Cancer mortality and competing causes of death in older adults with cancer: A prospective, multicentre cohort study (ELCAPA-19).

BACKGROUND: In older patients with cancer, comorbidities compete with cancer for cause of death. The objectives were to evaluate cancer mortality and factors associated, according to metastatic status. METHODS: Between 2007 and 2014, patients with cancer aged ≥70 referred for pre-therapeutic geriatric assessment (GA) were included through the ELCAPA prospective cohort study. The underlying cause of death was defined according to the International Classification of Diseases, 10th Revision. The World Health Organisation definition was used to categorise the cause of death as cancer versus another disease (e.g. cardiovascular disease, infectious disease, etc.) Competing risk models were used. RESULTS: Mean (SD) age of the 1445 included patients was 80.2 (5.8) and 48% were women. Most common tumour sites were colorectal (19%), breast (17%) and urinary (15%); 773 patients (49%) had metastases. After a 34-month median follow-up, 706 cancer deaths were observed among 843 deaths. The 6-month and 3-year cancer mortality rates (95% CI) were 12% (9-15) and 34% (29-38) for non-metastatic patients and 43% (39-47) and 79% (75-82) for metastatic patients, respectively. Dependency in activities of daily living and comorbidities were associated with 6-month and 3-year cancer mortality in non-metastatic (adjusted subhazard ratio [aSHR] = 1.68 [0.99-2.85] and 1.69 [1.16-2.45]; and 1.98 [1.08-3.63] and 3.38 [1.47-7.76], respectively) and metastatic patients (aSHR = 2.81 [2.01-3.93] and 2.95 [2.14-4.07]; and 1.63 [1.18-2.25] and 2.06 [1.39-3.05], respectively). Impaired Timed-Get-Up-and-Go test was associated with 6-month and 3-year cancer mortality in metastatic patients (aSHR = 1.5 [1.06-2.12] and 1.38 [1.06-1.81], respectively). Obesity was negatively associated with 3-year cancer death in non-metastatic (aSHR = 0.53 [0.29-0.97]) and metastatic patients (aSHR = 0.71 [0.51-1.00]). CONCLUSIONS: The majority of older adults with cancer referred for pre-therapeutic GA die from cancer. Geriatric parameters are independently associated with cancer mortality and should be considered for prognosis assessment, decision-making and care.

Energy expenditure profiles and the risk of early limiting toxicity in older patients with cancer: The ELCAPA-25 prospective cohort survey.

BACKGROUND & AIMS: Predicting the risk of early limiting toxicity (ELT) is major challenge for the clinician seeking an effective, safe treatment for older patients with cancer. The Cancer and Aging Research Group (CARG) and CRASH (Chemotherapy Risk Assessment Scale for High-Age Patients) toxicity scores were designed to predict chemotherapy-related toxicity. Elevated resting energy expenditure (REE) may predispose to cachexia and increase ELT and mortality in older patients with cancer. The primary objective was to assess the association between elevated REE and ELT in older patients with cancer. The secondary objectives were to assess the discriminant ability of a predictive model including REE (relative to the CARG and CRASH scores) and the prognostic value of elevated REE. METHODS: We assessed patients aged 70 or over included in the prospective ELCAPA cohort between 2014 and 2018. The inclusion criteria were a solid tumour, a measurement of REE at baseline (mREE, by indirect calorimetry), and a geriatric assessment prior to cancer treatment in a teaching hospital (Paris, France). The mREE was compared with the predicted REE (pREE), as defined by the Harris-Benedict equation. Depending on the mREE/pREE ratio, study participants were classified as hypermetabolic, hypometabolic or normometabolic. The primary endpoint was 3-month ELT, defined as any unplanned hospitalization or any event leading to dose reduction, a treatment delay of more than 7 days, or treatment discontinuation within 3 months of initiation. The secondary endpoint was the 3-month mortality rate. RESULTS: A total of 179 patients were included. The median age was 80 [interquartile range: 76-84] years, 37% of the patients were female, 81.8% had metastatic disease, 67.6% received chemotherapy, 20.7% received hormone therapy, and 11.7% received targeted therapies. According to the mREE/pREE ratio, 85 patients (47%) were hypermetabolic, 63 (35%) were normometabolic, and 31 (18%) were hypometabolic. Sixty patients (33.5%; 95% confidence interval (CI): 26.7-40.9) experienced ELT. The discriminant ability (as assessed by the C-index) of a multivariate model including REE and adjustment factors was 0.82 [95%CI: 0.73-0.91]. In comparison, the discriminant ability of the CARG and CRASH models was 0.57 [0.45-0.68] and 0.51 [0.40-0.62], respectively. In our model, hypermetabolism was an independent risk factor for ELT (adjusted odds ratio = 2.44; 95%CI: 1.02-5.80). Other risk factors were the cancer type and stage, the treatment protocol, a clinical diagnosis of depression, the presence of grade 3 or 4 comorbidities, and the serum lactate dehydrogenase level. CONCLUSION: Hypermetabolism status is an independent predictor of ELT in older patients with cancer, relative to normometabolic status. Baseline REE measurement might improve the ELT risk assessment and decision-making process.