Controlling for Frailty in Pharmacoepidemiologic Studies of Older Adults

Cuthbertson, Carmen C.; Kucharska‐Newton, Anna; Faurot, Keturah R.; Stürmer, Til; Funk, Michele Jönsson; Palta, Priya; Windham, B. Gwen; Thai, Sydney; Lund, Jennifer L.

doi:10.1097/ede.0000000000000833

Cited by 39 publications

(34 citation statements)

References 26 publications

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“…Frailty plays a role in health decisions and outcome, yet is a concept that is difficult to capture in administrative claims data; while many studies have tried they each have their limitations. [39,40] Our findings support the need for further research to elucidate the relationship between frailty, health service utilisation, and CUP diagnosis.…”

Section: Plos Onesupporting

confidence: 62%

Diagnostic and health service pathways to diagnosis of cancer-registry notified cancer of unknown primary site (CUP)

et al. 2020

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Background Cancer of unknown primary (CUP) is a late-stage malignancy with poor prognosis, but we know little about what diagnostic tests and procedures people with CUP receive prior to diagnosis. The purpose of this study was to determine how health service utilisation prior to diagnosis for people with cancer-registry notified CUP differs from those notified with metastatic cancer of known primary. Methods We identified people with a cancer registry notification of CUP (n = 327) from the 45 and Up Study, a prospective cohort of 266,724 people �45 years in New South Wales, Australia, matched with up to three controls with a diagnosis of metastatic cancer of known primary (n = 977). Baseline questionnaire data were linked to population health data to identify all health service use, diagnostic tests, and procedures in the month of diagnosis and 3 months prior. We used conditional logistic regression to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Results After adjusting for age and educational attainment, people with a cancer-registry notified CUP diagnosis were more likely to be an aged care resident (OR = 2.78, 95%CI 1.37-5.63), have an emergency department visit (OR = 1.65, 95%CI 1.23-2.21), serum tumor marker tests (OR = 1.51, 95%CI 1.12-2.04), or a cytology test without immunohistochemistry (OR = 2.01, 95%CI 1.47-2.76), and less likely to have a histopathology test without immunohistochemistry (OR = 0.43, 95%CI 0.31-0.59). Neither general practitioner, specialist, allied health practitioner or nurse consultations, hospitalisations, nor imaging procedures were associated with a CUP diagnosis.

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Section: Plos Onesupporting

confidence: 62%

Diagnostic and health service pathways to diagnosis of cancer-registry notified cancer of unknown primary site (CUP)

et al. 2020

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“…The EMA recommends the Short Physical Performance Battery (SPPB) as an instrument to assess physical frailty in clinical trials, and gait speed as an alternative instrument [46]. As claims databases and electronic health records became important sources for observational studies, several tools have recently been developed to measure geriatric frailty in these datasets, e.g., Medicare claims-based algorithm of frailty [47], claims-based frailty index [48], claims-based frailty indicator [49], electronic frailty index [50], etc. In observational studies, these tools may help to improve the validity and reduce confounding when adverse drug outcomes are tested.…”

Section: Smaller Sample Larger Samplementioning

confidence: 99%

Medication use in older patients and age-blind approach: narrative literature review (insufficient evidence on the efficacy and safety of drugs in older age, frequent use of PIMs and polypharmacy, and underuse of highly beneficial nonpharmacological strategies)

Fialová

Laffón²,

Marinković

et al. 2019

Eur J Clin Pharmacol

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“…37,53) Database-derived frailty measures varied widely in terms of development approaches (clinical knowledge in nine measures, cluster analysis in one measure, and reference standard measures in six measures), number of variables included (nine to 109 variables), target populations (general vs. specific disease populations), and validation outcomes (clinical frailty assessment, functional status, mortality, health care utilization, or costs). Only seven of 16 measures have been compared against a clinical frailty assessment 37,[54][55][56][57][58][59] and seven measures have been tested for disability 50,52,56,57,60) or nursing home admission. 45,52,57,60) The comparative performance of database-derived frailty measures has not been well studied.…”

Section: Approach 3: Data-driven Selection With a Reference Standardmentioning

confidence: 99%

Measuring Frailty in Health Care Databases for Clinical Care and Research

Kim

2020

Ann Geriatr Med Res

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Frailty is a clinical state resulting from age-related changes in multiple physiologic systems and accumulation of diseases that reduces patient ability to maintain homeostasis in response to stressors. 1) Frailty is common in older adults, affecting one in every 10 community-dwellers 2,3) and one in every two nursing home residents, 4) and is associated with increased risks of death (relative risk [RR], 1.6-6.0), disability (RR, 1.8-2.8), institutionalization (RR, 2.6-24.0), and falls (RR, 1.2-2.4). 1) Health care costs for older adults with frailty increase by up to 2-fold compared to those in their non-frail counterparts, 5,6) mainly due to inpatient care, post-acute care, and care for potentially preventable conditions. 7,8) Given the considerable clinical and societal consequences of frailty in the ever-growing aging population, assessment of frailty in clinical and population settings offers valuable opportunities for prevention and treatment through efficient use of evidence-based interventions and resources. 9-11) Considering the increasing burden and serious consequences of frailty in aging populations, there is increasing interest in measuring frailty in health care databases for clinical care and research. This review synthesizes the latest research on the development and application of 21 frailty measures for health care databases. Frailty measures varied widely in terms of target population (16 ambulatory, 1 long-term care, and 4 inpatient), data source (16 claims-based and 5 electronic health records [EHR]-based measures), assessment period (6 months to 36 months), data types (diagnosis codes required for 17 measures, health service codes for 7 measures, pharmacy data for 4 measures, and other information for 9 measures), and outcomes for validation (clinical frailty for 7 measures, disability for 7 measures, and mortality for 16 measures). These frailty measures may be useful to facilitate frailty screening in clinical care and quantify frailty for large database research in which clinical assessment is not feasible.

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Controlling for Frailty in Pharmacoepidemiologic Studies of Older Adults

Abstract: The Medicare claims-based algorithm showed good discrimination of phenotypic frailty and high predictive ability with adverse health outcomes. This algorithm can be used in future Medicare claims analyses to reduce confounding by frailty and improve study validity.

Cited by 39 publications

References 26 publications

Diagnostic and health service pathways to diagnosis of cancer-registry notified cancer of unknown primary site (CUP)

Diagnostic and health service pathways to diagnosis of cancer-registry notified cancer of unknown primary site (CUP)

Medication use in older patients and age-blind approach: narrative literature review (insufficient evidence on the efficacy and safety of drugs in older age, frequent use of PIMs and polypharmacy, and underuse of highly beneficial nonpharmacological strategies)

Measuring Frailty in Health Care Databases for Clinical Care and Research

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