Identifying the review questions
The specific review questions are as follows: (1) What are the options for measurement time points in longitudinal studies on financial toxicity among cancer patients? (2) What are the options for assessment tools in longitudinal studies on financial toxicity among cancer patients? (3) What are the changing trends of financial toxicity among cancer patients? (4) What are the influencing factors of financial toxicity among cancer patients in longitudinal studies?
Eligibility criteria
The inclusion criteria were determined using the PICOS framework (Population, Intervention, Comparator, Outcome, Study design) ( 15 ). As the included studies were observational in nature, intervention and comparator components were not applicable.
Inclusion criteria:
(1) Study participants: Patients pathologically diagnosed with cancer, aged ≥ 18 years.
(2) Study design: Observational studies adopting a longitudinal research method.
(3) Outcome measures: Studies reporting the influencing factors of financial toxicity among cancer patients.
(4) Assessment standards: Studies using explicit assessment tools or diagnostic criteria for financial toxicity.
Exclusion criteria:
(1) Studies only presenting viewpoints without specific data or supporting materials;
(2) Studies not focusing on financial toxicity in cancer patients aged ≥18 years;
(3) Literature not written in English or Chinese;
(4) Reviews, dissertations, editorials, commentaries, and other forms of expert opinions.
Search strategy
A systematic search was conducted across the following databases: PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wan Fang Data, VIP Chinese Science and Technology Journal Database, and Chinese Biomedical Literature Database (CBM). The search timeframe spanned from the inception of each database to November 8, 2025.
Screening and selection of evidence
The retrieved literature was imported into EndNote X9. First, duplicate studies were identified and removed. According to the inclusion and exclusion criteria, two trained researchers independently screened the titles and abstracts for initial eligibility, followed by a second screening through careful full-text review. Any disagreements were resolved through discussion with a third researcher. After confirming the included articles, the reference lists of the included studies were manually searched. Finally, all selected studies were checked by the reviewers. Data extracted from the included literature included: author, country, year of publication, cancer type, sample size, dropout rate, assessment tool and cutoff value, measurement time point, score, and influencing factors. The processes of study screening, data extraction, and analysis in this study were performed manually by researchers without the use of artificial intelligence (AI) tools.
Search outcome
The initial search yielded a total of 1,035 articles. After removing 376 duplicate publications using EndNote X9, 659 records remained for the initial screening. According to the inclusion and exclusion criteria, 350 articles were excluded after screening the titles and abstracts, including 82 review articles, 125 articles with inappropriate study population, 119 articles with inappropriate study design, and 24 articles with unavailable full text. A total of 309 articles proceeded to full-text screening. During the full-text evaluation, 295 articles were further excluded, including 21 articles with incomplete data and 274 articles with inappropriate study design. After rigorous screening, a total of 14 articles were finally included in this scoping review ( Figure 1 ).

Results
Literature search outcomes
A total of 1,035 articles were retrieved initially, and 14 studies were finally included after screening. Among the included articles, 6 were conducted in China ( 16–21 ), 6 in the United States ( 22–27 ), 1 in Germany ( 28 ), and 1 in Malaysia ( 29 ). The basic characteristics of the included studies are presented in detail in Table 1 .
Table 1
Basic information of the included literature ( n = 14).
(1) Physical symptom burden (2) psychological symptom burden (3) self-efficacy (4) out-of-pocket expenses (5) monthly per capita household income (6) unplanned expenses (7) distance to hospital (8) family function (9) medical insurance (10) social support (11) place of residence (12) household savings (13) treatment method (14) subjective socioeconomic status (15) annual household income (16) impact on quality of life (17) age (18) gender (19) educational level (20) measurement time (21) ability to afford basic treatment (22) loss of wages, salaries or benefits (23) per capita household income (24) preoperative social function (25) tumor stage.
| Author | Country | Year | Tumor Type | Sample size | Attrition rate (%) | Assessment tool | Cut-off value | Measurement time point(s) | Score | Influencing factors |
| Li X. X. et al. | China | 2025 | Pancreatic cancer | 340 | 23.8 | COST-PROM | Score < 26 = positive | At admission, at discharge, 3 months after discharge, 6 months after discharge | —— | (3) (4) (5) (6) (7) |
| Wu Y et al. | China | 2025 | Glioma | 266 | 9.0 | COST-PROM | Score < 26 = positive | Initial diagnosis; 3-month follow-up; 6-month follow-up | —— | (3) (8) |
| Zheng Guimei et al. | China | 2025 | Cervical cancer | 190 | 13.2 | COST-PROM | Score < 26 = positive | After the first chemotherapy, 3 months later, and 6 months later | 17.01 ± 8.90/15.15 ± 8.83/13.00 ± 8.47 | (5) (9) (10) |
| Mark A Fiala et al. | USA | 2025 | Multiple myeloma | 214 | 65 | COST-PROM | Score < 26 = positive | After the diagnosis, one year later | (17) (23) | |
| Westhofen T. et al. | German | 2024 | Prostatic cancer | 397 | — | The “Financial Toxicity Subscale” of EORTC QLQ-C30 (FTS) | FTS ≥ 17 | The maximum follow-up period was 120 months, including before the operation, 3 months after the operation, and each year thereafter | —— | (2) (13) (16) (24) |
| Kuang Yi et al. | China | 2024 | Breast cancer | 447 | 15.4 | COST-PROM | Score < 26 = positive | One week after the operation, three months after the operation, six months after the operation, and one year after the operation | 23.47 ± 10.53/22.74 ± 11.37/24.01 ± 10.57/24.24 ± 10.49 | (1) (2) (5) (9) (10) (11) (12) (13) (14) |
| Kircher S. et al. | USA | 2024 | Colorectal cancer | 450 | 66.4 | COST-PROM | Score < 26 = positive | Before the start of radiotherapy and chemotherapy, 3 months, 6 months, and 12 months | 23.5 ± 11.9/25 ± 12.4/26.0 ± 12.1/28.6 ± 11.7 | (3) (11) (15) (16) |
| Sadigh G. et al. | USA | 2024 | Colorectal cancer | 451 | 51.9 | COST-PROM | Score < 26 = positive | At the time of diagnosis, 3 months, 6 months, 12 months and 24 months | —— | (17) (18) (19) (20) |
| Storandt M. H. et al. | USA | 2023 | Breast cancer | 3,465 | 43.5 | Projects that address the financial concerns raised | 0–10 Score | At the time of diagnosis, 1 year later, 2 years later, 3 years later, 4 years later, 5 years later | 2.76 ± 3.01/2.13 ± 2.8/2.04 ± 2.65/1.83 ± 2.56/1.78 ± 2.61/1.82 ± 2.65 | (12) (17) (18) |
| Cheng Yuting et al. | China | 2023 | Brain Tumor | 256 (pairs) | 9.0 | COST-PROM | Score < 26 = positive | Three days after diagnosis, six months | —— | (8) |
| Friedes C. et al. | USA | 2021 | Lung cancer | 215 | 47.9 | COST-PROM | Score < 26 = positive | Within 5 weeks after the initial diagnosis or the start of cancer treatment, 6 months ±5 weeks | (5) (12) (21) | |
| Liang M. I. et al. | USA | 2021 | Gynecological cancer | 205 | 56.0 | COST-PROM | Score < 26 = positive | Baseline (within 8 weeks after initiating the new systemic treatment regimen), 3 months and 6 months | 23.6/25.1/25.6 | (2) (16) (22) |
| Zhang Fagu et al. | China | 2020 | Esophagus cancer | 100 | —— | The Self-perceived burden questionnaire includes an economic burden dimension | If the score is over 20, there is a sense of self-burden | One month, three months and six months after the operation | 29.46 ± 7.45/19.55 ± 5.44/17.32 ± 4.77 | (1) |
| Meram Azzani et al. | Malaysia | 2016 | Colorectal cancer | 138 | 1.4 | (1) Cost diary (2) Treatment cost Questionnaire and family Questionnaire (3) Inquiring about the subjective economic burden of patients and their families through a 5-point Likert score (4) Answering questions on financial coping strategies | —— | At the time of diagnosis, six months after diagnosis, and one year after diagnosis | —— | (13) (25) (20) |
The 14 included studies were distributed across 4 countries: the United States ( n = 6, 42.9%) and China ( n = 6, 42.9%) were the most predominant, while Germany and Malaysia each contributed 1 study (7.1% each). This highly concentrated geographic distribution indicates that the current evidence is mainly derived from North America and East Asia. Importantly, we identified a lack of relevant longitudinal studies in Africa and South America, which represents a substantial evidence gap in this field. This limitation suggests that our findings may not be generalizable to populations in these regions ( Figure 2 ).

Measurement time points and trajectories of financial toxicity
All the included studies were longitudinal investigations on financial toxicity in cancer patients, with the number of measurements ranging from 2 to 6 times. Specifically, 4 studies adopted a 3-month interval between measurements ( 19 , 21 , 23 , 25 ), while the remaining studies had fewer than 2 measurement time points. The longest follow-up duration was 5 years ( 24 ), and the shortest was 3 days after cancer diagnosis ( 17 ). Generally, after the first year of follow-up, researchers tended to set the interval of subsequent measurements as 1 year. The common measurement time points were selected as before the initiation of treatment, 3 months, 6 months, and 12 months after the start of treatment. The central tendency of measurement time point selection is illustrated in Figure 3 .

Based on the 5 studies providing detailed data, the changing trend of financial toxicity among breast cancer patients tended to be stable with a small fluctuation range. The financial toxicity of colorectal cancer patients showed a continuous upward trend, with a greater increase after 6 months. For esophageal cancer patients, financial toxicity decreased continuously, with a particularly significant decline at 1 month and 6 months after treatment. The financial toxicity of cervical cancer patients also presented a downward trend, though the magnitude of change was smaller than that of esophageal cancer patients. Details are illustrated in Figure 4 .

Assessment tools for financial toxicity in cancer patients
In the included studies, the follow-up investigation of financial toxicity in cancer patients was mainly conducted through two approaches: subjective and objective. The subjective approaches were mainly divided into three types: one was self-designed questions by researchers regarding patients’ economic status; another was the use of the Comprehensive Score for Financial Toxicity-Patient-Reported Outcome Measure (COST-PROM) questionnaire. Among the 14 included studies, 10 adopted the COST-PROM as the questionnaire for tracking patients’ financial toxicity. This questionnaire was first developed and published by American scholar DeSouza et al. ( 30 ) in 2013, and it is the first assessment tool designed for evaluating financial toxicity in cancer patients. As a self-reported scale for patients, it consists of 11 items, with a Cronbach’s α coefficient of 0.92 and a test–retest reliability of 0.80, indicating good reliability and validity ( 31 ). In the remaining studies, researchers recorded the development of patients’ financial toxicity through subscales within the scales. The objective approach mainly used cost diaries to record the changes in patients’ financial toxicity through objective data.
Influencing factors of financial toxicity in cancer patients
A total of 25 influencing factors were identified in the included studies, involving 4 aspects: sociodemographic factors (4), disease-related factors (4), economic-related factors (11), and psychosocial factors (6). Details are presented in Table 2 .
Table 2
Influencing factors of longitudinal studies of economic toxicity in cancer patients.
| Factor Category | Influencing factors | Number of literatures |
| Demographic factors | Place of residence | 2 |
| Age | 3 | |
| Gender | 2 | |
| Educational level | 1 | |
| Disease-related factors | Treatment method | 3 |
| Measurement time | 2 | |
| Preoperative social function | 1 | |
| Tumor stage | 1 | |
| Economic-related factors | Out-of-pocket expenses | 1 |
| Monthly per capital household income | 4 | |
| Per capital household income | 1 | |
| Unplanned expenses | 1 | |
| Distance to hospital | 1 | |
| Medical insurance | 2 | |
| Household savings | 3 | |
| Subjective socioeconomic status | 1 | |
| Annual household income | 1 | |
| Ability to afford basic treatment | 1 | |
| Loss of wages, salaries or benefits | 1 | |
| Psychosocial factors | Physical symptom burden | 2 |
| Psychological symptom burden | 3 | |
| Self-efficacy | 3 | |
| Family function | 2 | |
| Social support | 2 | |
| Impact on quality of life | 3 |
Sociodemographic factors
Two studies ( 18 , 25 ) indicated that living in regions with a lower level of economic development had a significant impact on the financial toxicity of cancer patients. Three studies ( 24 , 26 , 27 ) showed that age was an important influencing factor of financial toxicity. Two studies ( 24 , 26 ) found that gender was also a key influencing factor, especially for males. One study ( 26 ) suggested that a higher educational level had a negative impact on financial toxicity.
Disease-related factors
Three studies ( 18 , 28 , 29 ) demonstrated that the choice and quantity of treatment modalities had an important influence on the development of financial toxicity. Two studies ( 26 , 29 ) found that the measurement time points selected in longitudinal follow-up studies played a crucial role in identifying the severity of financial toxicity. One study ( 28 ) revealed that patients’ social function before surgery had a significant impact on their financial toxicity after surgery. One study ( 29 ) indicated that tumor stage was an important influencing factor of financial toxicity.
Economic-related factors
One study ( 20 ) indicated that patients’ out-of-pocket medical expenses exerted a significant impact on the development of financial toxicity. Four studies ( 18–20 , 22 ) demonstrated that the per capita monthly household income played an important role in the development of financial toxicity among cancer patients. One study ( 27 ) showed that per capita household income was a crucial influencing factor of financial toxicity. One study ( 20 ) found that unexpected events experienced by patients had an impact on their financial toxicity. One study ( 20 ) suggested that the distance from patients’ residences to hospitals could affect their financial toxicity. Two studies ( 18 , 19 ) revealed that different types of medical insurance had an influence on patients’ financial toxicity. Three studies ( 18 , 22 , 24 ) indicated that household savings were associated with patients’ financial toxicity. One study ( 18 ) showed that subjective social economic status had an impact on financial toxicity. One study ( 22 ) suggested that patients’ capacity to pay for treatment affected their financial toxicity. One study ( 23 ) found that the reduction in salaries, wages, and social welfare due to illness had a negative impact on financial toxicity. One study ( 25 ) discovered that the total annual household income was closely correlated with patients’ financial toxicity.
Psychosocial factors
Two studies ( 16 , 18 ) demonstrated that patients’ physical symptom burden had an important influence on financial toxicity. Three studies ( 18 , 23 , 28 ) indicated that patients’ psychological symptom burden affected their financial toxicity. Three studies ( 20 , 21 , 25 ) found that patients’ self-efficacy had a negative impact on financial toxicity. Two studies ( 17 , 21 ) revealed that family function affected the subsequent development of patients’ financial toxicity. Two studies ( 18 , 19 ) showed that social support played an important role in financial toxicity. Three studies ( 23 , 25 , 28 ) found that patients’ quality of life was also affected by financial toxicity.
Discussion
This scoping review included 14 articles and summarized the current evidence regarding financial toxicity among cancer patients. The aim of this study was to explore the long-term dynamic changes in financial toxicity, analyze relevant assessment tools, summarize influencing factors, and provide a basis for future intervention strategies.
Considerable heterogeneity was observed in the follow-up durations across included studies, with no unified standard, which limited the comparability across studies. Currently, no consistent guidelines define the appropriate follow-up period for financial toxicity. Most studies determined follow-up schedules based on clinical follow-up guidelines for specific cancer types. For example, guidelines recommend follow-up every 3 to 6 months for patients with colorectal cancer, with a colonoscopy required within one year after surgery ( 32 ). For patients with breast cancer, follow-up every 3 months is recommended during the first 3 years postoperatively ( 33 ). The lack of long-term longitudinal studies may be attributed to two main factors: first, financial toxicity is a sensitive issue involving patient privacy, often leading to high dropout rates; second, the study duration is closely related to investigators’ capacity and research objectives. Therefore, future studies should emphasize long-term follow-up to comprehensively reveal the dynamic trajectory of financial toxicity and develop targeted interventions based on the clinical characteristics of different cancers.
Financial toxicity showed a clear increasing trend among patients with colorectal cancer, which may be related to stoma construction following anal invasion. Both temporary and permanent stomas are associated with additional economic burden. For patients with temporary enterostomy, two surgeries (stoma construction and reversal) result in substantially higher medical costs than those for most other cancer patients ( 34 ). Furthermore, long-term stoma care further increases financial toxicity ( 35 ). Notably, in this review, financial toxicity decreased significantly among patients with esophageal cancer and cervical cancer undergoing chemotherapy, while it remained relatively stable among breast cancer patients. This discrepancy may be explained by two factors: first, within 12 months after diagnosis, most patients become familiar with medical insurance policies, which alleviates financial anxiety caused by cost uncertainty ( 25 ). Second, patients with esophageal cancer and cervical cancer do not require stoma care, which may reduce their financial burden. However, comparative studies on financial toxicity across different cancer types remain limited, weakening the generalizability of these findings. Further research with larger datasets is needed to verify whether patients with colorectal cancer experience more severe financial burden than those with other cancers.
Current assessment tools present notable limitations that compromise the reliability of study conclusions. Although the COST questionnaire is widely used, its 7-day recall period is insufficient to capture dynamic changes in financial toxicity, and its non-cancer-specific design may introduce bias. In addition, self-designed questionnaires and subscales lack standardized criteria, and their reliability and validity are often unproven. For objective measurement, cost diaries rely on self-reporting, which limits data accuracy and timeliness. Moreover, no universal standard exists for currency conversion in cross-national studies. Future tools should integrate subjective and objective indicators, be cancer-specific, and account for regional economic development levels to enable standardized assessment. Such tools would improve comparability and representativeness, thereby supporting more efficient allocation of medical resources and better identification of patients at high risk of financial toxicity.
In this study, financial toxicity among cancer patients was influenced by multiple factors, which were closely associated with national economic conditions, social infrastructure, and healthcare security systems. We observed that financial toxicity also exists in developed countries with well-established public healthcare systems. Systematic reviews have indicated that even in countries with universal public health insurance, material hardship persists due to insufficient public financial coverage for rising out-of-pocket costs and income loss related to cancer diagnosis ( 36 ). However, the severity of financial toxicity is generally lower in developed countries than in developing countries ( 37 ). One study suggested that barriers to healthcare may be absolute for older adults individuals in rural areas of sub-Saharan Africa ( 9 ). Persistent inequalities driven by political, social, and institutional factors may affect cancer survivors. Notably, financial toxicity includes not only direct medical costs but also indirect and non-medical costs. In developing countries, in particular, many patients seek medical care in urban tertiary hospitals, and long-distance transportation and temporary accommodation can become substantial burdens. Within the same country, the regional economic level significantly affects financial toxicity, with higher risks in less developed areas. Data show that 50% of rural patients experienced varying degrees of financial toxicity, compared with only 39% of urban patients, due to challenges such as limited reimbursement channels, low income, insufficient staffing, and additional costs caused by geographical barriers ( 38 , 39 ). Importantly, the economic consequences of cancer extend beyond patients to their families. Measuring only out-of-pocket expenses is insufficient to understand the full financial burden of cancer ( 40 ). Focusing solely on out-of-pocket costs may be misleading and fail to identify those most in need. Future research should pay more attention to developing and economically disadvantaged regions and compare whether they experience different types or degrees of financial difficulty compared with developed regions. In addition, further investigations are needed to clarify the real indirect burden borne by family members and friends. These findings have implications for the assessment, intervention, and support for families’ financial concerns, which should ideally be addressed alongside patient care.
Longitudinal studies allow more accurate identification of the temporal sequence of influencing factors across different disease stages, supporting early intervention. Existing evidence indicates that financial toxicity exacerbates physical symptom burden, patient-provider communication, and trust, further complicating symptom management ( 9 , 41 ). The lack of long-term data prevents researchers from capturing the cumulative effects and critical turning points of financial toxicity. For instance, patients may encounter episodic payment difficulties during adjuvant therapy due to cumulative out-of-pocket costs. Without timely identification, this may lead to delayed treatment, dose reduction, or unplanned treatment discontinuation, increasing the risk of disease progression and overall medical costs. Furthermore, financially distressed patients may hide their difficulties due to stigma or abandon cost-effective maintenance therapy because of uncertain prognosis. Therefore, future studies should implement long-term follow-up covering the entire treatment and survivorship period to clarify the dynamic evolution of financial toxicity and establish real-time early warning systems to avoid irreversible health damage caused by delayed intervention.
Limitations
First, as all included studies were conducted in North America, East Asia, and parts of Europe, the generalizability of the findings is limited, with underrepresentation of populations in Africa and South America. Future research should prioritize longitudinal investigations in these regions to address this critical evidence gap. Second, this review only included Chinese and English literature, which may have resulted in incomplete retrieval of relevant studies. Finally, due to the high heterogeneity of the available data, conclusions regarding the influencing factors of financial toxicity among cancer patients may vary, and follow-up with additional relevant studies is warranted for further validation and analysis.
Conclusion
This review included a limited number of studies with relatively short follow-up durations and uneven distribution across cancer types; thus, conclusions regarding differences in financial toxicity among different cancers need to be verified by more high-quality research. At present, the tools used to evaluate the financial toxicity of cancer patients lack specificity for different cancer types, and there is heterogeneity in assessment methods for long-term follow-up evaluations. Although existing studies have mentioned the use of objective data for assessment, due to the differences in economic development levels across different regions, it is difficult to form a unified evaluation formula to accurately reflect the development of patients’ financial toxicity. Therefore, future research should focus on advancing three aspects of work: first, further develop long-term follow-up financial toxicity assessment tools for different cancer types, and construct an evaluation system combining subjective and objective approaches; second, carry out targeted research and intervention focusing on the key time nodes of financial toxicity development in different cancer types, to accurately alleviate patients’ economic burden; third, strengthen comparative research on the heterogeneity of financial toxicity development among different cancer types, to provide a solid basis for the formulation of personalized intervention programs in the future.
Funding Statement
The author(s) declared that financial support was received for this work and/or its publication. This article has received funding from the 2024 Agricultural and Social Development Innovation and Development Project Fund of Tai’an City (ID: 2024NS220).
Footnotes
Edited by: Gianmauro Numico , Azienda Ospedaliera S.Croce e Carle Cuneo, Italy
Reviewed by: Barbara Bachtiary , Paul Scherrer Institut (PSI), Switzerland
Luciana Nogueira , Federal University of Paraná, Brazil
Author contributions
RL: Formal analysis, Writing – original draft, Software, Methodology, Conceptualization, Data curation. JW: Writing – review & editing.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Supplementary material
The supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2026.1798871/full#supplementary-material
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