Assessing frailty in older Indian patients before cancer treatment: Comparative analysis of three scales and their implications for overall survival

INTRODUCTION

Frailty, characterized by ageing-related vulnerability, influences outcomes in older adults. Our study aimed to investigate the relationship between frailty and clinical outcomes in older Indian patients with cancer.

MATERIALS AND METHODS

Our observational single-centre study, conducted at Tata Memorial Hospital from February 2020 to July 2022, enrolled participants aged 60 years and above with cancer. Frailty was assessed using the Clinical Frailty Scale (CFS), G8, and Vulnerable Elders Survey (VES)-13. The primary objective was to explore the correlation between baseline frailty and overall survival. Statistical analyses include Kaplan-Meier, Cox proportional hazards, and Harrell's C test.

RESULTS

A total of 1,177 patients (median age 68, 76.9% male) were evaluated in the geriatric oncology clinic. Common malignancies included lung (40.0%), gastrointestinal (35.8%), urological (11.9%), and head and neck (9.0%), with 56.5% having metastatic disease. Using CFS, G8, and VES-13 scales, 28.5%, 86.4%, and 38.0% were identified as frail, respectively. Median follow-up was 11.6 months, with 43.3% deaths. Patients fit on CFS (CFS 1-2) had a median survival of 28.02 months, pre-frail (CFS 3-4) 13.24 months, and frail (CFS ≥5) 7.79 months (p < 0.001). Abnormal G8 (≤14) and VES-13 (≥3) were associated with significantly lower median survival (p < 0.001). Multivariate analysis confirmed CFS's predictive power for mortality (p < 0.001), with hazard ratios [HRs] for pre-frail at 1.61(95% confidence interval [CI] 1.25 to 2.06) and frail at 2.31 (95%CI 1.74 to 3.05). G8 ≤ 14 had HR 2.00 (95%CI 1.42 to 2.83), and abnormal VES-13 had HR 1.36 (95%CI 1.11-1.67). In the likelihood ratio test, CFS significantly improved the model fit (p < 0.001). Harrell's C index for survival prediction was 0.62 for CFS, 0.54 for G8, and 0.58 for VES-13.

DISCUSSION

In conclusion, our study highlights varying frailty prevalence and prognostic implications in older Indian patients with cancer, emphasizing the need for personalized care in oncology for this aging population. We would recommend using CFS as a tool to screen for frailty for older Indian patients with cancer.

Correlation of the Geriatric Assessment with Overall Survival in Older Patients with Cancer

AIMS

Global guidelines recommend that all older patients with cancer receiving chemotherapy should undergo a geriatric assessment. However, utilisation of the geriatric assessment is often constrained by its time-intensive nature, which limits its adoption in settings with limited resources and high demand. There is a lack of evidence correlating the results of the geriatric assessment with survival from the Indian subcontinent. Therefore, the aims of the present study were to assess the impact of the geriatric assessment on survival in older Indian patients with cancer and to identify the factors associated with survival in these older patients.

MATERIALS AND METHODS

This was an observational study, conducted in the geriatric oncology clinic of the Tata Memorial Hospital (Mumbai, India). Patients aged 60 years and older with cancer who underwent a geriatric assessment were enrolled. We assessed the non-oncological geriatric domains of function and falls, nutrition, comorbidities, cognition, psychology, social support and medications. Patients exhibiting impairment in two or more domains were classified as frail.

RESULTS

Between June 2018 and January 2022, we enrolled 897 patients. The median age was 69 (interquartile range 65-73) years. The common malignancies were lung (40.5%), oesophagus (31.9%) and genitourinary (12.1%); 54.6% had metastatic disease. Based on the results of the geriatric assessment, 767 (85.4%) patients were frail. The estimated median overall survival in fit patients was 24.3 (95% confidence interval 18.2-not reached) months, compared with 11.2 (10.1-12.8) months in frail patients (hazard ratio 0.54; 95% confidence interval 0.41-0.72, P < 0.001). This difference in overall survival remained significant after adjusting for age, sex, primary tumour and metastatic status (hazard ratio 0.56; 95% confidence interval 0.41-0.74, P < 0.001). In the patients with a performance status of 0 or 1 (n = 454), 365 (80.4%) were frail; the median overall survival in the performance status 0-1 group was 33.0 months (95% confidence interval 24.31-not reached) in the fit group versus 14.4 months (95% confidence interval 12.25-18.73) in the frail patients (hazard ratio 0.50; 95% confidence interval 0.34-0.74, P = 0.001). In the multivariate analysis, the geriatric assessment domains that were predictive of survival were function (hazard ratio 0.68; 95% confidence interval 0.52-0.88; P = 0.003), nutrition (hazard ratio 0.64; 95% confidence interval 0.48-0.85, P = 0.002) and cognition (hazard ratio 0.67; 95% confidence interval 0.49-0.91, P = 0.011).

DISCUSSION

The geriatric assessment is a powerful prognostic tool for survival among older Indian patients with cancer. The geriatric assessment is prognostic even in the cohort of patients thought to be the fittest, i.e. performance status 0 and 1. Our study re-emphasises the critical importance of the geriatric assessment in all older patients planned for cancer-directed therapy.

The current status of geriatric oncology in India

Geriatric oncology in India is relatively new. The number of older persons with cancer is increasing exponentially; at our institution, 34% of patients registered are 60 years and over. Apart from the Tata Memorial Hospital in Mumbai, there are currently no other Indian centers that have a dedicated geriatric oncology unit. Geriatric assessments (GAs) are done sporadically, and older patients with cancer are usually assessed and treated based on clinical judgement. Challenges to increasing the uptake of GA include a lack of training/time/interest or knowledge of the importance of the GA. Other challenges include a lack of trained personnel with expertise in geriatric oncology, and a paucity of research studies that seek to advance the outcomes in older Indian patients with cancer. We anticipate that over the next 10 years, along with the inevitable increase in the number of older persons with cancer in India, there will be a commensurate increase in the number of skilled personnel to care for them. Key goals for the future include increased research output, increased number of dedicated geriatric oncology units across the country, India-specific geriatric oncology guidelines, geriatric oncology training programs, and a focus on collaborative work across India and with global partners. In this narrative review, we provide a broad overview of the status of geriatric oncology in India, along with a description of the work done at our center. We hope to spark interest and provide inspiration to readers to consider developing geriatric oncology services in other settings.

Validation of the Onco-MPI in predicting short-term mortality in older Indian patients with cancer

INTRODUCTION

The number of older patients with cancer is increasing exponentially worldwide, and a similar trend has also been noted in India. The Multidimensional Prognostic Index (MPI) strongly correlates the presence of individual comorbidities with mortality, and the Onco-MPI prognosticates patients accurately for overall mortality. However, limited studies have evaluated this index in patient populations beyond Italy. We evaluated the performance of the Onco-MPI index in predicting mortality in older Indian patients with cancer.

MATERIALS AND METHODS

This observational study was conducted between October 2019 and November 2021 in the Geriatric Oncology Clinic at Tata Memorial Hospital in Mumbai, India. The data of patients aged ≥60 years with solid tumors who underwent a comprehensive geriatric assessment was analysed. The study's primary aim was to calculate the Onco-MPI for patients in the study and correlate it with one-year mortality.

RESULTS

A total of 576 patients aged ≥60 years were included in the study. The median age (range) of the population was 68 (60-90) years, and 429 (74.5%) were male. After a median follow-up of 19.2 months, 366 (63.7%) patients had died. The proportion of patients classified as low risk (0-0.46), moderate risk (0.47-0.63) and high risk (0.64-1.0) were 38% (219 patients), 37% (211 patients) and 25% (145 patients), respectively. There was a significant difference in one-year mortality rates between the low-risk patients compared to medium and high-risk patients (40.6% vs 53.1% vs 71.7%; p < 0.001).

DISCUSSION

The current study validates the Onco-MPI as a predictive tool for estimating short-term mortality in older Indian patients with cancer. Further prospective studies need to build on this index to obtain a score with greater discrimination in the Indian population.