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Falls among geriatric cancer patients: a systematic review and meta-analysis of prevalence and risk across cancer types

BMC Geriatrics volume 25, Article number: 179 (2025) Cite this article

Abstract

Background

Falls represent a significant health concern among the older adults, particularly geriatric cancer patients, due to their increased susceptibility from both age-related and cancer treatment-related factors. This systematic review and meta-analysis aimed to synthesize global data on the prevalence and risk of falls in this population to inform targeted fall prevention strategies.

Methods

Following PRISMA 2020 guidelines, we conducted a comprehensive search of PubMed, Embase, and Web of Science up to October 2024. Articles were screened using Nested Knowledge software by two independent reviewers. Eligible studies included those involving geriatric cancer patients aged 60 years or older reporting on fall prevalence. Quality assessment was performed using a modified Newcastle–Ottawa Scale, and meta-analysis was conducted using random-effects models with R software.

Results

From 1,365 identified studies, 86 met the inclusion criteria, encompassing 180,974 participants. The pooled prevalence of falls was 24% (95% CI, 20%–28%), with substantial heterogeneity (I2 = 100%). Country- and cancer-type-specific analyses revealed variability in fall prevalence, with breast cancer patients showing the highest prevalence. The comparative risk analysis did not show a statistically significant difference in fall risk between cancer patients and non-cancer controls.

Conclusion

Falls are a prevalent and concerning issue among geriatric cancer patients, with substantial variability influenced by cancer type and study design. Personalized fall prevention strategies tailored to cancer-specific risk factors are essential. Further research is warranted to explore the complex interplay of cancer treatments, frailty, and fall risk in this vulnerable population.

Peer Review reports

Introduction

Falls were a significant and often under-recognized health concern among older adults, contributing to substantial morbidity, mortality, and increased healthcare costs [1]. For older adults, falls were not merely a natural consequence of aging but were frequently indicative of underlying health issues such as frailty, polypharmacy, and neurological or musculoskeletal disorders [2]. Geriatric cancer patients, in particular, presented unique vulnerabilities due to the complex interplay between age-related physiological changes and cancer-specific treatments, which could worsen balance and mobility impairments [3, 4]. Radiotherapy is vital for treating cancer in geriatric patients but can exacerbate frailty through side effects like fatigue and reduced physical function, increasing fall risks. Integrating frailty assessment into radiotherapy could improve treatment outcomes and safety for this vulnerable population [5]. Studies have highlighted the higher fall risk in this group due to factors such as chemotherapy-induced neuropathy, sarcopenia, and impaired physical function [6]. Reported prevalence rates of falls in older cancer patients varied widely, ranging from 15 to 50% depending on cancer type, treatment regimen, and comorbidities, necessitating a comprehensive analysis to clarify these variations [7, 8]. For instance, older adults with multiple myeloma were found to have a significantly higher fall risk due to cancer-related bone disease and treatment-induced weakness [3]. Similarly, pre-treatment falls in older women receiving adjuvant chemotherapy for breast cancer were shown to predict greater hospitalization risks and chemotherapy-related toxicities [4]. Understanding these nuanced impacts on geriatric oncology patients was crucial for developing effective fall-prevention strategies tailored to this vulnerable population.

The confluence of oncological and geriatric syndromes in older cancer patients contributed to a complex clinical concern that keen fall risk through multiple pathways [6, 7]. For example, among older men undergoing androgen deprivation therapy for prostate cancer, the treatment was associated with reduced bone density and increased fracture risk, further elevating their susceptibility to falls [9]. Additionally, the symptom burden and reduced physical function reported in older cancer patients were strongly linked to an increased risk of falls and subsequent physical decline [6]. A population-based study demonstrated that community-dwelling older adults cancer survivors had a higher prevalence of falls compared to their non-cancer counterparts, underscoring the need for tailored interventions targeting this group [7]. Moreover, older Medicare beneficiaries with cancer frequently presented with multiple geriatric syndromes, such as cognitive impairment, incontinence, and mobility disability, which compounded their risk of falling [8]. These findings highlighted the need for a comprehensive approach to fall prevention that accounted for both oncological and geriatric factors.

This study aims to systematically review and analyze the global prevalence and risk of falls among geriatric cancer patients. By synthesizing evidence from diverse settings, it provides a comprehensive understanding of the burden of falls, informing evidence-based guidelines and personalized fall prevention strategies to enhance patient safety, reduce hospitalizations, and improve quality of life in this vulnerable population.

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 standards were followed in this systematic review and meta-analysis [10] (Table S1). The review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) with CRD42024596426.

Eligibility criteria

Studies were included if they met the following criteria: (1) the study population consisted of geriatric cancer patients aged 60 years or older, (2) the study reported data on either the prevalence of falls or factors associated with fall risk in this population, (3) the study design was clinical trial and observational (cross-sectional, cohort, or case–control), and (4) the article was published in a peer-reviewed journal in English. Studies were excluded if they were reviews, commentaries, editorials, case reports, or focused on non-cancer-related falls or falls in non-geriatric populations. Articles that did not present original data, provided insufficient fall-related data, or were not accessible in full text were also excluded (Table S2).

Literature search

A systematic literature search was conducted using PubMed, Embase, and Web of Science from their inception to September 2024. The search strategy employed a combination of MeSH terms and keywords to identify studies investigating the prevalence and risk falls among older cancer patients. Additionally, manual searches of reference lists from selected studies and relevant reviews were conducted to ensure no eligible articles were missed (Table S3).

Screening and data extraction

The screening process was performed in two stages using Nested Knowledge software: (1) title and abstract screening, and (2) full-text review. During the second stage, full texts of potentially eligible studies were retrieved and reviewed by the same two independent reviewers to confirm their inclusion. Any disagreements were resolved through discussion until a consensus was reached.

Data extraction was conducted using Nested Knowledge, a semi-automatic software designed to streamline systematic reviews and meta-analyses. The software facilitates data extraction through its tagging function, allowing reviewers to systematically organize and annotate study characteristics such as author, year, country, participant demographics (age, sex, sample size), cancer type, and fall prevalence. In cases of missing or unclear data, corresponding authors were contacted for clarification. To ensure accuracy and reliability, all extracted data were cross-verified by a third reviewer.

Quality assessment

The quality of the included studies was evaluated using the Modified Newcastle–Ottawa Scale (NOS) modified for geriatric cancer research [11]. The NOS assessed study quality based on three domains: (1) selection of participants (0–4 points), (2) comparability of study groups (0–2 points), and (3) ascertainment of outcomes (0–3 points). Studies scoring 7 to 9 points were considered to have a low risk of bias, scores of 4 to 6 indicated moderate risk, and scores of 0 to 3 were classified as having a high risk of bias. The detailed scoring and assessment are provided in Table S4.

Statistical analysis

All statistical analyses were conducted using R® software (version 4.4.0) with the “meta” and “metafor” packages. Prevalence data were pooled using a random-effects model to account for between-study variability. For pooling prevalence data, the logit-transformed proportions (PLOGIT) were used as the primary summary measure, along with 95% confidence intervals (CI). Heterogeneity across studies was quantified using the I2 statistic, where values of 25%, 50%, and 75% represented low, moderate, and high heterogeneity, respectively [11]. Publication bias was assessed using Doi plots, and quantified using the Luis Furuya-Kanamori (LFK) index. An LFK index value between −1 and + 1 indicated no asymmetry, values between ± 1 and ± 2 indicated minor asymmetry, and values beyond ± 2 suggested major asymmetry [12, 13]. Leave-one-out sensitivity analyses were performed to test the robustness of the pooled results by excluding one study at a time and observing changes in the overall effect size. All statistical tests were two-tailed, with a significance level set at p < 0.05.

Results

Literature search

A total of 1,365 studies were identified through comprehensive database searches. After the excision of 437 duplicates, 928 records remained for title and abstract screening. During this stage, 575 records were excluded for not meeting the relevance criteria. The full texts of 353 articles were then reviewed for eligibility, resulting in the exclusion of 267 articles. In the final selection, 86 studies were included in the quantitative synthesis. The entire process of study selection is outlined in PRISMA flow diagram (Fig. 1).

Fig. 1
figure 1

PRISMA flow diagram

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Summary of study characteristics

A total of 86 studies were included in the systematic review, representing a variety of study designs, cancer types, and geographic regions (Table 1). The majority of these studies were conducted in the United States (n = 52), followed by Canada (n = 10), Belgium (n = 4), and France (n = 4), with additional studies from countries such as Denmark, Germany, and Australia. The study designs were diverse, with cross-sectional studies being the most common (n = 29), followed by prospective (n = 25), retrospective (n = 22), and randomized clinical trials (n = 8). One study utilized a case–control design. The included studies examined various types of cancer, most notably breast cancer (n = 12), colorectal cancer (n = 7), prostate cancer (n = 5), and gastrointestinal cancers (n = 6). Other types, including lymphoma, multiple myeloma, and gynaecologic cancers, were also investigated. Study sample sizes varied widely, ranging from 51 to 60,265 participants. The majority of studies focused on older adults, especially those at heightened risk of falls due to cancer treatments and related comorbidities.

Table 1 Characteristics of studies
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Meta-analysis

Prevalence of falls among geriatric cancer patients

Meta-analysis of 86 studies including 180,974 participants, the pooled prevalence of falls among geriatric cancer patients was estimated at 24% (95% CI, 20%–28%) (Fig. 2). The prediction interval ranged widely, from 4 to 68%, reflecting considerable variability between studies (Table 2). A high degree of heterogeneity was noted (I2 = 100%, P < 0.001). The leave-one-out sensitivity analysis (Figure S1) demonstrated that excluding individual studies had minimal impact on the overall pooled prevalence of falls among geriatric cancer patients, which consistently stayed at around 24% (95% CI: 0.2–0.28). The slight variations observed across duplications of the meta-analysis results. Despite significant heterogeneity (I2 = 100%), the stability of the pooled estimates suggests that no single study excessively influenced the final outcomes, thereby confirming the reliability of the findings. Following the exclusion of outliers, a reanalysis was performed. This refined analysis resulted in a slightly lower pooled prevalence of 23% (95% CI, 21%–24%). The prediction interval narrowed to 17% to 30%, indicating reduced variability between the studies (Fig. 3). Furthermore, the heterogeneity decreased markedly to I2 = 75% (P < 0.001), suggesting a more consistent pattern among the remaining studies after outliers were removed.

Fig. 2
figure 2

Forest plot illustrating the pooled prevalence of falls among geriatric cancer patients

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Table 2 Subgroup analysis based on study design, country-specific, cancer types
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Fig. 3
figure 3

Forest plot illustrating the pooled prevalence of falls among geriatric cancer patients after the exclusion of outliers

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Sub-group analysis

The pooled prevalence of falls among older adults cancer patients varied across cancer types, study designs, and countries, as shown in the Table 2. Breast cancer had the highest prevalence at 32% (I2 = 94%), while colorectal and gastrointestinal cancers had prevalence of 15% (I2 = 100%) and 28% (I2 = 98%), respectively. Across all cancer types, the overall pooled prevalence was 24% (95% CI: 0.17–0.33), with substantial heterogeneity (I2 = 99%). Prevalence also differed by study design, with cross-sectional studies reporting the highest prevalence at 30% (I2 = 99%), followed by prospective studies at 24% (I2 = 98%) and retrospective studies at 14% (I2 = 100%). Randomized clinical trials showed a lower prevalence of 18% (I2 = 88%). The pooled prevalence across all study designs was 24% (95% CI: 0.20–0.28, I2 = 100%). Country-specific analysis revealed that the United States had a pooled prevalence of 22% (I2 = 100%) across 33 studies, Canada 23% (I2 = 95%), and France 58% (I2 = 98%). Denmark reported a lower prevalence of 12%, while Spain had a higher rate at 55% (I2 = 98%). In Korea and Japan, the prevalence were 50% and 41%, respectively. Overall, the pooled prevalence across all countries was 23% (95% CI: 0.17–0.30), with significant regional variability.

Risk of falls among geriatric cancer patients

The forest plot (Fig. 4) compares the fall risk between geriatric cancer patients and non-cancer controls, incorporating data from six studies. The pooled risk ratio (RR) was 1.099 (95% CI: 0.558–2.164), indicating no statistically significant difference in fall risk between the groups, although substantial heterogeneity was present (I2 = 96%). Sensitivity analysis showed that excluding individual studies had little impact on the overall pooled risk. For instance, when Wildes et al. [88] was excluded, the pooled risk ratio decreased to 0.9 (95% CI: 0.52–1.57), with I2 remaining at 96%. Conversely, omitting Spoelstra et al. [7] increased the risk ratio to 1.3 (95% CI: 0.6–2.5), reducing heterogeneity to I2 = 83% (Figure S2).

Fig. 4
figure 4

Forest plot interprets the risk of falls among geriatric cancer patients compared to non-cancer controls

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Meta-regression

The bubble plot shows the meta-regression that analysed the impact of sample size on the rate of falls among older adult cancer patients. The meta-regression analysis indicated that changes in the pooled prevalence were not significantly affected by variations in sample size, with a p-value of 0.5577 (Fig. 5).

Fig. 5
figure 5

Bubble plot demonstrating meta-regression based on sample size and its effect on the proportion of falls in geriatric cancer patients

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Publication bias

The Doi plot (Figure S3) shows substantial asymmetry, with an LFK index of −4.1, indicating the presence of publication bias. The asymmetry suggests potential issues with the included studies, affecting the consistency of the pooled estimates. This bias may influence the overall reliability of the results.

Discussion

This meta-analysis identified a pooled fall prevalence of 24% (95% CI: 20%–28%) across 86 studies, highlighting the significant risk faced by geriatric cancer patients. The high heterogeneity observed (I2 = 100%) suggests considerable variability across studies, likely attributable to differences in cancer types, treatments, and study designs. Notably, breast cancer patients exhibited the highest fall prevalence at 32%, while colorectal and gastrointestinal cancer patients had lower rates of 15% and 28%, respectively. These findings underscore the need for cancer-specific considerations when evaluating fall risk in older adults. The analysis also revealed that cross-sectional studies reported a higher fall prevalence (30%) than prospective (24%) and retrospective (14%) studies, emphasizing the influence of study design on reported outcomes. Despite this heterogeneity, sensitivity analyses confirmed the robustness of the pooled estimates, indicating that the overall conclusions remain valid despite individual study differences.

A comparison of fall risk between cancer patients and non-cancer controls revealed no statistically significant difference overall (RR: 1.099, 95% CI: 0.558–2.164). However, individual studies presented mixed findings, such as Spoelstra et al. [7], which reported a reduced fall risk (RR: 0.476) among cancer patients, and Wildes et al. [88], which documented an elevated fall risk (RR: 3.249). These discrepancies likely stem from variations in patient characteristics, study methodologies, and cancer treatments. Nonetheless, the overall analysis suggests that fall risk is not uniformly higher across all cancer subgroups, emphasizing the need for context-specific assessments in clinical practice.

Several factors likely contribute to the increased fall risk observed in geriatric cancer patients. Cancer treatments, including chemotherapy, radiotherapy, and hormone therapy, are associated with well-documented side effects such as fatigue, neuropathy, and muscle weakness, all of which increase fall risk [36]. In breast cancer patients, aromatase inhibitors exacerbate joint pain and mobility limitations, leading to increased falls [23]. Similarly, prostate cancer patients on androgen deprivation therapy (ADT) experience muscle wasting and bone density loss, further elevating their fall risk, as noted in Wildes et al. (2018) [3, 88]. In addition to treatment effects, age-related frailty compounds fall risk, as older adults with cancer often present with comorbid conditions such as osteoporosis, cardiovascular disease, and diabetes, all of which heighten fall susceptibility. The interaction between cancer, its treatment, and underlying frailty underscores the complexity of fall risk management in this population.

Clinically, these findings highlight the critical need for routine fall risk assessments in geriatric oncology care. Given the multifactorial nature of falls in this population, clinicians should adopt multidisciplinary approaches that incorporate physical therapy, balance training, and medication reviews to mitigate fall risk [95]. These interventions are particularly important for high-risk subgroups, such as breast cancer patients on aromatase inhibitors and prostate cancer patients receiving ADT [96]. Moreover, integrating personalized fall prevention strategies into cancer treatment plans could significantly reduce fall-related injuries and hospitalizations, improving overall patient outcomes [97]. From a public health perspective, community-based programs that promote physical activity and home safety modifications could play a key role in reducing fall incidence among older cancer patients. Such initiatives, when coupled with clinical interventions, could lessen the burden of falls and enhance the quality of life for this vulnerable population [98].

Despite the robustness of the findings, the high heterogeneity observed in this analysis indicates that further research is necessary to better understand the factors contributing to fall risk variability. Prospective cohort studies focused on specific cancer types and treatments would be instrumental in elucidating the long-term effects of these therapies on fall risk. For example, studies examining the impact of chemotherapy-induced neuropathy or hormone therapy-induced frailty could provide valuable insights into targeted interventions aimed at reducing fall risk [99]. Moreover, future research should explore the role of sarcopenia and frailty as mediators between cancer treatment and falls. Studies such as Kenis et al. [49] have already begun investigating the potential of geriatric screening to identify patients at high risk of falls, and further work in this area could refine risk stratification in clinical practice [49].

Addressing publication bias, as indicated by the asymmetry observed in the Doi plot, is also critical for enhancing the accuracy of future meta-analyses. Ensuring that smaller or negative studies are adequately represented will help create a more comprehensive understanding of fall risk in geriatric cancer patients. Future research should prioritize efforts to address these gaps, ultimately leading to more effective fall prevention strategies and better patient outcomes in this high-risk population.

Conclusion

This meta-analysis provides a comprehensive assessment of the prevalence of falls among geriatric cancer patients, with an overall estimate of 24%. Significant variability was observed across subgroups, including cancer types, study designs, and geographic regions, indicating the need for tailored interventions. Despite the high heterogeneity, sensitivity analyses confirmed the robustness of the pooled estimates. No statistically significant difference in fall risk was observed when comparing geriatric cancer patients to non-cancer controls. These findings highlight the importance of implementing personalized fall prevention strategies and underscore the need for further research to address the factors contributing to fall risk in this vulnerable population.

Data availability

All data generated or analyzed during this study are included in this published article (and its Supplementary information files).

References

  1. Vaishya R, Vaish A. Falls in older adults are serious. Indian J Orthop. 2020;54(1):69–74.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Ambrose AF, Paul G, Hausdorff JM. Risk factors for falls among older adults: a review of the literature. Maturitas. 2013;75(1):51–61.

    Article  PubMed  Google Scholar 

  3. Wildes TM, Fiala MA. Falls in older adults with multiple myeloma. Eur J Haematol. 2018;100(3):273–8.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Ji J, Bae M, Sun CL, Wildes TM, Freedman RA, Magnuson A, et al. Falls prechemotherapy and toxicity-related hospitalization during adjuvant chemotherapy for breast cancer in older women: Results from the prospective multicenter HOPE trial. Cancer. 2024;130(6):936–46.

    Article  CAS  PubMed  Google Scholar 

  5. Fernández-Camacho E, Ferrer-Ramos C, Morilllo-Macías V, Rodríguez-Cordón M, Sánchez-Iglesias Á, Beato-Tortajada I, et al. The impact of frailty screening on radiation treatment modification. Cancers. 2022;14(4):1072.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Pandya C, Magnuson A, Flannery M, Zittel J, Duberstein P, Loh KP, et al. Association between symptom burden and physical function in older patients with cancer. J Am Geriatr Soc. 2019;67(5):998–1004.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Spoelstra S, Given B, von Eye A, Given C. Fall risk in community-dwelling elderly cancer survivors: a predictive model for gerontological nurses. J Gerontol Nurs. 2010;36(2):52–60.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Mohile SG, Fan L, Reeve E, Jean-Pierre P, Mustian K, Peppone L, et al. Association of cancer with geriatric syndromes in older Medicare beneficiaries. J Clin Oncol. 2011;29(11):1458–64.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hussain S, Breunis H, Timilshina N, Alibhai SM. Falls in men on androgen deprivation therapy for prostate cancer. Journal of Geriatric Oncology. 2010;1(1):32–9.

    Article  Google Scholar 

  10. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372.

  11. Bushi G, Shabil M, Padhi BK, Ahmed M, Pandey P, Satapathy P, et al. Prevalence of acute kidney injury among dengue cases: a systematic review and meta-analysis. Trans R Soc Trop Med Hyg. 2023;118(1):1–11.

    Article  Google Scholar 

  12. Langan D, Higgins JP, Jackson D, Bowden J, Veroniki AA, Kontopantelis E, et al. A comparison of heterogeneity variance estimators in simulated random-effects meta-analyses. Research synthesis methods. 2019;10(1):83–98.

    Article  PubMed  Google Scholar 

  13. Gandhi AP, Shamim MA, Padhi BK. Steps in undertaking meta-analysis and addressing heterogeneity in meta-analysis. The Evidence. 2023;1(1):44–59.

    Google Scholar 

  14. Abraham NS, Kunik M, Richardson PA, Castillo DL, Naik AD. Life expectancy of colorectal cancer patients with geriatric syndromes. Gastroenterology. 2011;140(5):S–206.

  15. Ala’S A, Phillips SP, Curcio C-L, Guerra RO, Auais M. Fear of falling in community-dwelling older adults diagnosed with cancer: a report from the International Mobility in Aging Study (IMIAS). J Geriatr Oncol. 2020;11(4):603–9.

  16. Anderson C, Olshan A, Bae-Jump V, Park J, Brewster W, Kent E, Nichols HB. Falls, walking or balance problems, and limitations in activities of daily living (ADLs) among older endometrial cancer survivors. Support Care Cancer. 2022;30(7):6339–51.

    Article  PubMed  Google Scholar 

  17. Arora S, Fowler ME, Harmon C, Al-Obaidi M, Outlaw D, Hollis R, et al. Differences in pretreatment frailty across gastrointestinal cancers in older adults: Results from the cancer and aging resilience evaluation registry. JCO Oncology Practice. 2022;18(11):e1796–806.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Arrieta H, Astrugue C, Regueme S, Durrieu J, Maillard A, Rieger A, et al. Effects of a physical activity programme to prevent physical performance decline in onco-geriatric patients: a randomized multicentre trial. J Cachexia Sarcopenia Muscle. 2019;10(2):287–97.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Bartlett DB, Broadwater G, White HK, Shelby R, Zullig LL, Robertson J, et al. Factors associated with falls in older women with breast cancer: the use of a brief geriatric screening tool in clinic. Breast Cancer Res Treat. 2020;184:445–57.

    Article  PubMed  Google Scholar 

  20. Basal C, Vertosick E, Gillis TA, Li Q, Bao T, Vickers A, Mao JJ. Joint pain and falls among women with breast cancer on aromatase inhibitors. Support Care Cancer. 2019;27:2195–202.

    Article  PubMed  Google Scholar 

  21. Bjerre ED, Petersen TH, Jørgensen AB, Johansen C, Krustrup P, Langdahl B, et al. Community-based football in men with prostate cancer: 1-year follow-up on a pragmatic, multicentre randomised controlled trial. PLoS Med. 2019;16(10): e1002936.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Blackwood J, Rybicki K. Assessment of gait speed and timed up and go measures as predictors of falls in older breast cancer survivors. Integr Cancer Ther. 2021;20:15347354211006462.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Bluethmann SM, Flores E, Campbell G, Klepin HD. Mobility device use and mobility disability in US Medicare beneficiaries with and without cancer history. J Am Geriatr Soc. 2020;68(12):2872–80.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Bylow K, Dale W, Mustian K, Stadler WM, Rodin M, Hall W, et al. Falls and physical performance deficits in older patients with prostate cancer undergoing androgen deprivation therapy. Urology. 2008;72(2):422–7.

    Article  PubMed  Google Scholar 

  25. Chen T-Y, Janke MC. Predictors of falls among community-dwelling older adults with cancer: results from the health and retirement study. Support Care Cancer. 2014;22:479–85.

    Article  PubMed  Google Scholar 

  26. Childs DS, Yoon HH, Eiring RA, Jin Z, Jochum JA, Pitot HC, Jatoi A. Falls: descriptive rates and circumstances in age-unspecified patients with locally advanced esophageal cancer. Support Care Cancer. 2021;29:733–9.

    Article  PubMed  Google Scholar 

  27. Cobbing S, Timilshina N, Tomlinson G, Yang H, Kim VS, Emmenegger U, Alibhai SM. Falls in older adults during treatment for metastatic castration-resistant prostate cancer. J Geriatr Oncol. 2024;16:102047.

    Article  PubMed  Google Scholar 

  28. Eriksen GF, Šaltytė Benth J, Grønberg BH, Rostoft S, Kirkhus L, Kirkevold Ø, et al. Geriatric impairments are prevalent and predictive of survival in older patients with cancer receiving radiotherapy: a prospective observational study. Acta Oncol. 2022;61(4):393–402.

    Article  CAS  PubMed  Google Scholar 

  29. Fagard K, Casaer J, Wolthuis A, Flamaing J, Milisen K, Lobelle J-P, et al. Value of geriatric screening and assessment in predicting postoperative complications in patients older than 70 years undergoing surgery for colorectal cancer. Journal of geriatric oncology. 2017;8(5):320–7.

    Article  PubMed  Google Scholar 

  30. Fahimnia S, Mirhedayati Roudsari H, Doucette J, Shahrokni A. Falls in older patients with cancer undergoing surgery: prevalence and association with geriatric syndromes and levels of disability assessed in preoperative evaluation. Current gerontology and geriatrics research. 2018;2018(1):5713285.

    PubMed  PubMed Central  Google Scholar 

  31. Farcet A, De Decker L, Pauly V, Rousseau F, Bergman H, Molines C, Retornaz F. Frailty markers and treatment decisions in patients seen in oncogeriatric clinics: results from the ASRO pilot study. PLoS ONE. 2016;11(2): e0149732.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Feliu J, Espinosa E, Basterretxea L, Paredero I, Llabrés E, Jiménez-Munárriz B, et al. Prediction of unplanned hospitalizations in older patients treated with chemotherapy. Cancers. 2021;13(6):1437.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Gewandter JS, Dale W, Magnuson A, Pandya C, Heckler CE, Lemelman T, et al. Associations between a patient-reported outcome (PRO) measure of sarcopenia and falls, functional status, and physical performance in older patients with cancer. Journal of geriatric oncology. 2015;6(6):433–41.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Godby RC, Dai C, Al-Obaidi M, Giri S, Young-Smith C, Kenzik K, et al. Depression among older adults with gastrointestinal malignancies. Journal of geriatric oncology. 2021;12(4):599–604.

    Article  CAS  PubMed  Google Scholar 

  35. Jahrestagung der Deutschen, Österreichischen und Schweizerischen Gesellschaften für Hämatologie und Medizinische Onkologie, Hamburg, 10.-14. Oktober 2014: Abstracts. Oncol Res Treat. 2014;37(Suppl. 5):1–332.

  36. Guerard EJ, Deal AM, Williams GR, Jolly TA, Nyrop KA, Muss HB. Falls in older adults with cancer: Evaluation by oncology providers. Journal of oncology practice. 2015;11(6):470–4.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Gupta E, Tennison JM, Shin KY, Fu JB, Rozman de Moraes A, Naqvi SMA, et al. Frequency, characteristics, and risk factors for falls at an inpatient cancer rehabilitation unit. JCO Oncol Pract. 2023;19(9):741–9.

  38. Habib MH, Alibhai SM, Puts M. How representative are participants in geriatric oncology clinical trials? The case of the 5C RCT in geriatric oncology: a cross-sectional comparison to a geriatric oncology clinic. Journal of Geriatric Oncology. 2024;15(2): 101703.

    Article  CAS  PubMed  Google Scholar 

  39. Hamid M, Hannan M, Myo Oo N, Lynch P, Walsh DJ, Matthews T, et al. Chemotherapy toxicity in older adults optimized by geriatric assessment and intervention: a non-comparative analysis. Curr Oncol. 2022;29(9):6167–76.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Hines RB, Schoborg C, Sumner T, Thiesfeldt DL, Zhang S. The associations of oxaliplatin-induced peripheral neuropathy, sociodemographic characteristics, and clinical characteristics with time to fall in older adults with colorectal cancer. Am J Epidemiol. 2024;193(9):1271–80. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/aje/kwae067.

    Article  PubMed  Google Scholar 

  41. Huang MH, Blackwood J, Godoshian M, Pfalzer L. Prevalence of self-reported falls, balance or walking problems in older cancer survivors from Surveillance, Epidemiology and End Results—Medicare Health Outcomes Survey. J Geriatr Oncol. 2017;8(4):255–61.

    Article  PubMed  Google Scholar 

  42. Hurria A, Mohile S, Lichtman S, Owusu C, Klepin H, Gross C, et al. Geriatric assessment of older adults with cancer: baseline data from a 500 patient multicenter study. J Clin Oncol. 2009;27(15_suppl):9546.

  43. Sucuoglu Isleyen Z, Besiroglu M, Yasin AI, Simsek M, Topcu A, Smith L, et al. The risk of malnutrition and its clinical implications in older patients with cancer. Aging Clin Exp Res. 2023;35(11):2675–83.

    Article  PubMed  Google Scholar 

  44. Jensen-Battaglia M, Lei L, Xu H, Loh KP, Wells M, Tylock R, et al. Communication about fall risk in community oncology practice: the role of geriatric assessment. JCO Oncol Pract. 2022;18(10):e1630–40.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Jespersen E, Winther SB, Minet LR, Möller S, Pfeiffer P. Frailty screening for predicting rapid functional decline, rapid progressive disease, and shorter overall survival in older patients with gastrointestinal cancer receiving palliative chemotherapy-a prospective, clinical study. J Geriatr Oncol. 2021;12(4):578–84.

    Article  CAS  PubMed  Google Scholar 

  46. Jolly TA, Mariano CJ, Deal AM, Williams GR, Alston SM, Bryant AL, et al. The association of Geriatric Assessment (GA) identified deficits and 30-day re-admission in hospitalized older cancer patients. American Society of Clinical Oncology; 2015.

  47. Jun M, Lee K, Park S. Risk factors of falls among inpatients with cancer. Int Nurs Rev. 2018;65(2):254–61.

    Article  CAS  PubMed  Google Scholar 

  48. Kalariya NM, Hildebrandt MA, Hansen DK, Sidana S, Khouri J, Ferreri CJ, et al. Clinical outcomes after idecabtagene vicleucel in older patients with multiple myeloma: a multicenter real-world experience. Blood Adv. 2024;8(17):4679–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kenis C, Decoster L, Flamaing J, Debruyne PR, De Groof I, Focan C, et al. Incidence of falls and fall-related injuries and their predictive factors in frail older persons with cancer: a multicenter study. BMC Geriatr. 2022;22(1):877.

  50. Kikuchi R, Broadwater G, Shelby R, Robertson J, Zullig LL, Maloney B, et al. Detecting geriatric needs in older patients with breast cancer through use of a brief geriatric screening tool. Journal of geriatric oncology. 2019;10(6):968–72.

    Article  PubMed  Google Scholar 

  51. Kim J, Ferrell B, Raz D, Erhunmwunsee L, Teteh D, Dale W, et al. EP10. 01–012 geriatric assessment in patients undergoing lung cancer surgery and their family caregivers. J Thorac Oncol. 2022;17(9):S505.

    Article  Google Scholar 

  52. Komatsu H, Yagasaki K, Komatsu Y, Yamauchi H, Yamauchi T, Shimokawa T, Doorenbos AZ. Falls and functional impairments in breast cancer patients with chemotherapy-induced peripheral neuropathy. Asia Pac J Oncol Nurs. 2019;6(3):253–60.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Kong QH, Wang Y, Song CG, Liu YS, Qin HY, Feng YD, Li YJ. Prospective analysis of the risk factors for falls in lymphoma patients. Eur J Oncol Nurs. 2014;18(5):540–4.

    Article  PubMed  Google Scholar 

  54. Korc-Grodzicki B, Sun SW, Zhou Q, Iasonos A, Lu B, Root JC, et al. Geriatric assessment as a predictor of delirium and other outcomes in elderly patients with cancer. Ann Surg. 2015;261(6):1085–90.

    Article  PubMed  Google Scholar 

  55. Liu X, Dong C, Zhao R, Gu Z, Sun C. Fall risk in older adults hospitalized with tumours: Contributing factors and prediction model. Nurs Open. 2023;10(10):7084–91.

    Article  PubMed  PubMed Central  Google Scholar 

  56. LoConte NK, et al. Severe falls among older adults with resected stage II/III colon cancer receiving chemotherapy. JCO. 2013;31:e14550. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/jco.2013.31.15_suppl.e14550.

  57. Loh KP, Pandya C, Zittel J, Kadambi S, Flannery M, Reizine N, et al. Associations of sleep disturbance with physical function and cognition in older adults with cancer. Support Care Cancer. 2017;25:3161–9.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Lund CM, Nielsen DL, Schultz M, Dolin TG. Physical decline, falls, and hospitalization among vulnerable older patients in the trajectory of colorectal cancer treatment. J Geriatr Oncol. 2024;15(7): 101820.

    Article  CAS  PubMed  Google Scholar 

  59. Mariano C, Williams G, Deal A, Alston S, Bryant AL, Jolly T, Muss HB. Geriatric assessment of older adults with cancer during unplanned hospitalizations: an opportunity in disguise. Oncologist. 2015;20(7):767–72. https://doiorg.publicaciones.saludcastillayleon.es/10.1634/theoncologist.2015-0023.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Martí-Dillet MM, Fernández-Rodriguez C, Ginesta-Guanter A, Suñer-Soler R. Accumulated incidence of falls in people hospitalised with cancer and related factors. Nurs Open. 2023;10(8):5571–7.

    Article  PubMed  PubMed Central  Google Scholar 

  61. May P, Roe L, McGarrigle CA, Kenny RA, Normand C. End-of-life experience for older adults in Ireland: results from the Irish longitudinal study on ageing (TILDA). BMC Health Serv Res. 2020;20:1–10.

    Article  Google Scholar 

  62. Mir N, MacLennan P, Al-Obaidi M, Murdaugh D, Kenzik KM, McDonald A, et al. Patient-reported cognitive complaints in older adults with gastrointestinal malignancies at diagnosis–Results from the Cancer & Aging Resilience Evaluation (CARE) study. J Geriatr Oncol. 2020;11(6):982–8.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Mohamed MR, Juba K, Awad H, Flannery M, Culakova E, Wells M, et al. Effect of polypharmacy and potentially inappropriate medications on physical functional decline among older adults with advanced cancer receiving systemic treatment. Support Care Cancer. 2024;32(10):1–9.

    Article  Google Scholar 

  64. Nassani NA, et al. The ability of physical performance test and Karnofsky performance status to identify elderly cancer patients requiring a comprehensive geriatric assessment: a comparative study. JCO. 2013;31:e20534. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/jco.2013.31.15_suppl.e20534.

  65. Overcash J. Prediction of falls in older adults with cancer: a preliminary study. Oncol Nurs Forum. 2007;34(2):341–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1188/07.ONF.341-346.

    Article  PubMed  Google Scholar 

  66. Paillaud E, Liuu E, Laurent M, Le Thuaut A, Vincent H, Raynaud-Simon A, et al. Geriatric syndromes increased the nutritional risk in elderly cancer patients independently from tumoursite and metastatic status. The ELCAPA-05 cohort study. Clin Nutr. 2014;33(2):330-5.

  67. Pan K, Ray RM, Cauley JA, Shadyab AH, Hurria A, Chlebowski RT. Trajectory of recurrent falls in post-menopausal breast cancer survivors and in matched cancer-free controls. Breast Cancer Res Treat. 2020;180:767–75.

    Article  PubMed  Google Scholar 

  68. Pandya C, Magnuson A, Dale W, Lowenstein L, Fung C, Mohile SG. Association of falls with health-related quality of life (HRQOL) in older cancer survivors: a population based study. J Geriatr Oncol. 2016;7(3):201–10.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Abstracts P. Asia Pac J Clin Oncol. 2015;11(S3):50–69.

    Article  Google Scholar 

  70. Pautex S, Herrmann FR, Zulian GB. Factors associated with falls in patients with cancer hospitalized for palliative care. J Palliat Med. 2008;11(6):878–84.

    Article  PubMed  Google Scholar 

  71. Peeters L, De Cock J, Kenis C, Wildiers H, Decoster L, Laethem L, et al. Risk factors for falls in older persons with cancer: a multicenter study. J Geriatr Oncol. 2019;10(6):S23.

    Article  Google Scholar 

  72. Pergolotti M, et al. The underutilization of occupational and physical therapy for older adults with cancer. JCO. 2014;32:9548. https://doiorg.publicaciones.saludcastillayleon.es/10.1200/jco.2014.32.15_suppl.9548.

    Article  Google Scholar 

  73. Piper KS, Myhre KK, Jensen HE, Madsen K, Mikkelsen MK, Lund C. Dizziness and impaired walking balance in aging patients during chemotherapy. J Geriatr Oncol. 2024;15(8): 102059.

    Article  CAS  PubMed  Google Scholar 

  74. Pollock Y, Smith MR, Saad F, Chowdhury S, Oudard S, Hadaschik B, et al. Clinical characteristics associated with falls in patients with non-metastatic castration-resistant prostate cancer treated with apalutamide. Prostate Cancer Prostatic Dis. 2023;26(1):156–61.

    Article  CAS  PubMed  Google Scholar 

  75. Rattanakrong N, Siriphorn A, Boonyong S. Incidence and risk factors associated with falls among women with breast cancer during taxane-based chemotherapy. Support Care Cancer. 2022;30(9):7499–508.

    Article  PubMed  Google Scholar 

  76. Reyes KR, Huang C-Y, Lo M, Arora S, Chung A, Wong SW, et al. Safety and efficacy of BCMA CAR-T cell therapy in older patients with multiple myeloma. Transplant Cell Ther. 2023;29(6):350–5.

    Article  CAS  PubMed  Google Scholar 

  77. Rosko AE, Huang Y, Benson DM, Efebera YA, Hofmeister C, Jaglowski S, et al. Use of a comprehensive frailty assessment to predict morbidity in patients with multiple myeloma undergoing transplant. J Geriatr Oncol. 2019;10(3):479–85.

    Article  PubMed  Google Scholar 

  78. Saarelainen LK, Turner JP, Shakib S, Singhal N, Hogan-Doran J, Prowse R, et al. Potentially inappropriate medication use in older people with cancer: prevalence and correlates. J Geriatr Oncol. 2014;5(4):439–46.

    Article  PubMed  Google Scholar 

  79. Sattar S, Alibhai SM, Spoelstra SL, Puts MT. The assessment, management, and reporting of falls, and the impact of falls on cancer treatment in community-dwelling older patients receiving cancer treatment: Results from a mixed-methods study. Journal of geriatric oncology. 2019;10(1):98–104.

    Article  PubMed  Google Scholar 

  80. Sulicka J, Pac A, Puzianowska-Kuźnicka M, Zdrojewski T, Chudek J, Tobiasz-Adamczyk B, et al. Health status of older cancer survivors—results of the PolSenior study. J Cancer Surviv. 2018;12:326–33.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Tennison JM, Ng AH, Rianon NJ, Liu DD, Bruera E. Patient-reported continuity of care and functional safety concerns after inpatient cancer rehabilitation. Oncologist. 2021;26(10):887–96.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Tomczak U, Sattar S, Schoenbeck KL, Cordner T, Wildes TM. Circumstances around falls in older adults with Cancer. J Geriatr Oncol. 2021;12(1):91–5.

    Article  CAS  PubMed  Google Scholar 

  83. Turner JP, Jamsen KM, Shakib S, Singhal N, Prowse R, Bell JS. Polypharmacy cut-points in older people with cancer: how many medications are too many? Support Care Cancer. 2016;24:1831–40.

    Article  PubMed  Google Scholar 

  84. Vande Walle N, Kenis C, Heeren P, Van Puyvelde K, Decoster L, Beyer I, et al. Fall predictors in older cancer patients: a multicenter prospective study. BMC Geriatr. 2014;14:1–10.

    Article  Google Scholar 

  85. Vetrano DL, Foebel AD, Marengoni A, Brandi V, Collamati A, Heckman GA, et al. Chronic diseases and geriatric syndromes: The different weight of comorbidity. Eur J Intern Med. 2016;27:62–7.

    Article  PubMed  Google Scholar 

  86. Villani ER, Fusco D, Franza L, Onder G, Bernabei R, Colloca GF. Characteristics of patients with cancer in European long-term care facilities. Aging Clin Exp Res. 2022;34:1–8.

    Article  Google Scholar 

  87. Whittle A, Kalsi T, Babic-Illman G, Wang Y, Fields P, Ross P, et al. A comprehensive geriatric assessment screening questionnaire (CGA-GOLD) for older people undergoing treatment for cancer. Eur J Cancer Care. 2017;26(5): e12509.

    Article  Google Scholar 

  88. Wildes TM, Maggiore RJ, Tew WP, Smith D, Sun C-L, Cohen H, et al. Factors associated with falls in older adults with cancer: a validated model from the Cancer and Aging Research Group. Support Care Cancer. 2018;26:3563–70.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Williams GR, Deal AM, Nyrop KA, Pergolotti M, Guerard EJ, Jolly TA, Muss HB. Geriatric assessment as an aide to understanding falls in older adults with cancer. Support Care Cancer. 2015;23:2273–80.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Williams GR, Al-Obaidi M, Dai C, Mir N, Challa SA, Daniel M, et al. Association of malnutrition with geriatric assessment impairments and health-related quality of life among older adults with gastrointestinal malignancies. Cancer. 2020;126(23):5147–55.

    Article  PubMed  Google Scholar 

  91. Winters-Stone KM, Torgrimson B, Horak F, Eisner A, Nail L, Leo MC, et al. Identifying factors associated with falls in postmenopausal breast cancer survivors: a multi-disciplinary approach. Arch Phys Med Rehabil. 2011;92(4):646–52.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Wu F-J, Sheu S-Y, Lin H-C, Chung S-D. Increased fall risk in patients receiving androgen deprivation therapy for prostate cancer. Urology. 2016;95:145–50.

    Article  PubMed  Google Scholar 

  93. Zak M, Biskup M, Macek P, Krol H, Krupnik S, Opuchlik A. Identifying predictive motor factors for falls in post-menopausal breast cancer survivors. PLoS ONE. 2017;12(3): e0173970.

    Article  PubMed  PubMed Central  Google Scholar 

  94. Zhang X, Sun M, Liu S, Leung CH, Pang L, Popat UR, et al. Risk factors for falls in older patients with cancer. BMJ Support Palliat Care. 2018;8(1):34–7.

    Article  PubMed  Google Scholar 

  95. Hopewell S, Adedire O, Copsey BJ, Boniface GJ, Sherrington C, Clemson L, et al. Multifactorial and multiple component interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2018;7(7):Cd012221.

    PubMed  Google Scholar 

  96. Chaput G, Sumar N. Endocrine therapies for breast and prostate cancers: Essentials for primary care. Can Fam Physician. 2022;68(4):271–6.

    Article  PubMed  PubMed Central  Google Scholar 

  97. Turner K, Staggs VS, Potter C, Cramer E, Shorr RI, Mion LC. Fall prevention practices and implementation strategies: examining consistency across hospital units. J Patient Saf. 2022;18(1):e236–42.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Guo X, Wang Y, Wang L, Yang X, Yang W, Lu Z, He M. Effect of a fall prevention strategy for the older patients: a quasi-experimental study. Nurs Open. 2023;10(2):1116–24.

    Article  PubMed  Google Scholar 

  99. Tofthagen C, Overcash J, Kip K. Falls in persons with chemotherapy-induced peripheral neuropathy. Support Care Cancer. 2012;20(3):583–9.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors acknowledge Nested-Knowledge, MN, USA for providing access to the software.

Funding

This study received no funding.

Author information

Author notes

  1. Doddolla Lingamaiah and Shilpa Gaidhane contributed equally as first authors.

Authors and Affiliations

  1. Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, India

    Doddolla Lingamaiah

  2. School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, India

    Ganesh Bushi

  3. Research and Enterprise, University of Cyberjaya, Persiaran Bestari, Cyber 11, Cyberjaya, Selangor, 63000, Malaysia

    Ganesh Bushi & Ashok Kumar Balaraman

  4. One Health Centre, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education, Wardha, India

    Shilpa Gaidhane

  5. Department of Chemistry and Biochemistry, School of Sciences, JAIN (Deemed to Be University), Bangalore, Karnataka, India

    G. Padmapriya

  6. Department of Allied Healthcare and Sciences, Vivekananda Global University, Jaipur, Rajasthan, 303012, India

    Irwanjot Kaur

  7. Department of Medicine, NIMS University, Jaipur, India

    Madan Lal

  8. Chandigarh Pharmacy College, Chandigarh Group of College, Jhanjeri, Punjab, Mohali, 140307, India

    Suhaib Iqbal

  9. Department of Chemistry, Raghu Engineering College, Visakhapatnam, Andhra Pradesh, 531162, India

    G. V. Siva Prasad

  10. School of Applied and Life Sciences, Division of Research and Innovation, Uttaranchal University, Dehradun, India

    Atreyi Pramanik

  11. IES Institute of Pharmacy, IES University, Bhopal, Madhya Pradesh, 462044, India

    Teena Vishwakarma

  12. New Delhi Institute of Management, Delhi, India

    Praveen Malik

  13. Department of Microbiology, Graphic Era (Deemed to Be University, Clement Town, Dehradun, 248002, India

    Promila Sharma

  14. Center for Global Health Research, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India

    Mahendra Pratap Singh

  15. Centre of Research Impact and Outcome, Chitkara University, Rajpura, Punjab, 140417, India

    Ankit Punia

  16. Chitkara Centre for Research and Development, Chitkara University, Himachal, 174103, Pradesh, India

    Megha Jagga

  17. University Center for Research and Development, Chandigarh University, Mohali, Punjab, India

    Muhammed Shabil

  18. Medical Laboratories Techniques Department, AL-Mustaqbal University, Hillah, Babil, 51001, Iraq

    Muhammed Shabil

  19. Clinical Microbiology, RDC, Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, 121004, India

    Rachana Mehta

  20. Dr Lal PathLabs - Nepal, Chandol-4, Maharajgunj, Kathmandu, 44600, Nepal

    Rachana Mehta

  21. SR Sanjeevani Hospital, Kalyanpur, Siraha, 56517, Nepal

    Sanjit Sah

  22. Department of Paediatrics, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, 411018, India

    Sanjit Sah

  23. Department of Public Health Dentistry, Dr. D.Y. Patil Dental College and Hospital, Dr. D.Y. Patil Vidyapeeth, Pune, Maharashtra, 411018, India

    Sanjit Sah

  24. Department of Medicine, Korea Universtiy, Seoul, South Korea

    Sanjit Sah

  25. South Asia Infant Feeding Research Network, Division of Evidence Synthesis, Global Consortium of Public Health and Research, Dattameghe Institute of Higher Education, Wardha, India

    Quazi Syed Zahiruddin

Authors
  1. Doddolla Lingamaiah
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  2. Ganesh Bushi
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  3. Shilpa Gaidhane
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  20. Quazi Syed Zahiruddin
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Contributions

Conceptualization: G.B., D.L., S.G., A.K.B. Data curation: G.P., I.K., M.L., S.I. Formal analysis: G.V.S.P., A.P., T.V., P.M. Investigation: P.S., M.P.S., A.Y., A.P. Methodology: M.J., M.S., R.M., S.S. Project administration: Q.S.Z., G.B., D.L., S.G. Resources: A.K.B., G.P., I.K., M.L. Software: S.I., G.V.S.P., A.P., T.V. Supervision: P.M., P.S., M.P.S., A.Y. Validation: A.P., M.J., M.S., R.M. Visualization: S.S., Q.S.Z., G.B., D.L. Writing – original draft: S.G., A.K.B., G.P., I.K. Writing – review & editing: M.L., S.I., G.V.S.P., A.P.

Corresponding authors

Correspondence to Sanjit Sah or Quazi Syed Zahiruddin.

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Not applicable, as there were no human participants involved in this study.

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Not applicable, as this study does not involve any individual person’s data in any forms.

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The authors declare no competing interests.

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Supplementary Information

12877_2025_5722_MOESM1_ESM.docx

Supplementary Material 1: Table S1. PRISMA checklist. Table S2. Inclusion and Exclusion criteria. Table S3. The adjusted search terms as per searched electronic databases. Table S4. Modified-Newcastle–Ottawa Scale (NOS). Figure S1. Sensitivity analysis (Leave-one-out) assessing the influence of individual studies on the pooled prevalence of falls. Figure S2. Leave-one-out meta-analysis showing the risk of falls in geriatric cancer versus non-cancer patients. Figure S3. DOI plot with LFK index assessing publication bias in the meta-analysis of falls among geriatric cancer patients.

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Lingamaiah, D., Bushi, G., Gaidhane, S. et al. Falls among geriatric cancer patients: a systematic review and meta-analysis of prevalence and risk across cancer types. BMC Geriatr 25, 179 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-05722-1

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Keywords

BMC Geriatrics

ISSN: 1471-2318

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