Does frailty modulate the predictive value of performance status in older adults living with cancer?

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Daniela Patino-Hernández, Mario Ulises Pérez-Zepeda, Natalia Sánchez-Garrido, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6285336/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2025 Read the published version in Aging Clinical and Experimental Research → Version 1 posted 9 You are reading this latest preprint version Abstract Background. Cancer treatments are not a one-size-fits-all approach, treatment options are rarely studied in aging individuals, leading to worse outcomes related to increased vulnerability in this group of patients. Aims. Since frailty has shown the ability to modify outcomes, our study aims to assess if frailty modifies the association between performance status and days in bed with mortality risk in older adults with cancer. Methods. Our study is a secondary analysis of the Mexican Health and Aging Study, a cohort with a representative sample of individuals aged 50 years or older, with a baseline assessment in 2001 and follow-up data available for the years 2003, 2012, 2015, 2018 and 2021. We extracted the baseline variables from the main questionnaires, and the next-of-kin questionnaires were employed for information regarding mortality. We used Cox regression and Kaplan‒Meier curves for survival analysis. Results. Our sample was composed of 318 individuals, with a mean age of 68.02 years (± SD 10.78), and 62.57% were women. Cox regression revealed that age was a significant risk factor for mortality in frail patients but not in those with low frailty levels. Discussion. in settings where access to a geriatric assessment is limited or would significantly delay cancer-specific therapies, assessing frailty might improve the accuracy of those available cancer prognostic tools that might underperform in frail older adults. Conclusions. Frailty evaluation improves the assessment of older adults living with cancer. Days in bed performance status cancer older adults frailty. Figures Figure 1 Figure 2 Figure 3 Figure 4 Highlights - Frailty alters the predictive value of performance status in older cancer patients. - Higher frailty levels reduce the prognostic power of physical performance measures. - Social vulnerability strongly influences mortality, independent of frailty status. - Geriatric assessments are crucial for improving cancer prognosis in older adults. 1. Introduction Cancer treatments are not a one-size-fits-all approach, and even when age is a well-known risk factor for developing malignant neoplasms, course and treatment options are scarcely studied in aging individuals, leading in many cases to worse outcomes, due to increased vulnerability of these individuals [ 1 ]. Frequently impaired functional and cognitive status, increase the risk for treatment-related toxicity, leading to a decline of overall health or even death [ 2 ]. For example, social vulnerability; understood as the degree to which susceptibility to health problems may be modulated by the complexity of a particular social situations (e.g., family members, friends, community engagement, financial income, etc.), has shown to be a relevant factor into health outcomes of older adults [ 3 , 4 ]. Moreover, socioeconomic and cultural factors have important roles in these outcomes of older adults suffering from cancer [ 5 ]. On the other hand, frailty —the age-related phenomenon of increased susceptibility to common stressors— is associated with multiple adverse outcomes across common conditions of the older adults [ 6 , 7 ]. On the other hand, evidence has shown that this condition can shape the prognosis of individuals (e.g., diseases, treatments, emotional crises), particularly those diagnosed with cancer [ 8 , 9 ]; challenging the results of many tools adopted to predict adverse outcomes in younger individuals. Regarding cancer prognosis, functional status has been evidenced as having a better prognostic value in oncology than other parameters –such as age– accurately establishing prognosis, tolerance, quality of life and treatment response [ 10 , 11 ]. Indeed, two of the most used instruments for assessing performance status in oncological practice include the Eastern Cooperative Oncology Group (ECOG) and the Karnofsky scale [ 12 ], both of which include functional performance assessment. However, these instruments have been criticized for being highly subjective and not being able to detect real-time changes of potential clinical relevance (e.g., low prognostic value for older adults) [ 11 , 13 ]. Additionally, these evaluations were not initially intended to assess older adults and might not have the same clinimetric properties as in younger individuals [ 14 ], leading to undertreatment if functional status were to be underestimated. Therefore, we hypothesize that different frailty levels affect the associations of a measurement that includes days in bed and physical functioning with mortality, independent of other variables, such as social vulnerability. Our study aims to assess if frailty modifies the association of performance status and days in bed with mortality risk in older adults with cancer. 2. Methods 2.1 Design and Sample This is a secondary analysis of the Mexican Health and Aging Study (MHAS), a cohort with a national-level representative sample from Mexican individuals aged 50-years or older. In brief, this study aims to determine the factors that impact aging in Mexican individuals and consists of several waves, with a baseline assessment in 2001; follow-up data are available for the years 2003, 2012, 2015, 2018 and 2021; information from a wide array of topics was obtained from face‒to‒face interviews conducted by trained personnel. Further details about MHAS can be found elsewhere [ 15 – 17 ]. For this work, we used data from MHAS assessments from 2012, 2015 and 2018 and follow-up information on survival status through 2021. We extracted the baseline variables from the main questionnaires, and the next-of-kin (NOK) questionnaires were used for information regarding mortality. All individuals ≥ 50 years old who answered directly to the baseline interview and with complete data (both baseline and follow-up) were included (Fig. 1 ). 2.2 Variables 2.2.1 Cancer status Subjects who reported having cancer were identified by asking the following question: ‘Has a doctor or medical personnel ever diagnosed you with cancer?' If the individual answered ‘yes’ a follow-up question regarding the type of cancer was asked (including breast, cervix, endometrial/uterine, liver, stomach, pancreas, prostate, colorectal, and lung) (see Fig. 2 ). Our sample was composed only of ‘incident' cases, meaning that they had not previously been diagnosed with cancer and did not refer having cancer in previous waves. We further restricted our sample to include only subjects who reported being treated currently in any of the subsequent follow-up interviews. These two criteria (new cancer and currently receiving treatment) were introduced to maximize the approximation to ‘real-world’ and actual clinical practice. Finally, the type of cancer and treatment (surgery, radiotherapy or chemotherapy) were included for descriptive purposes. 2.2.2 Performance status, physical activity and days in bed assessment The Eastern Cooperative Oncology Group (ECOG) scale is based on the time spent in bed, with 0 representing full functionality for asymptomatic patients and 4 being bedridden [ 13 ]. Since MHAS does not include measurements to assess cancer prognosis due to its general scope of aging, the performance status was constructed with available variables in the study measuring days in bed, physical function and exercise. Firstly, number of days spent in bed per year was obtained through the following question: ‘Owing to sickness or injury, during the last 12 months, how many days did you stay in bed for at least half the day?' [ 18 ]. Secondly, physical activity was assessed by answering yes or no to the following question: ‘On average, during the previous two years, have you exercised or had done vigorous physical activity three times a week or more? ´ Finally, basic and instrumental activities of daily living were included, as follows: the MHAS includes a set of 19 of these activities (please see supplementary material); whenever an older adult answered that they were not able to perform an activity, a score of 1 was assigned; if no difficulty was present, the score was 0; and if help was required to perform the activity, a score of 0.5 was assigned. The scores were summed, resulting in a score of 0 (no difficulties in activities of daily living) or up to 19, the highest possible score (impossibility of performing all the assessed activities). More detail can be found in supplementary Table 1. We then categorized the performance status score into 5 categories: 0 (< 50% of days spent in bed during the previous year, no disability and reported physical activity), 1 (< 50% of days spent in bed during the previous year, no disability and no report of physical activity), 2 ( 50% of days spent in bed during the previous year, no disability and no report of physical activity), and 4 (> 50% of days spent in bed during the previous year, disability and no report of physical activity). 2.2.3 Mortality All-cause mortality was our outcome of interest, including time to event, for survival analysis. For those who survived, follow-up days were calculated as the difference between the interview date in 2001 and that from 2021; in a similar fashion, time to event was calculated as the difference in days from the baseline interview to the reported date of death. 2.2.4 Frailty index The frailty index (FI) was calculated from 33 variables related to self-reported health, comorbidities, depressive symptoms and other symptoms [ 19 ]. The FI is a synthetic measurement grounded on the deficit accumulation theory, that has been used and validated in MHAS [ 20 ]. A modified version of the original 52-item FI used in MHAS was used, since variables previously used, for purposes of this work had to be excluded since they were incorporated into the previously described tool for cancer prognosis (see above). Characteristics of the index, such as: prevalence of the deficits, coding and definition from MHAS are available in supplementary Table 2. 2.2.5 Sociodemographic characteristics We included the following variables: age in years and sex, marital status (married/civil union versus without a couple), and the number of completed years of formal education. 2.2.6 Social vulnerability index This variable was created by combining various items suggestive of living conditions for everyone, including marital status, support provided by friends and family, social activities and hobbies, among others [ 21 , 22 ]. The social vulnerability index (SVI) was created using the methods described [ 23 ] and has been previously used in MHAS [ 3 ]. A more detailed description can be found in Supplementary Table 3. 2.2.7 Lifestyle Smoking status was assessed based on the following questions: ‘Have you smoked more than 100 cigarettes or 5 packs in your lifetime; not including pipes or cigars?’ and ‘Do you smoke cigarettes now?’, resulting in three categories: never smoked, used to smoke and current smoking. Physical activity was defined as exercising ≥ 3 times a week in the previous year. Finally, risky alcohol use was defined as exercising ≥ 2 drinks per day for women and ≥ 3 drinks per day for men [ 24 ]. 2.3 Statistical analysis We conducted a descriptive analysis of all the variables and bivariate analyses by survival status for baseline characteristics, using chi-square tests for all the variables (except for FI and SVI, where t tests were used). Descriptive statistics were used to report these findings. In addition, Kaplan–Meier curves were plotted to assess the differences between performance status groups and other cancer-related variables; log-rank tests were used for statistical significance. Cox regression models were fitted to test the associations with mortality with hazard ratios (HR). Interaction terms between FI and performance status variables were included for the whole sample and were unadjusted and adjusted for baseline characteristics. All the statistical analyses were performed with the statistical software StataNow 18.5 (Stata Corp LLC, 4905 Lakeway Dr; College Station, TX, USA). 3. Results 3.1 Descriptive statistics Our sample was composed of 318 individuals (Figure 1), with a mean age of 68.02 years (SD 10.78), and most were women (62.57%). The main types of cancer found in our sample were breast cancer (26%), cervical cancer (24%) and endometrial cancer (23%) (see Figure 2). Chemotherapy was the most common treatment (47.33%), surgery was part of the treatment for 33.96% of the sample, and radiotherapy was the least used reported treatment for 21.39% of the studied individuals (see Figure 3). Overall, 22.64% of the sample were physically active. With respect to smoking status, approximately one-third of the sample were former smokers (30.48%), and 9.09% were active smokers. Risky alcohol was present in 8.56% of the individuals. No statistically significant differences were found for age, sex, alcohol or cigarette consumption or physical activity among individuals who were alive and those who were deceased at follow-up. However, those who died had higher means for the frailty index, social vulnerability status, days in bed and performance status scores (see Table 1). 3.2 Kaplan‒Meier survival estimates The Kaplan–Meier curves further revealed greater survival in patients with better performance status (lower scores) – (0.81% mortality with performance status category 0) - which decreased with increasing scores (worse performance status). – (49.6% mortality with performance status category 4) (see Figure 4). However, the group with higher mortality was the one categorized as 4, a statistically significant difference (p<0.001). Cox regression models Cox regression revealed that for low frailty levels, the social vulnerability index (HR 234.79; 95% CI 4.51–12222.8; p =0.007) and performance status 2 (HR 5.46; 95% CI 1.24–24.04; p =0.025) were significantly associated with increased risk of mortality, whereas age, sex, smoking status, and alcohol intake did not affect mortality risk. In contrast, among individuals with high frailty levels, age (HR 1.04; 95% CI 1.00–1.07; p =0.039) was the only significant predictor of increased risk. Additionally, when the performance status score was analyzed, a score of 4 clearly increased mortality 8-fold, but this association was lost in those with high frailty levels (see Table 2). 4. Discussion According to our results, older adults suffering from cancer and low frailty levels, the composite tool for performance status was associated with higher mortality rates, the higher the composite tool score category was. In fact, previous reports have consistently demonstrated this association across different types of cancer [ 25 – 27 ]. However, our results showed that in individuals with high frailty levels, this composite tool was not associated with mortality. Interestingly, other variables such as the SVI also lost their significant association for mortality. Older adults with cancer are at greater risk for mortality, treatment-related complications, hospitalizations and admissions to long-term care facilities [ 1 ]. Unlike younger patients, whose treatment decisions are typically based on outcomes such as survival and progression-free survival, for older adults, treatment goals should also include minimizing toxicity, maximizing quality of life and maintaining functional independence [ 28 ]. This broader focus has recently led to updates in guidelines from the American Society of Clinical Oncology (ASCO) and the Society of Geriatric Oncology (SGO), recommending the inclusion of comprehensive assessments of age-associated vulnerabilities in older patients receiving systemic cancer therapies [ 29 – 31 ]. For example, two randomized clinical trials published recently, the Geriatric Assessment for Patients 70 years and Older (GAP70+) and the Geriatric Assessment-Driven Intervention (GAIN), demonstrated the impact of an integral geriatric assessment (IGA) on reducing the risk of toxicity and improving clinical outcomes in older adults. By identifying vulnerabilities (i.e., frailty) and tailoring treatment plans accordingly, these studies have shown that IGA can help mitigate treatment-related risks and improve overall patient well-being [ 2 , 32 ]. However, while cost-effective and highly useful, the implementation of this assessment may be limited by resource and geriatricians’ availability across different settings [ 33 ]. Furthermore, our findings suggest that older adults suffering from high levels of frailty, physical performance —typically a cornerstone of cancer prognosis—is less predictive of mortality. This may be due to under recognition of frailty in settings where ECOG scores –or other similar tools– can be influenced by subjective assessments of a patient's functional status. For example, it has been reported that older adults often receive worst ECOG scores despite having similar levels of physical activity as younger individuals [ 14 ]. This underestimation of functional status can lead to undertreatment. On the other hand, ECOG scores may be overestimated in older adults who are deemed “normal for their age,” potentially masking manageable conditions. Moreover, recent studies suggest that clinicians have a limited ability to predict toxicity based on performance status alone, further emphasizing the need for additional evaluation for older adults suffering from cancer [ 34 ]. Our results also highlight the relevance of social vulnerability in predicting outcomes for older cancer patients, even when frailty is not present. On this matter, a study by Stuart et al. revealed that high social vulnerability scores were associated with patients presenting with advanced stages of cancer which lead to lower rates of surgery or chemotherapy, increasing the odds of dying due to these delays and incorrect decisions [ 35 ]. We recognize that our study has several limitations. This is a secondary analysis of already available data; the latter implies that we created our variables based on information that had been collected in a standardized fashion but that were not collected specifically for our research question. Furthermore, different ways of assessing frailty exist; if a different approach is used, the results may differ. However, our study also has various strengths to consider. For example, this is a representative cohort of individuals followed for 20 years. This allows our conclusions to represent not only a large population but also a significant period, indicating that despite changes in available therapies, frailty continues to modulate the predictive ability of prognostic scores in older adults with cancer. Furthermore, lifestyle factors such as risky alcohol intake and smoking, as well as social vulnerability risk, which are known to be linked to worse outcomes, were considered covariates, which allows conclusions to be of greater strength. 5. Conclusion Our results highlight the importance of frailty as a key element in treatment decision-making and outcomes in older cancer patients. While performance status remains a valuable tool, its predictive value diminishes when frailty is present. The latter reflects the complexity of assessing prognosis in older adults with cancer, where factors such as frailty may overshadow other clinical markers, making a geriatric assessment a cornerstone of rational treatment in this group of patients. Declarations 6. Acknowledgments None 7. Conflict of interest The authors declare that they have no conflicts of interest. 8. Data availability The MHAS (Mexican Health and Aging Study) is partly sponsored by the National Institutes of Health/National Institute on Aging (grant number NIH R01AG018016) in the United States and the Instituto Nacional de Estadística y Geografía (INEGI) in Mexico. Data files and documentation are publicly available at www.MHASweb.org. Prior to accessing MHAS public data, we request that the user register (free of charge) and agree to the following terms. 9. IRB statement TheInstitutional Review Boards of the University of Texas Medical Branch (Galveston, Texas, USA) and the National Institute of Public Health in Mexico reviewed and approved the MHAS. All the subjects provided signed informed consent, and all the procedures were performed in accordance with the Helsinki declaration. 10. CRediT author statement Daniela Patino-Hernandez. : Conceptualization, Methodology, Data curation, Writing- Original draft preparation. Mario Ulises Pérez-Zepeda: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation. Natalia Sánchez-Garrido: Writing- Reviewing and Editing. Alejandro Eliú Cedillo: Writing- Reviewing and Editing. Eduardo Cárdenas-Cárdenas: Writing- Reviewing and Editing. 11. Funding sources: The MHAS (Mexican Health and Aging Study) is partly sponsored by the National Institutes of Health/National Institute on Aging (grant number NIH R01AG018016) in the United States and the Instituto Nacional de Estadística y Geografía (INEGI) in Mexico. References Soo WK, King MT, Pope A, Parente P, Darzins P, Davis ID. Integrated Geriatric Assessment and Treatment Effectiveness (INTEGERATE) in older people with cancer starting systemic anticancer treatment in Australia: a multicentre, open-label, randomised controlled trial. Lancet Healthy Longev. 2022 Sep;3(9):e617-e27. Mohile SG, Mohamed MR, Xu H, Culakova E, Loh KP, Magnuson A, et al. Evaluation of geriatric assessment and management on the toxic effects of cancer treatment (GAP70+): a cluster-randomised study. Lancet. 2021 Nov 20;398(10314):1894-904. Sánchez-Garrido N, Aguilar-Navarro SG, Ávila-Funes JA, Theou O, Andrew M, Pérez-Zepeda MU. 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Descriptive statistics Dead Alive p value Age, mean (SD) 70.9 (0.92) 66.6 (0.67) 0.047 Female, n (%) 66 (66.9) 168 (53.7) 0.010 Physical activity, n (%) 12 (13.4) 60 (26.2) 0.015 Frailty index, mean (SD) 0.339 (0.153) 0.351 (0.011) <0.001 Social vulnerability index, mean (SD) 0.469 (0.106) 0.436 (0.109) <0.001 Days in bed, mean (SD) 23 (47.9) 7.3 (16.4) <0.001 Physical function score, mean (SD) 3.6 (3.02) 2.5 (2.53) <0.001 Smoking status, n (%) Never smoked Smoked in the past Currently smokes 69 (56.10) 39 (31.71) 15 (12.20) 157 (62.55) 75 (29.88) 19 (7.57) 0.272 Alcohol intake status*, n (%) 9 (7.32) 23 (9.16) 0.549 Performance status categories, n (%) 0 1 2 3 4 1 (0.81) 3 (2.44) 26 (21.14) 32 (26.02) 61 (49.59) 11 (4.38) 20 (7.97) 71 (28.29) 89 (35.46) 60 (23.90) <0.001 *≥2 drinks a day for women, ≥3 drinks a day for men Table 2. Cox regression models Low frailty levels, HR (CI 95%, p value) High frailty levels, HR (CI 95%, p value) Age 1.02 (0.98-1.06, 0.373) 1.04 (1.00-1.07, 0.039) Female 0.62 (0.28-1.36, 0.223) 0.56 (0.35-1.35, 0.281) Social vulnerability index 234.79 (4.51-12,222.8, 0.007) 0.56 (0.04-8.39, 0.678) Smoking status Never smoked Smoked in the past Currently smokes Reference 1.21 (0.52-2.85, 0.664) 1.60 (0.41-6.28, 0.498) Reference 0.95 (0.49-1.83, 0.864) 0.86 (0.33-2.35, 0.807) Alcohol intake 0.66 (0.18-2.44, 0.538) 1.86 (0.51-6.81, 0.347) Performance status 0 and 1 levels reference groups 2 5.46 (1.24-24.04, 0.025) 0.52 (0.08-3.28, 0.490) 3 3.98 (0.84-18.73, 0.081) 1.15 (0.25-5.25, 0.855) 4 8.01 (1.50-42.66, 0.015) 3.13 (0.73-13.47, 0.126) Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Published Journal Publication published 30 Oct, 2025 Read the published version in Aging Clinical and Experimental Research → Version 1 posted Editorial decision: Revision requested 01 Jul, 2025 Reviews received at journal 28 Jun, 2025 Reviewers agreed at journal 19 Jun, 2025 Reviews received at journal 17 Apr, 2025 Reviewers agreed at journal 27 Mar, 2025 Reviewers invited by journal 26 Mar, 2025 Editor assigned by journal 24 Mar, 2025 Submission checks completed at journal 23 Mar, 2025 First submitted to journal 22 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Pérez-Zepeda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYPACGx4YK4FYLWmkazkMZxHWoju7+diHD3/Oy5jzLz72geGXTR6D2BkDvFrM7hxLnjmD5zaP5YxnyTMY+9KKGaTT8NtkdiPHmJlH4jaPwY0zxgyMPYcTG6STDxDQkv+Z+Y/BOaCW85+hWhIbCNnCzMyQcIDH4HwPMwPDD2JsuXPMmLHnQDLQFjZjhsSGtGI2gn653fyY4ccfO3uD84cfM3z4Y5PHL52DP8QYJOAMoNmJbQwMbPjVI2vhB/ngD0H1o2AUjIJRMAIBAG4gR8x0aep9AAAAAElFTkSuQmCC","orcid":"","institution":"Instituto Nacional de Geriatría","correspondingAuthor":true,"prefix":"","firstName":"Mario","middleName":"Ulises","lastName":"Pérez-Zepeda","suffix":""},{"id":442057015,"identity":"61b1350b-b0d0-490b-89a0-c5c9b6ca86dc","order_by":2,"name":"Natalia Sánchez-Garrido","email":"","orcid":"","institution":"Instituto Nacional de Geriatría","correspondingAuthor":false,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Sánchez-Garrido","suffix":""},{"id":442057016,"identity":"e9d47cac-b498-4f5d-af19-8ae23b7a34d2","order_by":3,"name":"Alejandro Eliú Cedillo","email":"","orcid":"","institution":"Instituto Nacional de Geriatría","correspondingAuthor":false,"prefix":"","firstName":"Alejandro","middleName":"Eliú","lastName":"Cedillo","suffix":""},{"id":442057017,"identity":"fc4880f1-49f8-4421-93fb-0a2bcae6516c","order_by":4,"name":"Eduardo Cárdenas-Cárdenas","email":"","orcid":"","institution":"Centro Médico Nacional 20 de Noviembre","correspondingAuthor":false,"prefix":"","firstName":"Eduardo","middleName":"","lastName":"Cárdenas-Cárdenas","suffix":""}],"badges":[],"createdAt":"2025-03-22 20:08:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6285336/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6285336/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40520-025-03203-4","type":"published","date":"2025-10-30T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80584032,"identity":"3fe6bd2f-ff7d-48f0-8d8a-a5482cc94c1b","added_by":"auto","created_at":"2025-04-15 00:16:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44236,"visible":true,"origin":"","legend":"\u003cp\u003eSample flow chart\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6285336/v1/14c6c16359606b508317419c.jpg"},{"id":80584035,"identity":"22d66e45-0771-46a6-b54b-4336986eee3c","added_by":"auto","created_at":"2025-04-15 00:16:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37225,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of the different types of cancer for the sample\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6285336/v1/41817cccae97602c2201a6f5.jpg"},{"id":80584037,"identity":"fe72bfb7-a74c-4603-ade7-972dbdf49a32","added_by":"auto","created_at":"2025-04-15 00:16:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26627,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of the different types of treatment received as main therapy\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6285336/v1/a206fda0a64e6d6dcaa4c8cd.jpg"},{"id":80584036,"identity":"837cf36f-be79-4e8b-8447-18e9518fcc4d","added_by":"auto","created_at":"2025-04-15 00:16:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":24887,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan‒Meier survival estimates according to performance status categories\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6285336/v1/508775ca5e879de0a9252836.jpg"},{"id":95040460,"identity":"dec0daaa-e0dc-4001-a10c-2f818ed4247c","added_by":"auto","created_at":"2025-11-03 16:09:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":833603,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6285336/v1/db041104-f03b-431e-bb14-eaae02e2a66b.pdf"},{"id":80584628,"identity":"ca6dcc10-08e6-4ba1-be4f-8c4592ede926","added_by":"auto","created_at":"2025-04-15 00:24:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":37023,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6285336/v1/91074642da7ae2de85d95154.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Does frailty modulate the predictive value of performance status in older adults living with cancer?","fulltext":[{"header":"Highlights","content":"\u003cp\u003e- Frailty alters the predictive value of performance status in older cancer patients.\u003c/p\u003e\u003cp\u003e- Higher frailty levels reduce the prognostic power of physical performance measures.\u003c/p\u003e\u003cp\u003e- Social vulnerability strongly influences mortality, independent of frailty status.\u003c/p\u003e\u003cp\u003e- Geriatric assessments are crucial for improving cancer prognosis in older adults.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eCancer treatments are not a one-size-fits-all approach, and even when age is a well-known risk factor for developing malignant neoplasms, course and treatment options are scarcely studied in aging individuals, leading in many cases to worse outcomes, due to increased vulnerability of these individuals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Frequently impaired functional and cognitive status, increase the risk for treatment-related toxicity, leading to a decline of overall health or even death [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. For example, social vulnerability; understood as the degree to which susceptibility to health problems may be modulated by the complexity of a particular social situations (e.g., family members, friends, community engagement, financial income, etc.), has shown to be a relevant factor into health outcomes of older adults [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, socioeconomic and cultural factors have important roles in these outcomes of older adults suffering from cancer [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, frailty \u0026mdash;the age-related phenomenon of increased susceptibility to common stressors\u0026mdash; is associated with multiple adverse outcomes across common conditions of the older adults [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. On the other hand, evidence has shown that this condition can shape the prognosis of individuals (e.g., diseases, treatments, emotional crises), particularly those diagnosed with cancer [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; challenging the results of many tools adopted to predict adverse outcomes in younger individuals.\u003c/p\u003e \u003cp\u003eRegarding cancer prognosis, functional status has been evidenced as having a better prognostic value in oncology than other parameters \u0026ndash;such as age\u0026ndash; accurately establishing prognosis, tolerance, quality of life and treatment response [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Indeed, two of the most used instruments for assessing performance status in oncological practice include the Eastern Cooperative Oncology Group (ECOG) and the Karnofsky scale [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], both of which include functional performance assessment. However, these instruments have been criticized for being highly subjective and not being able to detect real-time changes of potential clinical relevance (e.g., low prognostic value for older adults) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, these evaluations were not initially intended to assess older adults and might not have the same clinimetric properties as in younger individuals [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], leading to undertreatment if functional status were to be underestimated.\u003c/p\u003e \u003cp\u003eTherefore, we hypothesize that different frailty levels affect the associations of a measurement that includes days in bed and physical functioning with mortality, independent of other variables, such as social vulnerability. Our study aims to assess if frailty modifies the association of performance status and days in bed with mortality risk in older adults with cancer.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Design and Sample\u003c/h2\u003e \u003cp\u003eThis is a secondary analysis of the Mexican Health and Aging Study (MHAS), a cohort with a national-level representative sample from Mexican individuals aged 50-years or older. In brief, this study aims to determine the factors that impact aging in Mexican individuals and consists of several waves, with a baseline assessment in 2001; follow-up data are available for the years 2003, 2012, 2015, 2018 and 2021; information from a wide array of topics was obtained from face‒to‒face interviews conducted by trained personnel. Further details about MHAS can be found elsewhere [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor this work, we used data from MHAS assessments from 2012, 2015 and 2018 and follow-up information on survival status through 2021. We extracted the baseline variables from the main questionnaires, and the next-of-kin (NOK) questionnaires were used for information regarding mortality. All individuals\u0026thinsp;\u0026ge;\u0026thinsp;50 years old who answered directly to the baseline interview and with complete data (both baseline and follow-up) were included (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Variables\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Cancer status\u003c/h2\u003e \u003cp\u003eSubjects who reported having cancer were identified by asking the following question: \u0026lsquo;Has a doctor or medical personnel ever diagnosed you with cancer?' If the individual answered \u0026lsquo;yes\u0026rsquo; a follow-up question regarding the type of cancer was asked (including breast, cervix, endometrial/uterine, liver, stomach, pancreas, prostate, colorectal, and lung) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Our sample was composed only of \u0026lsquo;incident' cases, meaning that they had not previously been diagnosed with cancer and did not refer having cancer in previous waves. We further restricted our sample to include only subjects who reported being treated currently in any of the subsequent follow-up interviews. These two criteria (new cancer and currently receiving treatment) were introduced to maximize the approximation to \u0026lsquo;real-world\u0026rsquo; and actual clinical practice. Finally, the type of cancer and treatment (surgery, radiotherapy or chemotherapy) were included for descriptive purposes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Performance status, physical activity and days in bed assessment\u003c/h2\u003e \u003cp\u003eThe Eastern Cooperative Oncology Group (ECOG) scale is based on the time spent in bed, with 0 representing full functionality for asymptomatic patients and 4 being bedridden [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Since MHAS does not include measurements to assess cancer prognosis due to its general scope of aging, the performance status was constructed with available variables in the study measuring days in bed, physical function and exercise. Firstly, number of days spent in bed per year was obtained through the following question: \u0026lsquo;Owing to sickness or injury, during the last 12 months, how many days did you stay in bed for at least half the day?' [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Secondly, physical activity was assessed by answering yes or no to the following question: \u0026lsquo;On average, during the previous two years, have you exercised or had done vigorous physical activity three times a week or more? \u0026acute; Finally, basic and instrumental activities of daily living were included, as follows: the MHAS includes a set of 19 of these activities (please see supplementary material); whenever an older adult answered that they were not able to perform an activity, a score of 1 was assigned; if no difficulty was present, the score was 0; and if help was required to perform the activity, a score of 0.5 was assigned. The scores were summed, resulting in a score of 0 (no difficulties in activities of daily living) or up to 19, the highest possible score (impossibility of performing all the assessed activities). More detail can be found in supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eWe then categorized the performance status score into 5 categories: 0 (\u0026lt;\u0026thinsp;50% of days spent in bed during the previous year, no disability and reported physical activity), 1 (\u0026lt;\u0026thinsp;50% of days spent in bed during the previous year, no disability and no report of physical activity), 2 (\u0026lt;\u0026thinsp;50% of days spent in bed during the previous year, disability and no report of physical activity), 3 (\u0026gt;\u0026thinsp;50% of days spent in bed during the previous year, no disability and no report of physical activity), and 4 (\u0026gt;\u0026thinsp;50% of days spent in bed during the previous year, disability and no report of physical activity).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Mortality\u003c/h2\u003e \u003cp\u003eAll-cause mortality was our outcome of interest, including time to event, for survival analysis. For those who survived, follow-up days were calculated as the difference between the interview date in 2001 and that from 2021; in a similar fashion, time to event was calculated as the difference in days from the baseline interview to the reported date of death.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 Frailty index\u003c/h2\u003e \u003cp\u003eThe frailty index (FI) was calculated from 33 variables related to self-reported health, comorbidities, depressive symptoms and other symptoms [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The FI is a synthetic measurement grounded on the deficit accumulation theory, that has been used and validated in MHAS [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A modified version of the original 52-item FI used in MHAS was used, since variables previously used, for purposes of this work had to be excluded since they were incorporated into the previously described tool for cancer prognosis (see above). Characteristics of the index, such as: prevalence of the deficits, coding and definition from MHAS are available in supplementary Table\u0026nbsp;2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5 Sociodemographic characteristics\u003c/h2\u003e \u003cp\u003eWe included the following variables: age in years and sex, marital status (married/civil union versus without a couple), and the number of completed years of formal education.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.6 Social vulnerability index\u003c/h2\u003e \u003cp\u003eThis variable was created by combining various items suggestive of living conditions for everyone, including marital status, support provided by friends and family, social activities and hobbies, among others [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The social vulnerability index (SVI) was created using the methods described [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and has been previously used in MHAS [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A more detailed description can be found in Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.7 Lifestyle\u003c/h2\u003e \u003cp\u003eSmoking status was assessed based on the following questions: \u0026lsquo;Have you smoked more than 100 cigarettes or 5 packs in your lifetime; not including pipes or cigars?\u0026rsquo; and \u0026lsquo;Do you smoke cigarettes now?\u0026rsquo;, resulting in three categories: never smoked, used to smoke and current smoking. Physical activity was defined as exercising\u0026thinsp;\u0026ge;\u0026thinsp;3 times a week in the previous year. Finally, risky alcohol use was defined as exercising\u0026thinsp;\u0026ge;\u0026thinsp;2 drinks per day for women and \u0026ge;\u0026thinsp;3 drinks per day for men [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003eWe conducted a descriptive analysis of all the variables and bivariate analyses by survival status for baseline characteristics, using chi-square tests for all the variables (except for FI and SVI, where t tests were used). Descriptive statistics were used to report these findings.\u003c/p\u003e \u003cp\u003eIn addition, Kaplan\u0026ndash;Meier curves were plotted to assess the differences between performance status groups and other cancer-related variables; log-rank tests were used for statistical significance. Cox regression models were fitted to test the associations with mortality with hazard ratios (HR). Interaction terms between FI and performance status variables were included for the whole sample and were unadjusted and adjusted for baseline characteristics. All the statistical analyses were performed with the statistical software StataNow 18.5 (Stata Corp LLC, 4905 Lakeway Dr; College Station, TX, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cem\u003e3.1 Descriptive statistics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOur sample was composed of 318 individuals (Figure 1), with a mean age of 68.02 years (SD 10.78), and most were women (62.57%). The main types of cancer found in our sample were breast cancer (26%), cervical cancer (24%) and endometrial cancer (23%) (see Figure 2). Chemotherapy was the most common treatment (47.33%), surgery was part of the treatment for 33.96% of the sample, and radiotherapy was the least used reported treatment for 21.39% of the studied individuals (see Figure 3).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Overall, 22.64% of the sample were physically active. With respect to smoking status, approximately one-third of the sample were former smokers (30.48%), and 9.09% were active smokers. Risky alcohol was present in 8.56% of the individuals. No statistically significant differences were found for age, sex, alcohol or cigarette consumption or physical activity among individuals who were alive and those who were deceased at follow-up. However, those who died had higher means for the frailty index, social vulnerability status, days in bed and performance status scores (see Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2 Kaplan‒Meier survival estimates\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Kaplan\u0026ndash;Meier curves further revealed greater survival in patients with better performance status (lower scores) \u0026ndash; (0.81% mortality with performance status category 0) - which decreased with increasing scores (worse performance status). \u0026ndash; (49.6% mortality with performance status category 4) (see Figure 4). However, the group with higher mortality was the one categorized as 4, a statistically significant difference (p\u0026lt;0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCox regression models\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCox regression revealed that for low frailty levels, the social vulnerability index (HR 234.79; 95% CI 4.51\u0026ndash;12222.8; \u003cem\u003ep\u003c/em\u003e=0.007) and performance status 2 (HR 5.46; 95% CI 1.24\u0026ndash;24.04; \u003cem\u003ep\u003c/em\u003e=0.025) were significantly associated with increased risk of mortality, whereas age, sex, smoking status, and alcohol intake did not affect mortality risk. In contrast, among individuals with high frailty levels, age (HR 1.04; 95% CI 1.00\u0026ndash;1.07; \u003cem\u003ep\u003c/em\u003e=0.039) was the only significant predictor of increased risk.\u003c/p\u003e\n\u003cp\u003eAdditionally, when the performance status score was analyzed, a score of 4 clearly increased mortality 8-fold, but this association was lost in those with high frailty levels (see Table 2).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAccording to our results, older adults suffering from cancer and low frailty levels, the composite tool for performance status was associated with higher mortality rates, the higher the composite tool score category was. In fact, previous reports have consistently demonstrated this association across different types of cancer [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, our results showed that in individuals with high frailty levels, this composite tool was not associated with mortality. Interestingly, other variables such as the SVI also lost their significant association for mortality.\u003c/p\u003e \u003cp\u003eOlder adults with cancer are at greater risk for mortality, treatment-related complications, hospitalizations and admissions to long-term care facilities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Unlike younger patients, whose treatment decisions are typically based on outcomes such as survival and progression-free survival, for older adults, treatment goals should also include minimizing toxicity, maximizing quality of life and maintaining functional independence [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This broader focus has recently led to updates in guidelines from the American Society of Clinical Oncology (ASCO) and the Society of Geriatric Oncology (SGO), recommending the inclusion of comprehensive assessments of age-associated vulnerabilities in older patients receiving systemic cancer therapies [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor example, two randomized clinical trials published recently, the Geriatric Assessment for Patients 70 years and Older (GAP70+) and the Geriatric Assessment-Driven Intervention (GAIN), demonstrated the impact of an integral geriatric assessment (IGA) on reducing the risk of toxicity and improving clinical outcomes in older adults. By identifying vulnerabilities (i.e., frailty) and tailoring treatment plans accordingly, these studies have shown that IGA can help mitigate treatment-related risks and improve overall patient well-being [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, while cost-effective and highly useful, the implementation of this assessment may be limited by resource and geriatricians\u0026rsquo; availability across different settings [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Furthermore, our findings suggest that older adults suffering from high levels of frailty, physical performance \u0026mdash;typically a cornerstone of cancer prognosis\u0026mdash;is less predictive of mortality. This may be due to under recognition of frailty in settings where ECOG scores \u0026ndash;or other similar tools\u0026ndash; can be influenced by subjective assessments of a patient's functional status. For example, it has been reported that older adults often receive worst ECOG scores despite having similar levels of physical activity as younger individuals [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This underestimation of functional status can lead to undertreatment. On the other hand, ECOG scores may be overestimated in older adults who are deemed \u0026ldquo;normal for their age,\u0026rdquo; potentially masking manageable conditions.\u003c/p\u003e \u003cp\u003eMoreover, recent studies suggest that clinicians have a limited ability to predict toxicity based on performance status alone, further emphasizing the need for additional evaluation for older adults suffering from cancer [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Our results also highlight the relevance of social vulnerability in predicting outcomes for older cancer patients, even when frailty is not present. On this matter, a study by Stuart et al. revealed that high social vulnerability scores were associated with patients presenting with advanced stages of cancer which lead to lower rates of surgery or chemotherapy, increasing the odds of dying due to these delays and incorrect decisions [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe recognize that our study has several limitations. This is a secondary analysis of already available data; the latter implies that we created our variables based on information that had been collected in a standardized fashion but that were not collected specifically for our research question. Furthermore, different ways of assessing frailty exist; if a different approach is used, the results may differ. However, our study also has various strengths to consider. For example, this is a representative cohort of individuals followed for 20 years. This allows our conclusions to represent not only a large population but also a significant period, indicating that despite changes in available therapies, frailty continues to modulate the predictive ability of prognostic scores in older adults with cancer. Furthermore, lifestyle factors such as risky alcohol intake and smoking, as well as social vulnerability risk, which are known to be linked to worse outcomes, were considered covariates, which allows conclusions to be of greater strength.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur results highlight the importance of frailty as a key element in treatment decision-making and outcomes in older cancer patients. While performance status remains a valuable tool, its predictive value diminishes when frailty is present. The latter reflects the complexity of assessing prognosis in older adults with cancer, where factors such as frailty may overshadow other clinical markers, making a geriatric assessment a cornerstone of rational treatment in this group of patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e6. Acknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7. Conflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8. Data availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MHAS (Mexican Health and Aging Study) is partly sponsored by the National Institutes of Health/National Institute on Aging (grant number NIH R01AG018016) in the United States and the Instituto Nacional de Estad\u0026iacute;stica y Geograf\u0026iacute;a (INEGI) in Mexico. Data files and documentation are publicly available at www.MHASweb.org. Prior to accessing MHAS public data, we request that the user register (free of charge) and agree to the following terms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e9. IRB statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTheInstitutional Review Boards of the University of Texas Medical Branch (Galveston, Texas, USA) and the National Institute of Public Health in Mexico reviewed and approved the MHAS. All the subjects provided signed informed consent, and all the procedures were performed in accordance with the Helsinki declaration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e10. CRediT author statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDaniela Patino-Hernandez.\u003c/strong\u003e: Conceptualization, Methodology, Data curation, Writing- Original draft preparation. \u003cstrong\u003eMario Ulises P\u0026eacute;rez-Zepeda:\u003c/strong\u003e Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation.\u0026nbsp;\u003cstrong\u003eNatalia S\u0026aacute;nchez-Garrido:\u003c/strong\u003e Writing- Reviewing and Editing.\u0026nbsp;\u003cstrong\u003eAlejandro Eli\u0026uacute; Cedillo:\u003c/strong\u003e Writing- Reviewing and Editing.\u0026nbsp;\u003cstrong\u003eEduardo C\u0026aacute;rdenas-C\u0026aacute;rdenas:\u003c/strong\u003e Writing- Reviewing and Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e11. Funding sources:\u003c/strong\u003e The MHAS (Mexican Health and Aging Study) is partly sponsored by the National Institutes of Health/National Institute on Aging (grant number NIH R01AG018016) in the United States and the Instituto Nacional de Estad\u0026iacute;stica y Geograf\u0026iacute;a (INEGI) in Mexico.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSoo WK, King MT, Pope A, Parente P, Darzins P, Davis ID. Integrated Geriatric Assessment and Treatment Effectiveness (INTEGERATE) in older people with cancer starting systemic anticancer treatment in Australia: a multicentre, open-label, randomised controlled trial. Lancet Healthy Longev. 2022 Sep;3(9):e617-e27.\u003c/li\u003e\n\u003cli\u003eMohile SG, Mohamed MR, Xu H, Culakova E, Loh KP, Magnuson A, et al. Evaluation of geriatric assessment and management on the toxic effects of cancer treatment (GAP70+): a cluster-randomised study. Lancet. 2021 Nov 20;398(10314):1894-904.\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-Garrido N, Aguilar-Navarro SG, \u0026Aacute;vila-Funes JA, Theou O, Andrew M, P\u0026eacute;rez-Zepeda MU. The Social Vulnerability Index, Mortality and Disability in Mexican Middle-Aged and Older Adults. Geriatrics (Basel). 2021 Mar;6(1).\u003c/li\u003e\n\u003cli\u003eAndrew MK, Mitnitski AB, Rockwood K. Social vulnerability, frailty and mortality in elderly people. PLoS One. 2008 May 21;3(5):e2232.\u003c/li\u003e\n\u003cli\u003eFowler ME, Harmon C, Tucker A, Sharafeldin N, Oates G, Baker E, et al. The association between social vulnerability and geriatric assessment impairments among older adults with gastrointestinal cancers-The CARE Registry. Cancer. 2024 Sep 15;130(18):3188-97.\u003c/li\u003e\n\u003cli\u003eRockwood K. Frailty and aging medicine. Aging Med (Milton). 2019 Mar;2(1):4-6.\u003c/li\u003e\n\u003cli\u003eRockwood K, Howlett SE. Fifteen years of progress in understanding frailty and health in aging. BMC Med. 2018 Nov 27;16(1):220.\u003c/li\u003e\n\u003cli\u003eSkelly A, O\u0026apos;Donovan A. Recognizing Frailty in Radiation Oncology Clinical Practice: Current Evidence and Future Directions. Semin Radiat Oncol. 2022 Apr;32(2):115-24.\u003c/li\u003e\n\u003cli\u003eShe R, Vetrano DL, Leung MKW, Jiang H, Qiu C. Differential interplay between multimorbidity patterns and frailty and their mutual mediation effect on mortality in old age. J Nutr Health Aging. 2024 Aug;28(8):100305.\u003c/li\u003e\n\u003cli\u003ePrigerson HG, Bao Y, Shah MA, Paulk ME, LeBlanc TW, Schneider BJ, et al. Chemotherapy Use, Performance Status, and Quality of Life at the End of Life. JAMA Oncol. 2015 Sep;1(6):778-84.\u003c/li\u003e\n\u003cli\u003eScott JM, Stene G, Edvardsen E, Jones LW. Performance Status in Cancer: Not Broken, But Time for an Upgrade? J Clin Oncol. 2020 Sep 1;38(25):2824-9.\u003c/li\u003e\n\u003cli\u003eAzami-Aghdash S, Pournaghi-Azar F, Moosavi A, Mohseni M, Derakhshani N, Kalajahi RA. Oral Health and Related Quality of Life in Older People: A Systematic Review and Meta-Analysis. Iran J Public Health. 2021 Apr;50(4):689-700.\u003c/li\u003e\n\u003cli\u003eAzam F, Latif MF, Farooq A, Tirmazy SH, AlShahrani S, Bashir S, et al. Performance Status Assessment by Using ECOG (Eastern Cooperative Oncology Group) Score for Cancer Patients by Oncology Healthcare Professionals. Case Rep Oncol. 2019 Sep-Dec;12(3):728-36.\u003c/li\u003e\n\u003cli\u003eBroderick JM, Hussey J, Kennedy MJ, DM OD. Patients over 65 years are assigned lower ECOG PS scores than younger patients, although objectively measured physical activity is no different. J Geriatr Oncol. 2014 Jan;5(1):49-56.\u003c/li\u003e\n\u003cli\u003eWong R, Garc\u0026iacute;a-Pe\u0026ntilde;a C, Guti\u0026eacute;rrez-Robledo LM, Aguila E, Samper-Ternent R. 20 years of the Mexican Health and Aging Study. Salud Publica Mex2023.\u003c/li\u003e\n\u003cli\u003eWong R. MHAS, Mexican Health and Aging Study. www.MHASweb.org2017 [cited 2017 17/04/2017].\u003c/li\u003e\n\u003cli\u003eWong R, Michaels-Obregon A, Palloni A. Cohort Profile: The Mexican Health and Aging Study (MHAS). Int J Epidemiol. 2015 Jan 27.\u003c/li\u003e\n\u003cli\u003eOken MM, Creech RH, Tormey DC, Horton J, Davis TE, McFadden ET, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982 Dec;5(6):649-55.\u003c/li\u003e\n\u003cli\u003eTheou O, Haviva C, Wallace L, Searle SD, Rockwood K. How to construct a frailty index from an existing dataset in 10 steps. Age Ageing. 2023 Dec 1;52(12).\u003c/li\u003e\n\u003cli\u003eGarcia-Pena C, Avila-Funes JA, Dent E, Gutierrez-Robledo L, Perez-Zepeda M. Frailty prevalence and associated factors in the Mexican health and aging study: A comparison of the frailty index and the phenotype. Exp Gerontol. 2016 Jun 15;79:55-60.\u003c/li\u003e\n\u003cli\u003eAndrew MK, Keefe JM. Social vulnerability from a social ecology perspective: a cohort study of older adults from the National Population Health Survey of Canada. BMC Geriatr. 2014 Aug 16;14:90.\u003c/li\u003e\n\u003cli\u003eAndrew MK, Mitnitski A, Kirkland SA, Rockwood K. The impact of social vulnerability on the survival of the fittest older adults. Age Ageing. 2012 Mar;41(2):161-5.\u003c/li\u003e\n\u003cli\u003eMah JC, Theou O, Perez-Zepeda MU, Penwarden JL, Godin J, Rockwood K, et al. A standard procedure for constructing a multi-level social vulnerability index using CLSA and SOS data as working examples. PLoS One. 2024;19(12):e0315474.\u003c/li\u003e\n\u003cli\u003eMukamal KJ, Ding EL, Djousse L. Alcohol consumption, physical activity, and chronic disease risk factors: a population-based cross-sectional survey. BMC Public Health. 2006 May 3;6:118.\u003c/li\u003e\n\u003cli\u003eAssayag J, Kim C, Chu H, Webster J. The prognostic value of Eastern Cooperative Oncology Group performance status on overall survival among patients with metastatic prostate cancer: a systematic review and meta-analysis. Front Oncol. 2023;13:1194718.\u003c/li\u003e\n\u003cli\u003eMeyers DE, Pasternak M, Dolter S, Grosjean HAI, Lim CA, Stukalin I, et al. Impact of Performance Status on Survival Outcomes and Health Care Utilization in Patients With Advanced NSCLC Treated With Immune Checkpoint Inhibitors. JTO Clin Res Rep. 2023 Apr;4(4):100482.\u003c/li\u003e\n\u003cli\u003eHess LM, Smith D, Cui ZL, Montejano L, Liepa AM, Schelman W, et al. The relationship between Eastern Cooperative Oncology Group performance status and healthcare resource utilization among patients with advanced or metastatic colorectal, lung or gastric cancer. J Drug Assess. 2020 Dec 16;10(1):10-7.\u003c/li\u003e\n\u003cli\u003eMohile SG, Epstein RM, Hurria A, Heckler CE, Canin B, Culakova E, et al. Communication With Older Patients With Cancer Using Geriatric Assessment: A Cluster-Randomized Clinical Trial From the National Cancer Institute Community Oncology Research Program. JAMA Oncol. 2020 Feb 1;6(2):196-204.\u003c/li\u003e\n\u003cli\u003eGoede V. Frailty and Cancer: Current Perspectives on Assessment and Monitoring. Clin Interv Aging. 2023;18:505-21.\u003c/li\u003e\n\u003cli\u003eDale W, Klepin HD, Williams GR, Alibhai SMH, Bergerot C, Brintzenhofeszoc K, et al. Practical Assessment and Management of Vulnerabilities in Older Patients Receiving Systemic Cancer Therapy: ASCO Guideline Update. J Clin Oncol. 2023 Sep 10;41(26):4293-312.\u003c/li\u003e\n\u003cli\u003eHormigo-Sanchez AI, Lopez-Garcia A, Mahillo-Fernandez I, Askari E, Morillo D, Perez-Saez MA, et al. Frailty assessment to individualize treatment in older patients with lymphoma. Eur Geriatr Med. 2023 Dec;14(6):1393-402.\u003c/li\u003e\n\u003cli\u003eLi D, Sun CL, Kim H, Soto-Perez-de-Celis E, Chung V, Koczywas M, et al. Geriatric Assessment-Driven Intervention (GAIN) on Chemotherapy-Related Toxic Effects in Older Adults With Cancer: A Randomized Clinical Trial. JAMA Oncol. 2021 Nov 1;7(11):e214158.\u003c/li\u003e\n\u003cli\u003eWilliams GR, Weaver KE, Lesser GJ, Dressler E, Winkfield KM, Neuman HB, et al. Capacity to Provide Geriatric Specialty Care for Older Adults in Community Oncology Practices. Oncologist. 2020 Dec;25(12):1032-8.\u003c/li\u003e\n\u003cli\u003eOrtland I, Mendel Ott M, Kowar M, Sippel C, Jaehde U, Jacobs AH, et al. Comparing the performance of the CARG and the CRASH score for predicting toxicity in older patients with cancer. J Geriatr Oncol. 2020 Jul;11(6):997-1005.\u003c/li\u003e\n\u003cli\u003eDyas AR, Carmichael H, Bronsert MR, Stuart CM, Garofalo DM, Henderson WG, et al. Social vulnerability is associated with higher risk-adjusted rates of postoperative complications in a broad surgical population. Am J Surg. 2024 Mar;229:26-33.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Descriptive statistics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"888\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003eDead\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003eAlive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003eAge, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e70.9 (0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e66.6 (0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003eFemale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e66 (66.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e168 (53.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003ePhysical activity, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e12 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e60 (26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003eFrailty index, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e0.339 (0.153)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e0.351 (0.011)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003eSocial vulnerability index, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e0.469 (0.106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e0.436 (0.109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003eDays in bed, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e23 (47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e7.3 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003ePhysical function score, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e3.6 (3.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e2.5 (2.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003eSmoking status, n (%)\u003c/p\u003e\n \u003cp\u003eNever smoked\u003c/p\u003e\n \u003cp\u003eSmoked in the past\u003c/p\u003e\n \u003cp\u003eCurrently smokes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e69 (56.10)\u003c/p\u003e\n \u003cp\u003e39 (31.71)\u003c/p\u003e\n \u003cp\u003e15 (12.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e157 (62.55)\u003c/p\u003e\n \u003cp\u003e75 (29.88)\u003c/p\u003e\n \u003cp\u003e19 (7.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003eAlcohol intake status*, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e9 (7.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e23 (9.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e0.549\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8604%;\"\u003e\n \u003cp\u003ePerformance status categories, n (%)\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 (0.81)\u003c/p\u003e\n \u003cp\u003e3 (2.44)\u003c/p\u003e\n \u003cp\u003e26 (21.14)\u003c/p\u003e\n \u003cp\u003e32 (26.02)\u003c/p\u003e\n \u003cp\u003e61 (49.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.991%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (4.38)\u003c/p\u003e\n \u003cp\u003e20 (7.97)\u003c/p\u003e\n \u003cp\u003e71 (28.29)\u003c/p\u003e\n \u003cp\u003e89 (35.46)\u003c/p\u003e\n \u003cp\u003e60 (23.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2838%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u0026ge;2 drinks a day for women, \u0026ge;3 drinks a day for men\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eCox regression models\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"888\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eLow frailty levels, HR (CI 95%, p value)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eHigh frailty levels, HR (CI 95%, p value)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e1.02 (0.98-1.06, 0.373)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e1.04 (1.00-1.07, 0.039)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e0.62 (0.28-1.36, 0.223)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e0.56 (0.35-1.35, 0.281)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSocial vulnerability index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e234.79 (4.51-12,222.8, 0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e0.56 (0.04-8.39, 0.678)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSmoking status\u003c/p\u003e\n \u003cp\u003eNever smoked\u003c/p\u003e\n \u003cp\u003eSmoked in the past\u003c/p\u003e\n \u003cp\u003eCurrently smokes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.21 (0.52-2.85, 0.664)\u003c/p\u003e\n \u003cp\u003e1.60 (0.41-6.28, 0.498)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.95 (0.49-1.83, 0.864)\u003c/p\u003e\n \u003cp\u003e0.86 (0.33-2.35, 0.807)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eAlcohol intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e0.66 (0.18-2.44, 0.538)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e1.86 (0.51-6.81, 0.347)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003ePerformance status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003e0 and 1 levels reference groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e5.46 (1.24-24.04, 0.025)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e0.52 (0.08-3.28, 0.490)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e3.98 (0.84-18.73, 0.081)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e1.15 (0.25-5.25, 0.855)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e8.01 (1.50-42.66, 0.015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e3.13 (0.73-13.47, 0.126)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Days in bed, performance status, cancer, older adults, frailty.","lastPublishedDoi":"10.21203/rs.3.rs-6285336/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6285336/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eBackground.\u003c/em\u003e Cancer treatments are not a one-size-fits-all approach, treatment options are rarely studied in aging individuals, leading to worse outcomes related to increased vulnerability in this group of patients.\u003c/p\u003e \u003cp\u003e \u003cem\u003eAims.\u003c/em\u003e Since frailty has shown the ability to modify outcomes, our study aims to assess if frailty modifies the association between performance status and days in bed with mortality risk in older adults with cancer.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMethods.\u003c/em\u003e Our study is a secondary analysis of the Mexican Health and Aging Study, a cohort with a representative sample of individuals aged 50 years or older, with a baseline assessment in 2001 and follow-up data available for the years 2003, 2012, 2015, 2018 and 2021. We extracted the baseline variables from the main questionnaires, and the next-of-kin questionnaires were employed for information regarding mortality. We used Cox regression and Kaplan‒Meier curves for survival analysis.\u003c/p\u003e \u003cp\u003e \u003cem\u003eResults.\u003c/em\u003e Our sample was composed of 318 individuals, with a mean age of 68.02 years (\u0026plusmn;\u0026thinsp;SD 10.78), and 62.57% were women. Cox regression revealed that age was a significant risk factor for mortality in frail patients but not in those with low frailty levels.\u003c/p\u003e \u003cp\u003e \u003cem\u003eDiscussion.\u003c/em\u003e in settings where access to a geriatric assessment is limited or would significantly delay cancer-specific therapies, assessing frailty might improve the accuracy of those available cancer prognostic tools that might underperform in frail older adults.\u003c/p\u003e \u003cp\u003eConclusions. Frailty evaluation improves the assessment of older adults living with cancer.\u003c/p\u003e","manuscriptTitle":"Does frailty modulate the predictive value of performance status in older adults living with cancer?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-15 00:16:18","doi":"10.21203/rs.3.rs-6285336/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-01T14:44:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-28T12:52:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139876822237188029692473049345499483911","date":"2025-06-19T15:35:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-17T12:41:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"158230298356291869649602987760263070970","date":"2025-03-27T18:42:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-26T18:06:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-24T14:07:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-23T08:49:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aging Clinical and Experimental Research","date":"2025-03-22T19:54:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"fca404a8-1afa-4de8-b25b-5c8652f40804","owner":[],"postedDate":"April 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-03T16:04:57+00:00","versionOfRecord":{"articleIdentity":"rs-6285336","link":"https://doi.org/10.1007/s40520-025-03203-4","journal":{"identity":"aging-clinical-and-experimental-research","isVorOnly":false,"title":"Aging Clinical and Experimental Research"},"publishedOn":"2025-10-30 15:57:11","publishedOnDateReadable":"October 30th, 2025"},"versionCreatedAt":"2025-04-15 00:16:18","video":"","vorDoi":"10.1007/s40520-025-03203-4","vorDoiUrl":"https://doi.org/10.1007/s40520-025-03203-4","workflowStages":[]},"version":"v1","identity":"rs-6285336","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6285336","identity":"rs-6285336","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}