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Background Automated frailty screening tools like the Hospital Frailty Risk Score (HFRS) are primarily validated for care consumption outcomes. We assessed the predictive ability of the HFRS regarding care consumption outcomes, frailty domain impairments and mortality among older adults with cancer, using the Geriatric 8 (G8) screening tool as a clinical benchmark. Methods This retrospective, linkage-based study included patients aged ≥70 years with solid tumor, enrolled in the Elderly Cancer Patients (ELCAPA) multicentre cohort study (2016–2020) and hospitalized in acute care within the Greater Paris University Hospitals. HFRS scores, which encompass hospital-acquired problems and frailty-related syndromes, were calculated using data from the index admission and the preceding 6 months. A multidomain geriatric assessment (GA), including cognition, nutrition, mood, functional status, mobility, comorbidities, polypharmacy, incontinence, and social environment, was conducted at ELCAPA inclusion, with computation of the G8 score. Logistic and Cox regressions measured associations between the G8, HFRS, altered GA domains, length of stay exceeding 10 days, 30-day readmission, and mortality. Results Among 587 patients included (median age 82 years, metastatic cancer 47.0%), 237 (40.4%) were at increased frailty risk by the HFRS (HFRS>5) and 261 (47.5%) by the G8 (G8≤10). Both HFRS and G8 were significantly associated with cognitive and functional impairments, incontinence, comorbidities, prolonged length of stay, and 30-day mortality. The G8 was associated with polypharmacy, nutritional and mood impairment. Discussion Although showing significant associations with short-term care consumption, the HFRS could not identify polypharmacy, nutritional, mood and social environment impairments and showed low discriminatory ability across all GA domains. [ABSTRACT FROM AUTHOR]

Background: The expression of depressive symptoms in older people with cancer is heterogeneous because of specific features of age or cancer comorbidity. We aimed to identify depressive symptom profiles in this population and describe the associated features including survival. Materials and Methods: Patients ≥70 years who were referred to geriatric oncology clinics were prospectively included in the ELCAPA study. In this subanalysis, depressive symptoms were used as indicators in a latent class analysis. Multinomial multivariable logistic regression and Cox models examined the association of each class with baseline characteristics and mortality. Results: For the 847 complete‐case patients included (median age, 79 years; interquartile range, 76–84; women, 47.9%), we identified five depressive symptom classes: "no depression/somatic only" (38.8%), "no depression/pauci‐symptomatic" (26.4%), "severe depression" (20%), "mild depression" (11.8%), and "demoralization" (3%). Compared with the no depression/pauci‐symptomatic class, the no depression/somatic only and severe depression classes were characterized by more frequent comorbidities with poorer functional status and higher levels of inflammation. "Severe" and "mild" depression classes also featured poorer nutritional status, more medications, and more frequent falls. Severe depression was associated with poor social support, inpatient status, and increased risk of mortality at 1 year (adjusted hazard ratio, 1.62, 95% confidence interval, 1.06–2.48) and 3 years (adjusted hazard ratio, 1.49; 95% confidence interval, 1.06–2.10). Conclusion: A data‐driven approach based on depressive symptoms identified five different depressive symptom profiles, including demoralization, in older patients with cancer. Severe depression was independently and substantially associated with poor survival. Implications for Practice: Older patients with cancer present with distinct profiles of depressive symptomatology, including different severity levels of depression and the demoralization syndrome. Clinicians should use a systematic assessment of depressive symptoms to adequately highlight these distinct profiles. Geriatric and oncological features are differently associated with these profiles. For instance, severe depression was associated with more frequent comorbidities with poorer functional, poor nutritional status, polypharmacy, frequent falls, inpatient status and poor social support. Also, severe depression was independently and substantially associated with poor survival so that the identification and management of depression should be considered a high priority in this population. The expression of depressive symptoms in older patients with cancer is complex, with greater heterogeneity than in younger patients. This article identifies different homogeneous classes of depressive symptoms that can assist in analyzing outcomes to avoid inconsistent interpretation of study results. [ABSTRACT FROM AUTHOR]

Background. A multidimensional geriatric assessment (GA) is recommended in older cancer patients to inventory health problems and tailor treatment decisions accordingly but requires considerable time and human resources. The G8 is among the most sensitive screening tools for selecting patients warranting a full GA but has limited specificity. We sought to develop and validate an optimized version of the G8. Patients and Methods. We used a prospective cohort of cancer patients aged ≥70 years referred to geriatricians for GA (2007-2012: n = 729 [training set]; 2012-2014: n = 414 [validation set]). Abnormal GA was defined as at least one impaired domain across seven validated tests. Multiple correspondence analysis, multivariate logistic regression, and bootstrapped internal validation were performed sequentially. Results. The final model included six independent predictors for abnormal GA: weight loss, cognition/mood, performance status, self-rated health status, polypharmacy (≥6 medications per day), and history of heart failure/coronary heart disease. For the original G8, sensitivity was 87.2% (95% confidence interval, 84.3-89.7), specificity 57.7% (47.3-67.7), and area under the receiver-operating characteristic curve (AUROC) 86.5% (83.5-89.6). The modified G8 had corresponding values of 89.2% (86.5-91.5), 79.0% (69.4-86.6), and 91.6% (89.3; 93.9), with higher AUROC values for all tumor sites and stable properties on the validation set. Conclusion. A modified G8 screening tool exhibited better diagnostic performance with greater uniformity across cancer sites and required only six items. If these features are confirmed in other settings, the modified tool may facilitate selection for a full GA in older patients with cancer. [ABSTRACT FROM AUTHOR]

Purpose: Establishing an accurate prognosis remains challenging in older patients with cancer because of the population's heterogeneity and the current predictive models' reduced ability to capture the complex interactions between oncologic and geriatric predictors. We aim to develop and externally validate a new predictive score (the Geriatric Cancer Scoring System [GCSS]) to refine individualized prognosis for older patients with cancer during the first year after a geriatric assessment (GA)., Materials and Methods: Data were collected from two French prospective multicenter cohorts of patients with cancer 70 years and older, referred for GA: ELCAPA (training set January 2007-March 2016) and ONCODAGE (validation set August 2008-March 2010). Candidate predictors included baseline oncologic and geriatric factors and routine biomarkers. We built predictive models using Cox regression, single decision tree (DT), and random survival forest (RSF) methods, comparing their predictive performance for 3-, 6-, and 12-month mortalities by computing time-dependent area under the receiver operator curve (tAUC)., Results: A total of 2,012 and 1,397 patients were included in the training and validation set, respectively (mean age: 81 ± 6 years/78 ± 5 years; women: 47%/70%; metastatic cancer: 50%/34%; 12-month mortality: 43%/16%). Tumor site/metastatic status, cancer treatment, weight loss, ≥five prescription drugs, impaired functional status and mobility, abnormal G-8 score, low creatinine clearance, and elevated C-reactive protein (CRP)/albumin were identified as relevant predictors in the Cox model. DT and RSF identified more complex combinations of features, with G-8 score, tumor site/metastatic status, and CRP/albumin ratio contributing most to the predictions. The RSF approach gave the highest tAUC (12 months: 0.87 [RSF], 0.82 [Cox], 0.82 [DT]) and was retained as the final model., Conclusion: The GCSS on the basis of a machine learning approach applied to two large French cohorts gave an accurate externally validated mortality prediction. The GCSS might improve decision making and counseling in older patients with cancer referred for pretherapeutic GA. GCSS's generalizability must now be confirmed in an international setting.

Background: The longitudinal hospital care experiences of older adults with cancer, from the treatment decision-making process until their end of life, remain unexplored. We examined the hospital care trajectories of these patients and identified associated clinical determinants., Materials and Methods: We linked the ELCAPA multicenter cohort study (patients aged ≥70 with a solid tumor and having been referred for a geriatric assessment between 2012 and 2019) and the Greater Paris University Hospitals' clinical data warehouse. Individual care trajectories, defined as series of consultations, hospital admissions (in day, acute, or rehabilitation units), and emergency room (ER) visits, were clustered using multichannel sequence analysis. Cluster membership determinants were identified among socio-demographic, oncological, and geriatric parameters by logistic regression analysis., Results: Seven hundred seven patients (median age: 82; metastatic cancer: 45.2%; 10 998 care episodes) were included. Four trajectory clusters were identified: cluster A (n = 149, 21.1%) with in-hospital surgical trajectories, cluster B (n = 198, 28.0%) with outpatient care trajectories with chemotherapy and/or radiotherapy, cluster C (n = 302, 42.7%) without any hospital cancer treatments, and cluster D (n = 58, 8.2%) with mostly chemotherapy and high hospital care consumption. Cluster belonging determinants included metastatic status and cancer site (for cluster A); cognition, mobility, and mood status (unimpaired parameters for cluster B and impaired for cluster C); and younger age (for cluster D)., Conclusions: While highlighting varied hospital care experiences among older patients with cancer, we found that age remains an independent determinant of chemotherapy-dominant care trajectories., (© The Author(s) 2024. Published by Oxford University Press.)