Comparing the association between multiple chronic conditions, multimorbidity, frailty, and survival among older patients with cancer

Association of early and late onset of chronic diseases with physical frailty among older Indian adults: study based on a population survey

BACKGROUND

There is a limited understanding of the age at onset of chronic diseases linked to an increased risk of physical frailty among older persons, despite the well-established link between chronic diseases and frailty. This study aimed to examine the prevalence of early- and late-onset chronic diseases and their association with physical frailty and its components in older adults in India.

METHODS

Data from the Longitudinal Aging Study in India (LASI), wave 1 (2017-2018), were used with a sample of 31,386 older adults aged 60 years and above, including 15,043 males and 16,343 females. Physical frailty was assessed by using an adapted version of the frailty phenotype developed by Fried et al.. The main explanatory variable was self-reported age at the onset of chronic diseases, and a cutoff of 50 years was considered to define the early and late onset of chronic disease. Multivariable logistic regression models were used to examine the association between early and late onset of chronic diseases and physical frailty and its components.

RESULTS

Overall, 30.65% of the sample population was physically frail, and frailty was much higher in the 80 years and aboveage group (54.23%). Compared to individuals without any morbidity, those with late onset of single morbidity (AOR: 1.22, CI: 1.09-1.36) and multimorbidity (AOR: 1.49, CI: 1.29-1.71) had higher odds of physical frailty. Similarly, multimorbidity was significantly associated with most components of physical frailty, with the exception of weight loss. Older adults with late-onset hypertension (AOR: 1.22, CI: 1.09-1.36), stroke (AOR: 1.75, CI: 1.35-2.27), and heart disease (AOR: 1.58, CI: 1.21-2.06) had higher odds of physical frailty than those without any morbidity. The odds of being physically frail were higher in those with early onset arthritis (AOR: 1.55, CI: 1.15-2.08) and late-onset of arthritis (AOR: 1.35, CI: 1.13-1.61) than in those without any morbidity. Additionally, the odds of physical frailty were higher among those with late-onset chronic diseases, particularly heart disease (AOR: 3.39, CI: 1.31-8.77) and psychiatric disease (AOR: 3.00, CI: 1.19-7.61), compared to individuals with early onset of these conditions.

CONCLUSIONS

This study found significant positive associations between early and late onset chronic diseases and physical frailty and its components among older Indians. These findings underscore the importance of managing late-onset chronic diseases, especially heart diseases and psychiatric conditions, to mitigate frailty in older adults. These findings also emphasize the critical role of age at onset of specific chronic conditions and multimorbidity in the development of frailty, suggesting that targeted disease-specific interventions could help delay or prevent frailty.

Optimal lung cancer care pathways: a Tasmanian perspective

Objective In Australia, Tasmania has the second highest rate of incident lung cancer cases at 44.0 per 100,000 population, with an overall 5year relative survival rate of 20%. The aim of this retrospective study was to map and compare patient transit timelines from referral, diagnosis and treatment, to national care quality indicators (NCQI) and optimal care pathway (OCP) benchmarks. Methods Data were extracted from the weekly lung cancer multidisciplinary team meeting minutes, digital medical records and the ARIA Oncology-Information System for newly diagnosed small cell and non-small cell lung cancer cases between 2019 and 2022, at a regional, university-affiliated tertiary hospital in Tasmania. Sociodemographic data and key dates were extracted, including first general practitioner (GP) referral, specialist appointments (respiratory, medical oncology, radiation oncology and cardiothoracic), investigations, diagnosis, staging and treatment of any intent. Timelines were benchmarked against NCQI and the OCP. Results A total of 165 cases were included; mean patient age was 72years, and 57% were male. A total of 153 patients (93%) were diagnosed with non-small cell cancer and 12 (7%) with small cell lung cancer. Results for all years showed that 93% of patients were seen by the respiratory service within 14days of their GP referral and 71% diagnosed within 28days of their referral, in accordance with current standards. The time taken between GP referrals and diagnosis to any treatment was greater than the required standards, with on average 7% of patients meeting the quality standards (range, 0-16%) for all treatment intents. Conclusion Current national benchmarks have proven challenging to achieve, with prolonged time to treatment of any intent. Challenges both at a patient and systemic level will need to be assessed to improve clinical indicator outcomes.

Trajectory Analysis of Healthcare Use Before and after Gastrointestinal Cancer Surgery

BACKGROUND

Frailty correlates with worse postoperative outcomes and higher surgical cost, but the long-term impact on healthcare use remains ill-defined. We sought to evaluate patterns of healthcare use pre- and postsurgery among patients with gastrointestinal cancer and characterize the association with frailty.

STUDY DESIGN

Data on patients who underwent surgical resection for liver, biliary, pancreatic, colon and rectal cancer were obtained from the SEER-Medicare database from 2005 to 2020. Frailty was assessed using the claims-based frailty index. Group-based trajectory modeling identified clusters of patients with discrete patterns of healthcare use. Multivariable regression was performed to predict cluster membership based on preoperative factors, including frailty.

RESULTS

Among 66,684 beneficiaries, 4 distinct use trajectories based on data from 12 months before and after surgical resection were identified. After a surge in use during the month of surgical resection, most patients reverted to presurgery baseline use (low: 6,588, 9.9%; moderate: 17,627, 26.4%; and high: 29,850, 44.8%). However, a notable trajectory involving 12,619 (18.9%) patients was identified, wherein surgical resection precipitated a transition from a "low" presurgery use state to a "high" use state postsurgery. Frail patients were more likely to be among those individuals who transitioned to high users (low: 4.2% vs transition: 12.6% vs high: 7.5%; p < 0.001). On multivariable analysis incorporating preoperative variables, frailty was associated with high group trajectory membership (ref: least and moderate; highest: odds ratio 4.90, 95% CI 4.49 to 5.35; p < 0.001).

CONCLUSIONS

Patients with gastrointestinal cancer demonstrated distinct clusters of healthcare use after surgical resection. Preoperative predictive models may help differentiate different healthcare use trajectories to help tailor care for patients in the postoperative period.

Prostate-specific antigen testing patterns and prostate cancer stage at diagnosis in older Ohio cancer patients

BACKGROUND

Prostate cancer (PCa) screening recommendations do not support prostate-specific antigen (PSA) screening for older men. Such screening often occurs, however. It is, therefore, important to understand how frequently and among which subgroups screening occurs, and the extent of distant stage PCa diagnoses among screened older men.

METHODS

Using the 2014-2016 linked Ohio Cancer Incidence Surveillance System (OCISS) and Medicare administrative database, we identified men 68 and older diagnosed with PCa and categorized their PSA testing in the three years preceding diagnosis as screening or diagnostic. We conducted multivariable logistic regression analysis to identify correlates of screening PSA and to determine whether screening PSA is independently associated with distant stage disease.

RESULTS

Our study population included 3034 patients (median age: 73 years). 62.1% of PCa patients underwent at least one screening-based PSA in the three years preceding diagnosis. Older age (75-84 years: aOR [95% CI]: 0.84 [0.71, 0.99], ≥ 85: aOR: 0.27 [0.19, 0.38]), and frailty (aOR: 0.51 [0.37, 0.71]) were associated with lower screening. Screening was associated with decreased odds of distant stage disease (aOR: 0.55 [0.42, 0.71]). However, older age (75-84 years: aOR: 2.43 [1.82, 3.25], ≥ 85: aOR: 10.57 [7.05, 15.85]), frailty (aOR: 5.00 [2.78, 9.31]), and being separated or divorced (aOR: 1.64 [1.01, 2.60]) were associated with increased distant stage PCa.

CONCLUSION

PSA screening in older men is common, though providers appear to curtail PSA screening as age and frailty increase. Screened older men are diagnosed at earlier stages, but the harms of screening cannot be assessed.

Optimizing Care Across the Continuum for Older Adults with Lung Cancer: A Review

Older adults with lung cancer experience inferior clinical outcomes compared to their younger counterparts. This review provides the scaffolding to address these disparities by delineating (1) the distinct and varied care needs of older adults with lung malignancies, (2) evidence-based measures for identifying subgroups within this population meriting tailored approaches to care, (3) age-specific considerations for the selection of cancer-directed therapy, and (4) opportunities for future work to enhance clinical outcomes and care delivery.

Prognostic value of three clinical nutrition scoring system (NRI, PNI, and CONUT) in elderly patients with prostate cancer

Background

Most of patients with prostate cancer (PCa) are elderly and have a long course of disease. Preoperative assessment of the patient's clinical nutritional status facilitates early intervention and improves patient prognosis.

Methods

We assessed the nutritional status of PCa patients utilizing the Nutritional Risk Index (NRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) scoring systems. Survival comparisons between groups were conducted using Kaplan-Meier curve analysis and log-rank tests, while Cox proportional hazards regression analysis was employed to identify independent prognostic factors. Furthermore, we implemented bootstrap-based optimism correction methods to validate the scoring systems and applied decision curve analysis to evaluate the non-inferiority of these three clinical nutrition scoring systems relative to the conventional American Joint Committee on Cancer (AJCC) staging.

Results

In this study, malnutrition was diagnosed in 31.51% of the patients using the NRI, 13.02% using the PNI, and 88.28% using the CONUT score. After adjusting for confounders, normal nutritional status as defined by NRI and PNI emerged as an independent prognostic factor for prostate-specific antigen progression-free survival (PSA-PFS). However, nutritional status assessed by CONUT inaccurately predicted PSA-PFS. Normal nutritional status, as determined by all three scoring systems, was found to be an independent prognostic factor for progression-free survival (PFS). Following adjustments for optimistic estimates, the C-index for NRI in predicting both PSA-PFS and PFS remained the highest among the three scoring systems. The results of the DCA indicated that the C-index of all three scoring systems was higher than that of AJCC stage.

Conclusions

NRI, PNI, and CONUT are convenient and clinically applicable scoring systems. A clinical malnutrition intervention may improve the prognosis of prostate cancer patients.

Specialist Palliative Care Use and End-of-Life Care in Patients With Metastatic Cancer

CONTEXT

For patients with advanced cancer, high intensity treatment at the end of life is measured as a reflection of the quality of care. Use of specialist palliative care has been promoted to improve care quality, but whether its use is associated with decreased treatment intensity on a population-level is unknown.

OBJECTIVES

To determine whether receipt of specialist palliative care use is associated with differences in end-of-life quality metrics in patients with metastatic cancer.

METHODS

Retrospective propensity-matched cohort of patients age ≥ 65 who died with metastatic cancer in U.S. hospitals with palliative care programs that participated in the National Palliative Care Registry in 2018-2019. Cox proportional hazards regression was used to assess the impact of specialist palliative care on use of chemotherapy in the last 14 days of life, use of intensive care unit (ICU) in the last 30 days of life, use of hospice, and hospice enrollment ≥ three days.

RESULTS

After 1:2 matching, our cohort consisted of 15,878 exposed and 31,756 unexposed patients. Receipt of specialist palliative care was associated with a decrease in use of chemotherapy (adjusted hazard ratio (aHR) 0.59 [0.50-0.70]) and ICU at the end of life (aHR 0.86 [0.80-0.92]), and an increase in hospice use (aHR 1.92 [1.85-1.99]) and hospice enrollment for ≥three days (aHR 2.00 [1.93-2.07]).

CONCLUSION

On a population-level, use of specialist palliative care was associated with improved metrics for quality end-of-life care for patients dying with metastatic cancer, underscoring the importance of its integration into cancer care.

Predictors of persistence of post-chemotherapy symptoms among survivors of solid tumor cancers

CONTEXT

Late or residual symptoms diminish quality of life for many cancer survivors after completion of treatment.

OBJECTIVES

Examine risk factors associated with persisting symptom burden after chemotherapy and the lack of symptom improvement over time.

METHODS

Survivors who completed curative-intent chemotherapy within two years for solid tumors were enrolled into a symptom management trial. There were 375 survivors with two or more comorbid conditions or one comorbid condition and elevated depressive symptoms (pre-defined risk factors in the trial design) who received interventions and 71 survivors without these risk factors who did not receive interventions. For all survivors, symptoms were assessed at intake, 4, and 13 weeks and categorized as mild, moderate, or severe based on the interference with daily life. The probabilities of moderate or severe symptoms and symptom improvement were analyzed using generalized mixed-effects models in relation to comorbidity, depressive symptoms, age, sex, race/ethnicity, employment, time since chemotherapy completion, and physical function. Multiple symptoms were treated as nested within the survivor.

RESULTS

Moderate or severe symptoms at baseline and the lack of improvement over time were associated with younger age and lower physical function over and above a greater number of comorbidities and elevated severity of depressive symptoms.

CONCLUSION

Risk factors identified in this research (younger age, lower physical function, greater comorbidity, and higher depressive symptoms) can be used to allocate resources for post-treatment symptom management for cancer survivors in order to relieve symptoms that do not necessarily resolve with time.

Comparing the use of aggressive end-of life care among frail and non-frail patients with cancer using a claims-based frailty index

INTRODUCTION

Despite mounting consensus that end-of-life (EOL) care for patients with cancer should focus on improving quality of life, many patients continue to receive aggressive, disease-oriented treatment until death. Within this group, patients with increased frailty may be at higher risk of adverse treatment-related outcomes. We therefore examined the relationship between degree of frailty and receipt of aggressive EOL care among Medicare-insured patients with cancer in Ohio.

MATERIALS AND METHODS

From the Ohio Cancer Incidence Surveillance System (OCISS) linked with Medicare claims, we identified patients diagnosed with breast, colorectal, lung, or prostate cancer who died between 2012 and 2016. Frailty was operationalized using a validated claims-based frailty index. Six quality indicators reflecting receipt of aggressive EOL care were identified from claims: (1) any cancer-directed treatment, (2) >1 emergency department (ED) visit, (3) >1 hospital admission, (4) any intensive care unit (ICU) admission in the last 30 days of life, (5) entry to hospice in the last three days of life, and (6) in-hospital mortality. Multivariable logistic regression analysis was performed to control for demographic factors, Medicare and Medicaid dual enrollment, and cancer type and stage in the relationship between frailty and aggressive EOL care.

RESULTS

Overall, 31,465 patients met selection criteria. Patients with moderate/severe frailty were less likely than non-/pre-frail patients to receive any aggressive EOL care (adjusted odds ratio [aOR] 0.92 [95% confidence interval 0.86-0.99]). This group was also less likely to undergo cancer-directed treatment in their last 30 days or to enter hospice in their last three days. Increasing frailty was associated with lower odds of admission to the ICU in the last 30 days of life (mild frailty: aOR 0.88 [0.83-0.94]; moderate/severe frailty: aOR 0.85 [0.78-0.92]) or of dying in-hospital (mild frailty: 0.85 [0.79-0.91]; moderate/severe frailty: aOR 0.74 [0.67-0.82]), but higher odds of having >1 ED visit in the last 30 days of life (mild frailty: aOR 1.43 [1.32-1.53]; moderate/severe frailty: aOR 1.61 [1.47-1.77]).

DISCUSSION

These findings suggest the need for more explicit discussion of emergency care seeking for patients with cancer at the end of life.

Association between Charlson comorbidity index and survival outcomes in patients with prostate cancer: A meta-analysis

Objective

This meta-analysis aimed to assess the influence of comorbidity, as assessed by the Charlson comorbidity index (CCI), on survival outcomes in patients with prostate cancer (PCa).

Methods

We conducted a comprehensive search of the PubMed, Web of Science, and Embase databases to identify studies that examined the association between CCI-defined comorbidity and survival outcomes in PCa patients. We employed a random effect model to merge adjusted hazard ratios (HR) with 95 % confidence intervals (CI) for survival outcomes.

Results

Sixteen studies reporting on 17 articles, which collectively included 457,256 patients. For the presence (CCI score ≥1) versus absence (CCI score of 0) of comorbidity, the pooled HR was 1.59 (95 % CI 1.43-1.77) for all-cause mortality, 0.98 (95 % CI 0.90-1.08) for PCa-specific mortality, and 1.88 (95 % CI 1.61-2.21) for other-cause mortality. When compared to a CCI score of 0, the pooled HR of all-cause mortality was 1.30 (95 % CI 1.18-1.44) for a CCI score of 1, 1.65 (95 % CI 1.37-2.00) for a CCI score ≥2, and 1.75 (95 % CI 1.57-1.95) for a CCI score ≥3. Additionally, the pooled HR of other cause mortality was 1.53 (95 % CI 1.41-1.67) for a CCI score of 1, 1.93 (95 % CI 1.74-2.75) for a CCI score ≥2, and 3.95 (95 % CI 2.13-7.34) for a CCI score ≥3.

Conclusions

Increased comorbidity, as assessed by the CCI, significantly predicts all-cause and other-cause mortality in patients with PCa, but not PCa-specific mortality. The risk of all-cause and other-cause mortality increases with the burden of comorbidity.

Frailty worsens long-term survival in patients with colorectal cancer: a systematic review and meta-analysis

Background

Colorectal cancer (CRC) is the 3rd most common cancer in men and 2nd most common malignancy in females across the globe leading to high mortality rates. Frailty is an age-related syndrome that has been associated with high morbidity and mortality. This systematic review aimed to examine if frailty can predict long-term (>1 year) outcomes of patients with CRC.

Methods

This PROSPERO registered review examined the databases of PubMed, Embase, and Web of Science till 4th September 2023 for cohort studies assessing the association between frailty and long-term outcomes of CRC.

Results

15 studies with 45288 patients were included. 6573 patients (14.5%) were frail. Meta-analysis demonstrated that frailty was associated with statistically significant poor overall survival (OS) (HR: 2.11 95% CI: 1.44, 3.08 I2 = 94%) (14 studies), cancer-specific survival (CSS) (HR: 4.59 95% CI: 2.75, 7.67 I2 = 38%) (2 studies), and disease-free survival (DFS) (HR: 1.46 95% CI: 1.28, 1.66 I2 = 0%) (5 studies) after CRC. Subgroup analysis for OS based on study type, location, sample size, stage of cancer, percentage with frailty, treatment, adjustment for CRC stage and comorbidities, and follow-up did not change the results. These results were not altered in significance on sensitivity analysis.

Conclusion

Our results show that frail CRC patients have poor OS and DFS as compared to non-frail patients. Variations in frailty measurement tools and high inter-study heterogeneity are major limitations of the review.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, PROSPERO, CRD42023450586.

Variation in multimorbidity by sociodemographics and social drivers of health among patients seen at community-based health centers

Purpose

Understanding variation in multimorbidity across sociodemographics and social drivers of health is critical to reducing health inequities.

Methods

From the multi-state OCHIN network of community-based health centers (CBHCs), we identified a cross-sectional cohort of adult (> 25 years old) patients who had a visit between 2019-2021. We used generalized linear models to examine the relationship between the Multimorbidity Weighted Index (MWI) and sociodemographics and social drivers of health (Area Deprivation Index [ADI] and social risks [e.g., food insecurity]). Each model included an interaction term between the primary predictor and age to examine if certain groups had a higher MWI at younger ages.

Results

Among 642,730 patients, 28.2% were Hispanic/Latino, 42.8% were male, and the median age was 48. The median MWI was 2.05 (IQR: 0.34, 4.87) and was higher for adults over the age of 40 and American Indians and Alaska Natives. The regression model revealed a higher MWI at younger ages for patients living in areas of higher deprivation. Additionally, patients with social risks had a higher MWI (3.16; IQR: 1.33, 6.65) than those without (2.13; IQR: 0.34, 4.89) and the interaction between age and social risk suggested a higher MWI at younger ages.

Conclusions

Greater multimorbidity at younger ages and among those with social risks and living in areas of deprivation shows possible mechanisms for the premature aging and disability often seen in community-based health centers and highlights the need for comprehensive approaches to improving the health of vulnerable populations.

Impact of multimorbidity and polypharmacy on mortality after cancer: a nationwide registry-based cohort study in Denmark 2005-2017

BACKGROUND

Concurrent chronic diseases and treatment hereof in patients with cancer may increase mortality. In this population-based study we examined the individual and combined impact of multimorbidity and polypharmacy on mortality, across 20 cancers and with 13-years follow-up in Denmark.

MATERIALS AND METHODS

This nationwide study included all Danish residents with a first primary cancer diagnosed between 1 January 2005 and 31 December 2015, and followed until the end of 2017. We defined multimorbidity as having one or more of 20 chronic conditions in addition to cancer, registered in the five years preceding diagnosis, and polypharmacy as five or more redeemed medications 2-12 months prior to cancer diagnosis. Cox regression analyses were used to estimate the effects of multimorbidity and polypharmacy, as well as the combined effect on mortality.

RESULTS

A total of 261,745 cancer patients were included. We found that patients diagnosed with breast, prostate, colon, rectal, oropharynx, bladder, uterine and cervical cancer, malignant melanoma, Non-Hodgkin lymphoma, and leukemia had higher mortality when the cancer diagnosis was accompanied by multimorbidity and polypharmacy, while in patients with cancer of the lung, esophagus, stomach, liver, pancreas, kidney, ovarian and brain & central nervous system, these factors had less impact on mortality.

CONCLUSION

We found that multimorbidity and polypharmacy was associated with higher mortality in patients diagnosed with cancer types that typically have a favorable prognosis compared with patients without multimorbidity and polypharmacy. Multimorbidity and polypharmacy had less impact on mortality in cancers that typically have a poor prognosis.

The 5-Factor Modified Frailty Index is effective in treatment decision and the determination of perioperative complications in patients with localized prostate cancer

PURPOSE

To determine the active treatment option and perioperative complications using the 5-Factor Modified Frailty Index (mFI-5) in localized prostate cancer patients.

MATERIAL AND METHODS

Patients diagnosed with localized prostate cancer in our clinic between January 2018 and October 2022 were evaluated. The patients were separated according to the mFI-5 scores as Group 1 (score = 0, n = 74), Group 2 (score = 1, n = 41), and Group 3 (score ≥ 2, n = 69). Factors affecting the determination of treatment selection, oncological results, and surgical complications were identified with regression analysis.

RESULTS

The mean age of the patients in Group 1 was lower than in Group 2 and Group 3 (63.09 ± 7.25 years vs. 67.56 ± 7.98 years and 69.2 ± 6.77 years, p < 0.001, respectively). In Group 1, more patients were treated with retropubic radical prostatectomy (RRP), and in Group 3 with radiotherapy (RT) and active surveillance (AS) (62.2%, 53.6%, and 17.4%, p = 0.001, respectively). The rate of Clavien-Dindo grade 3 and 4 complication rates were higher in Group 3 than in Group 1 (50% vs. 8.7%, p < 0.001, respectively). Frailty was found to be an independent risk factor for overall survival (HR: 10.68, p = 0.02), the presence of Clavien-Dindo ≥ 3 complication (HR: 4.9, p = 0.02) and determination of RT/AS as the active treatment option (HR: 2.45, p = 0.04).

CONCLUSION

In patients with frailty according to the mFI-5, the complication rate after RRP in localized prostate cancer increased. When selecting the treatment to be applied in these patients, it will be useful to also evaluate the frailty status.

Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study

BACKGROUND

Whilst multi-morbidity is known to be a concern in people with cancer, very little is known about the risk of cancer in multi-morbid patients. This study aims to investigate the risk of being diagnosed with lung, colorectal, breast and prostate cancer associated with multi-morbidity.

METHODS

We investigated the association between multi-morbidity and subsequent risk of cancer diagnosis in UK Biobank. Cox models were used to estimate the relative risks of each cancer of interest in multi-morbid participants, using the Cambridge Multimorbidity Score. The extent to which reverse causation, residual confounding and ascertainment bias may have impacted on the findings was robustly investigated.

RESULTS

Of the 436,990 participants included in the study who were cancer-free at baseline, 21.6% (99,965) were multi-morbid (≥ 2 diseases). Over a median follow-up time of 10.9 [IQR 10.0-11.7] years, 9,019 prostate, 7,994 breast, 5,241 colorectal, and 3,591 lung cancers were diagnosed. After exclusion of the first year of follow-up, there was no clear association between multi-morbidity and risk of colorectal, prostate or breast cancer diagnosis. Those with ≥ 4 diseases at recruitment had double the risk of a subsequent lung cancer diagnosis compared to those with no diseases (HR 2.00 [95% CI 1.70-2.35] p for trend < 0.001). These findings were robust to sensitivity analyses aimed at reducing the impact of reverse causation, residual confounding from known cancer risk factors and ascertainment bias.

CONCLUSIONS

Individuals with multi-morbidity are at an increased risk of lung cancer diagnosis. While this association did not appear to be due to common sources of bias in observational studies, further research is needed to understand what underlies this association.

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.