Prognostic value of the veterans affairs frailty index in older patients with non-small cell lung cancer

The performance status gap in immunotherapy for frail patients with advanced non-small cell lung cancer

PURPOSE

In advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitor (ICI) monotherapy is often preferred over intensive ICI treatment for frail patients and those with poor performance status (PS). Among those with poor PS, the additional effect of frailty on treatment selection and mortality is unknown.

METHODS

Patients in the veterans affairs national precision oncology program from 1/2019-12/2021 who received first-line ICI for advanced NSCLC were followed until death or study end 6/2022. Association of an electronic frailty index with treatment selection was examined using logistic regression stratified by PS. We also examined overall survival (OS) on intensive treatment using Cox regression stratified by PS. Intensive treatment was defined as concurrent use of platinum-doublet chemotherapy and/or dual checkpoint blockade and non-intensive as ICI monotherapy.

RESULTS

Of 1547 patients receiving any ICI, 66.2% were frail, 33.8% had poor PS (≥ 2), and 25.8% were both. Frail patients received less intensive treatment than non-frail patients in both PS subgroups (Good PS: odds ratio [OR] 0.67, 95% confidence interval [CI] 0.51 - 0.88; Poor PS: OR 0.69, 95% CI 0.44 - 1.10). Among 731 patients receiving intensive treatment, frailty was associated with lower OS for those with good PS (hazard ratio [HR] 1.53, 95% CI 1.2 - 1.96), but no association was observed with poor PS (HR 1.03, 95% CI 0.67 - 1.58).

CONCLUSION

Frail patients with both good and poor PS received less intensive treatment. However, frailty has a limited effect on survival among those with poor PS. These findings suggest that PS, not frailty, drives survival on intensive treatment.

Role of frailty in predicting prognosis of older patients with lung cancer: An updated systematic review and meta-analysis

INTRODUCTION

Frailty is a syndrome affecting primarily older adults that can impact disease course, treatment, and outcomes in patients with lung cancer (LC). We systematically reviewed current data on the correlation between frailty and overall survival (OS), recurrence-free survival (RFS), and the risk of complications in older patients with LC.

MATERIALS AND METHODS

PubMed, EMBASE, and Scopus databases were searched for observational cohort, cross-sectional, and case-control studies involving participants aged 18 years or older diagnosed with LC. Eligible studies were required to perform frailty assessments and have non-frail participants as a comparator group. Random-effects models were used for analysis, and the reported effect sizes were represented as hazards ratio (HR) or odds ratios (OR) with associated 95% confidence intervals (CI).

RESULTS

Seventeen studies were included, most with a retrospective cohort design (n = 16) and patients with non-small cell lung carcinoma (NSCLC). Older patients with LC and frailty had lower OS (HR 1.70, 95% CI: 1.39, 2.07) and RFS (HR 2.50, 95% CI: 1.02, 6.12), compared to non-frail subjects. Frail subjects also had increased risk of complications (OR 1.89, 95% CI: 1.42, 2.53).

DISCUSSION

The observed association between frailty and OS, RFS, and an increased susceptibility to complications emphasizes the potential significance of frailty status as a substantial prognostic indicator. Our results underscore the vital role of including frailty assessment as an integral element within the management plan for patients dealing with lung cancer.

The Association of Frailty and Neighborhood Disadvantage with Emergency Department Visits and Hospitalizations in Older Adults

BACKGROUND

Risk stratification and population management strategies are critical for providing effective and equitable care for the growing population of older adults in the USA. Both frailty and neighborhood disadvantage are constructs that independently identify populations with higher healthcare utilization and risk of adverse outcomes.

OBJECTIVE

To examine the joint association of these factors on acute healthcare utilization using two pragmatic measures based on structured data available in the electronic health record (EHR).

DESIGN

In this retrospective observational study, we used EHR data to identify patients aged ≥ 65 years at Atrium Health Wake Forest Baptist on January 1, 2019, who were attributed to affiliated Accountable Care Organizations. Frailty was categorized through an EHR-derived electronic Frailty Index (eFI), while neighborhood disadvantage was quantified through linkage to the area deprivation index (ADI). We used a recurrent time-to-event model within a Cox proportional hazards framework to examine the joint association of eFI and ADI categories with healthcare utilization comprising emergency visits, observation stays, and inpatient hospitalizations over one year of follow-up.

KEY RESULTS

We identified a cohort of 47,566 older adults (median age = 73, 60% female, 12% Black). There was an interaction between frailty and area disadvantage (P = 0.023). Each factor was associated with utilization across categories of the other. The magnitude of frailty's association was larger than living in a disadvantaged area. The highest-risk group comprised frail adults living in areas of high disadvantage (HR 3.23, 95% CI 2.99-3.49; P < 0.001). We observed additive effects between frailty and living in areas of mid- (RERI 0.29; 95% CI 0.13-0.45; P < 0.001) and high (RERI 0.62, 95% CI 0.41-0.83; P < 0.001) neighborhood disadvantage.

CONCLUSIONS

Considering both frailty and neighborhood disadvantage may assist healthcare organizations in effectively risk-stratifying vulnerable older adults and informing population management strategies. These constructs can be readily assessed at-scale using routinely collected structured EHR data.

Baseline correlates of frailty and its association with survival in United States veterans with acute myeloid leukemia

Frailty is an important construct to measure in acute myeloid leukemia (AML). We used the Veterans Affairs Frailty Index (VA-FI) - calculated using readily available data within the VA's electronic health records - to measure frailty in U.S. veterans with AML. Of the 1166 newly diagnosed and treated veterans with AML between 2012 and 2022, 722 (62%) veterans with AML were classified as frail (VA-FI > 0.2). At a median follow-up of 252.5 days, moderate-severely frail veterans had significantly worse survival than mildly frail, and non-frail veterans (median survival 179 vs. 306 vs. 417 days, p < .001). Increasing VA-FI severity was associated with higher mortality. A model with VA-FI in addition to the European LeukemiaNet (ELN) risk classification and other covariates statistically outperformed a model containing the ELN risk and other covariates alone (p < .001). These findings support the VA-FI as a tool to expand frailty measurement in research and clinical practice for informing prognosis in veterans with AML.

Assessment of an embedded primary care-derived electronic health record (EHR) frailty index (eFI) in older adults with acute myeloid leukemia

INTRODUCTION

Assessing frailty is integral to treatment decision-making for older adults with acute myeloid leukemia (AML). Prior electronic frailty indices (eFI) derive from an accumulated-deficit model and are associated with mortality in older primary care populations. We evaluated use of an embedded eFI in AML by describing baseline eFI categories by treatment type and exploring associations between eFI categories, survival, and treatment received.

MATERIALS AND METHODS

This was a retrospective study of subjects ≥60 years old with new AML treated at an academic medical center from 1/2018-10/2020. The eFI requires ≥2 ambulatory visits over two years and uses demographics, vitals, ICD-10 codes, outpatient labs, and available functional information from Medicare Annual Wellness Visits. Frailty was defined as fit (eFI ≤ 0.10), pre-frail (0.10 < eFI ≤ 0.21), and frail (eFI > 0.21). Chemotherapy was intensive (anthracycline-based) or less-intensive (hypomethylating agent, low dose cytarabine +/- venetoclax). Therapy type, pre-treatment characteristics, and chemotherapy cycles were compared by eFI category using chi-square and Fisher's exact tests and ANOVA. Median survival was compared by eFI category using log-rank tests stratified by therapy type.

RESULTS

Among 166 older adults treated for AML (mean age 74 years, 61% male, 85% Caucasian), only 79 (48%) had a calculable eFI score before treatment. Of these, baseline eFI category was associated with treatment received (fit (n = 31): 68% intensive, 32% less intensive; pre-frail (n = 38): 37% intensive, 63% less intensive; frail (n = 10): 0% intensive, 100% less intensive; not calculable (n = 87): 48% intensive, 52% less-intensive; p < 0.01). The prevalence of congestive heart failure and secondary AML differed by frailty status (p < 0.01). Median survival did not differ between eFI categories for intensively (p = 0.48) or less-intensively (p = 0.09) treated patients. For those with less-intensive therapy who lived ≥6 months, eFI category was not associated with the number of chemotherapy cycles received (p = 0.97). The main reason for an incalculable eFI was a lack of outpatient visits in our health system prior to AML diagnosis.

DISCUSSION

A primary care-derived eFI was incalculable for half of older adults with AML at an academic medical center. Frailty was associated with chemotherapy intensity but not survival or treatment duration. Next steps include testing adaptations of the eFI to the AML setting.

How frail is frail in oncology studies? A scoping review

AIMS

The frailty index (FI) is one way in which frailty can be quantified. While it is measured as a continuous variable, various cut-off points have been used to categorise older adults as frail or non-frail, and these have largely been validated in the acute care or community settings for older adults without cancer. This review aimed to explore which FI categories have been applied to older adults with cancer and to determine why these categories were selected by study authors.

METHODS

This scoping review searched Medline, EMBASE, Cochrane, CINAHL, and Web of Science databases for studies which measured and categorised an FI in adults with cancer. Of the 1994 screened, 41 were eligible for inclusion. Data including oncological setting, FI categories, and the references or rationale for categorisation were extracted and analysed.

RESULTS

The FI score used to categorise participants as frail ranged from 0.06 to 0.35, with 0.35 being the most frequently used, followed by 0.25 and 0.20. The rationale for FI categories was provided in most studies but was not always relevant. Three of the included studies using an FI > 0.35 to define frailty were frequently referenced as the rationale for subsequent studies, however, the original rationale for this categorisation was unclear. Few studies sought to determine or validate optimum FI categorises in this population.

CONCLUSION

There is significant variability in how studies have categorised the FI in older adults with cancer. An FI ≥ 0.35 to categorise frailty was used most frequently, however an FI in this range has often represented at least moderate to severe frailty in other highly-cited studies. These findings contrast with a scoping review of highly-cited studies categorising FI in older adults without cancer, where an FI ≥ 0.25 was most common. Maintaining the FI as a continuous variable is likely to be beneficial until further validation studies determine optimum FI categories in this population. Differences in how the FI has been categorised, and indeed how older adults have been labelled as 'frail', limits our ability to synthesise results and to understand the impact of frailty in cancer care.