Predictors of alcohol and other drug treatment completion among young people accessing residential and community-based treatment: A retrospective analysis of routinely collected service data.

BACKGROUND AND AIMS: Young people accessing alcohol and other drug (AOD) treatment experience high rates of treatment disengagement, contributing to poorer outcomes. To improve outcomes, it is important to identify factors associated with treatment retention. This study measured the relationships between client characteristics, treatment characteristics, clinical severity measures and completion of treatment among young people. DESIGN, SETTING AND PARTICIPANTS: This study was a retrospective analysis of routinely collected data set in residential- and community-based AOD services in New South Wales, Australia. Routinely collected data from the Network of Alcohol and Other Drug Agencies' (NADA) database were used. Included individuals were aged 10-24 years and accessed treatment between 2012 and 2023 (n = 17 474). MEASUREMENTS: Variables included client-related characteristics, service characteristics and baseline measures of clinical severity [Kessler-10 (K10), EUROHIS-QoL, severity of dependence scale (SDS)]. Multivariable binary logistic regression models assessed the relationships between these characteristics and treatment completion. FINDINGS: Rates of treatment completion were highest among adolescents in community-based treatment (57%) and lowest among young adults in residential treatment (35%). Polysubstance use was negatively associated with treatment completion among adolescents [adjusted odds ratio (adjOR) = 0.71, P < 0.001] and adults (adjOR = 0.70, P < 0.001) in community-based treatment, and adolescents in residential treatment (adjOR = 0.62, P = 0.006), as was housing insecurity (adolescents in community treatment, adjOR = 0.61, P = 0.001; adults in community treatment, adjOR = 0.77, P = 0.002; adolescents in residential treatment, adjOR = 0.42, P = 0.005). Attending youth-specific services was associated with higher treatment completion rates among adults in community-based (adjOR = 1.81, P < 0.001) and residential treatment (adjOR = 1.72, P < 0.001). Varying correlates of treatment completion were identified throughout treatment groups, reflecting the differences in population and/or needs across contexts. CONCLUSIONS: In New South Wales, Australia, fewer than half of young people accessing alcohol and other drug treatment between 2012 and 2023 completed treatment, and completion rates were lower among those facing barriers such as polysubstance use and housing insecurity.

Systematic review of treatment completion rates and correlates among young people accessing alcohol and other drug treatment.

BACKGROUND AND AIMS: Treatment completion is associated with improved alcohol and other drug (AOD) treatment outcomes. Unfortunately, treatment disengagement is common, particularly among young people. We reviewed and synthesised research on AOD treatment completion and/or early disengagement among young people. METHODS: We conducted a systematic review and meta-analysis of studies reporting on completion rates and/or early disengagement from psychosocial AOD treatment among adolescents and young adults. An overall estimated treatment completion rate was calculated using inverse-variance random effects meta-analysis, and random-effects meta-regression was used to identify between-study level moderators of completion rate. We completed a narrative review summarising literature on early treatment disengagement and within-study level correlates of treatment completion. Study quality was assessed using the EPHPP. RESULTS: Of the 6158 studies screened, we retained 410 for full text review and included 98 studies in the review. Treatment completion rates were reported in 88 studies, and early disengagement rates were reported in 13. The estimated overall treatment completion rate was 59 % (95 % CI=57-61 %), with experimental studies reporting higher rates of completion than observational studies. There was limited evidence for demographic or substance-related correlates of treatment completion. Contingency management was associated with increased completion rates, as was family-based intervention. CONCLUSIONS: Disengagement from AOD treatment among youth populations is common and contributes to poor treatment outcomes. Existing research has yielded little consensus on the factors associated with treatment completion. The use of contingency management strategies and involving family/social supports in treatment were identified as potential avenues for promoting ongoing treatment engagement.

Primary Treatment Modification and Treatment Tolerability Among Older Chemotherapy Recipients With Advanced Cancer.

Importance: Older adults with advanced cancer are less likely to tolerate treatment with cytotoxic chemotherapy compared with younger patients due to their aging-related conditions. Hence, oncologists sometimes opt to employ primary treatment modifications (deviation from standard of care) during the first cycle of chemotherapy. Objective: To examine the association between primary treatment modification and treatment tolerability in older adults with advanced cancer who were starting new palliative chemotherapy regimens. Design, Setting, and Participants: This cohort study was a secondary analysis of the GAP70+ (Geriatric Assessment Intervention for Reducing Toxicity in Older Patients with Advanced Cancer) trial, which was conducted between July 2014 and March 2019. The GAP70+ trial included patients aged 70 years or older who had advanced (ie, incurable) cancer, had 1 or more geriatric assessment domain impairments, and planned to start a new palliative chemotherapy regimen. Data analysis was conducted in November 2022. Exposures: Receipt of standard-of-care chemotherapy regimens vs primary treatment modification defined as any change from National Comprehensive Cancer Network guidelines or published clinical trials (eg, primary dose reduction, schedule change). Main Outcomes and Measures: Tolerability outcomes were assessed within 3 months of treatment. These outcomes included the following: (1) any grade 3 to 5 toxic effect, according to the National Cancer Institute Common Terminology Criteria for Adverse Events; (2) patient-reported functional decline, defined as the development of worse dependency in activities of daily living using scale scores; and (3) a composite adverse outcome (an end point that combined toxic effects, functional decline, and 6-month overall survival). Multivariable cluster-weighted generalized estimating equation models examined the association between primary treatment modification and outcomes adjusting for covariates. Results: This study included 609 patients with a mean (SD) age of 77.2 (5.2) years; more than half (333 [54.7%]) were men. Race and ethnicity was available for 607 patients: 39 (6.4%) were Black, 539 (88.5%) were non-Hispanic White, and 29 (4.8%) were of other race or ethnicity. Nearly half (281 [46.1%]) received a primary modified treatment regimen. The most common cancer types were gastrointestinal cancer (228 [37.4%]) and lung cancer (174 [28.6%]). In multivariable analysis, primary treatment modification was associated with a reduced risk of grade 3 to 5 toxic effects (relative risk [RR], 0.85 [95% CI, 0.77-0.94]) and functional decline (RR, 0.80 [95% CI, 0.67-0.95]). Patients who received primary treatment modification had 32.0% lower odds of having a worse composite adverse outcome (odds ratio, 0.68 [95% CI, 0.48-0.97]). Conclusions and Relevance: In this cohort study, primary treatment modification was associated with improved tolerability of chemotherapeutic regimens among older adults with advanced cancer and aging-related conditions. These findings may help optimize cancer treatment dosing in older adults with advanced cancer and aging-related conditions.

Modifiable fall risk factors among older adults with advanced cancer: Secondary analysis of a cluster-randomized clinical trial.

INTRODUCTION: Older adults with cancer have unique fall risk factors related to their disease and treatment such as polypharmacy and neurotoxic treatments. In this secondary analysis, we identified modifiable risk factors associated with future falls among older adults with advanced cancers. MATERIALS AND METHODS: Data were from the COACH study (ClinicalTrials.gov: NCT02107443; PI: Mohile). Patients were age ≥ 70, had stage III/IV solid tumor or lymphoma, ≥1 geriatric assessment impairment, and were receiving palliative intent treatment. Falls were self-reported at baseline (in the past six months), four to six weeks, three months, and six months. We generated inverse probability weights to account for mortality-related loss to follow-up and applied these in generalized linear mixed models to estimate incidence rate ratios. RESULTS: Of 541 patients (mean age: 77, standard deviation [SD]: 5.27), 140 (26%) reported prior falls at baseline, and 467 (86%) had falls data for ≥1 follow-up timepoint. Of those, 103 (22%) reported at least one fall during the follow-up period, and 112 (24%) had incomplete follow-up due to death. In fully adjusted models, prior falls and impaired Timed Up and Go score were associated with higher incidence of falls over 6 months. DISCUSSION: We identified several potentially modifiable fall risk factors in older adults with advanced cancers. Future studies should consider ways to integrate fall risk assessment into ongoing cancer care and intervene to reduce falls in this population.

External Validation of Risk Factors for Unplanned Hospitalization in Older Adults With Advanced Cancer Receiving Chemotherapy.

BACKGROUND: Older adults (age ≥65 years) receiving chemotherapy are at risk for hospitalization. Predictors of unplanned hospitalization among older adults receiving chemotherapy for cancer were recently published using data from a study conducted by the Cancer and Aging Research Group (CARG). Our study aimed to externally validate these predictors in an independent cohort including older adults with advanced cancer receiving chemotherapy. METHODS: This validation cohort included patients (n=369) from the GAP70+ trial usual care arm. Enrolled patients were aged ≥70 years with incurable cancer and were starting a new line of chemotherapy. Previously identified risk factors proposed by the CARG study were ≥3 comorbidities, albumin level <3.5 g/dL, creatinine clearance <60 mL/min, gastrointestinal cancer, ≥5 medications, requiring assistance with activities of daily activities (ADLs), and having someone available to take them to the doctor (ie, presence of social support). The primary outcome was unplanned hospitalization within 3 months of treatment initiation. Multivariable logistic regression was applied including the 7 identified risk factors. Discriminative ability of the fitted model was performed by calculating the area under the receiver operating characteristic (AUC) curve. RESULTS: Mean age of the cohort was 77 years, 45% of patients were women, and 29% experienced unplanned hospitalization within the first 3 months of treatment. The proportions of hospitalized patients with 0-3, 4-5, and 6-7 identified risk factors were 24%, 28%, and 47%, respectively (P=.04). Impaired ADLs (odds ratio, 1.76; 95% CI, 1.04-2.99) and albumin level <3.5 g/dL (odds ratio, 2.23; 95% CI, 1.37-3.62) were significantly associated with increased odds of unplanned hospitalization. The AUC of the model, including the 7 identified risk factors, was 0.65 (95% CI, 0.59-0.71). CONCLUSIONS: The presence of a higher number of risk factors was associated with increased odds of unplanned hospitalization. This association was largely driven by impairment in ADLs and low albumin level. Validated predictors of unplanned hospitalization can help with counseling and shared decision-making with patients and their caregivers. CLINICALTRIALS: gov identifier: NCT02054741.

An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Older adults with advanced cancer who have high pretreatment symptom severity often experience adverse events during cancer treatments. Unsupervised machine learning may help stratify patients into different risk groups. Objective: To evaluate whether clusters identified from baseline patient-reported symptom severity were associated with adverse outcomes. Design, Setting, and Participants: This secondary analysis of the Geriatric Assessment Intervention for Reducing Toxicity in Older Patients With Advanced Cancer (GAP70+) Trial (2014-2019) included patients who completed the National Cancer Institute Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) before starting a new cancer treatment regimen and received care at community oncology sites across the United States. An unsupervised machine learning algorithm (k-means with Euclidean distance) clustered patients based on similarities of baseline symptom severities. Clustering variables included severity items of 24 PRO-CTCAE symptoms (range, 0-4; corresponding to none, mild, moderate, severe, and very severe). Total severity score was calculated as the sum of 24 items (range, 0-96). Whether the clusters were associated with unplanned hospitalization, death, and toxic effects was then examined. Analyses were conducted in January and February 2022. Exposures: Symptom severity. Main Outcomes and Measures: Unplanned hospitalization over 3 months (primary), all-cause mortality over 1 year, and any clinician-rated grade 3 to 5 toxic effect over 3 months. Results: Of 718 enrolled patients, 706 completed baseline PRO-CTCAE and were included (mean [SD] age, 77.2 [5.5] years, 401 [56.8%] male patients; 51 [7.2%] Black and 619 [87.8%] non-Hispanic White patients; 245 [34.7%] with gastrointestinal cancer; 175 [24.8%] with lung cancer; mean [SD] impaired Geriatric Assessment domains, 4.5 [1.6]). The algorithm classified 310 (43.9%), 295 (41.8%), and 101 (14.3%) into low-, medium-, and high-severity clusters (within-cluster mean [SD] severity scores: low, 6.3 [3.4]; moderate, 16.6 [4.3]; high, 29.8 [7.8]; P < .001). Controlling for sociodemographic variables, clinical factors, study group, and practice site, compared with patients in the low-severity cluster, those in the moderate-severity cluster were more likely to experience hospitalization (risk ratio, 1.36; 95% CI, 1.01-1.84; P = .046). Moderate- and high-severity clusters were associated with a higher risk of death (moderate: hazard ratio, 1.31; 95% CI, 1.01-1.69; P = .04; high: hazard ratio, 2.00; 95% CI, 1.43-2.78; P < .001), but not toxic effects. Conclusions and Relevance: In this study, unsupervised machine learning partitioned patients into distinct symptom severity clusters; patients with higher pretreatment severity were more likely to experience hospitalization and death. Trial Registration: ClinicalTrials.gov Identifier: NCT02054741.

The role of self-perceived age in older adults considering adjuvant chemotherapy.

INTRODUCTION: Aging-related concerns can increase the risk of treatment toxicities among older adults considering adjuvant chemotherapy. We previously demonstrated that older adults with cancer who reported feeling older than their chronological age (i.e., self-perceived age) were more likely to have aging-related concerns identified during a geriatric assessment. We explored how decisions about adjuvant chemotherapy vary with or are related to older adults' self-perceived age. MATERIALS AND METHODS: We conducted a secondary analysis of a multi-phased feasibility pilot using semi-structured interviews that were conducted to explore the patient decision-making process for adjuvant chemotherapy. Interviews incorporated questions about chronological and perceived age as factors for decision-making. Patient eligibility for the study included (1) age ≥ 70 years and older, (2) a diagnosis of breast, colon, or lung cancer and considering adjuvant chemotherapy, and (3) able to read size 18 font in English. Interview data were analyzed using constant comparative method. RESULTS: Twenty-one patients were enrolled. The mean chronological age was 78 years (range 71-91). The average perceived age of patients was 57 years (range 21-80). Eleven patients chose to receive treatment while ten patients did not. Aging-related themes illustrated that self-perceived age plays an important role when patients make decisions about adjuvant chemotherapy. More specifically, patients who reported their self-perceived age as younger than their chronological age also reported better perceived health status and chose to receive adjuvant chemotherapy. DISCUSSION: Patients' experiences of aging and self-perceived age may have different implications for decision-making.

Association of polypharmacy and potential drug-drug interactions with adverse treatment outcomes in older adults with advanced cancer.

BACKGROUND: Polypharmacy is common in older adults who are starting cancer treatment and is associated with an increased risk of potentially inappropriate medications (PIMs) and potential drug-drug interactions (PDIs). The authors evaluated the association of medication measures with adverse outcomes in older adults with advanced cancer who were receiving systemic therapy. METHODS: This secondary analysis from GAP 70+ Trial (ClinicalTrials.gov identifier NCT02054741; principal investigator, Supriya G. Mohile) enrolled patients aged 70 years and older with advanced cancer who planned to start a new treatment regimen (n = 718). Polypharmacy was assessed before the initiation of treatment and was defined as the concurrent use of eight or more medications. PIMs were categorized using 2019 Beers Criteria and the Screening Tool of Older Persons' Prescriptions. PDIs were evaluated using Lexi-Interact Online. Study outcomes were assessed within 3 months of treatment and included: (1) the number of grade ≥2 and ≥3 toxicities according to the National Cancer Institute Common Toxicity Criteria, (2) treatment-related unplanned hospitalization, and (3) early treatment discontinuation. Multivariable regression models examined the association of medication measures with outcomes. RESULTS: The mean patient age was 77 years, and 57% had lung or gastrointestinal cancers. The median number of medications was five (range, 0-24 medications), 28% of patients received eight or more medications, 67% received one or more PIM, and 25% had one or more major PDI. The mean number of grade ≥2 toxicities in patients with polypharmacy was 9.8 versus 7.7 in those without polypharmacy (adjusted ß = 1.87; standard error, 0.71; p <.01). The mean number of grade ≥3 toxicities in patients with polypharmacy was 2.9 versus 2.2 in patients without polypharmacy (adjusted ß = 0.59; standard error, 0.29; p = .04). Patients with who had one or more major PDI had 59% higher odds of early treatment discontinuation (odds ratio, 1.59; 95% confidence interval, 1.03-2.46; p = .03). CONCLUSIONS: In a cohort of older adults with advanced cancer, polypharmacy and PDIs were associated with an increased risk of adverse treatment outcomes. Providing meaningful screening and interventional tools to optimize medication use may improve treatment-related outcomes in these patients.

Effects of a Geriatric Assessment Intervention on Patient-Reported Symptomatic Toxicity in Older Adults With Advanced Cancer.

PURPOSE: Providing a geriatric assessment (GA) summary with management recommendations to oncologists reduces clinician-rated toxicity in older patients with advanced cancer receiving treatment. This secondary analysis of a national cluster randomized clinical trial (ClinicalTrials.gov identifier: NCT02054741) aims to assess the effects of a GA intervention on symptomatic toxicity measured by Patient-Reported Outcomes Common Terminology Criteria for Adverse Events (PRO-CTCAE). METHODS: From 2014 to 2019, the study enrolled patients age ≥ 70 years, with advanced solid tumors or lymphoma and ≥ 1 GA domain impairment, who were initiating a regimen with high prevalence of toxicity. Patients completed PRO-CTCAEs, including the severity of 24 symptoms (11 classified as core symptoms) at enrollment, 4-6 weeks, 3 months, and 6 months. Symptoms were scored as grade ≥ 2 (at least moderate) and grade ≥ 3 (severe/very severe). Symptomatic toxicity was determined by an increase in severity during treatment. A generalized estimating equation model was used to assess the effects of the GA intervention on symptomatic toxicity. RESULTS: Mean age was 77 years (range, 70-96 years), 43% were female, and 88% were White, 59% had GI or lung cancers, and 27% received prior chemotherapy. In 706 patients who provided PRO-CTCAEs at baseline, 86.1% reported at least one moderate symptom and 49.7% reported severe/very severe symptoms at regimen initiation. In 623 patients with follow-up PRO-CTCAE data, compared with usual care, fewer patients in the GA intervention arm reported grade ≥ 2 symptomatic toxicity (overall: 88.9% v 94.8%, P = .035; core symptoms: 83.4% v 91.7%, P = .001). The results for grade ≥ 3 toxicity were comparable but not significant (P > .05). CONCLUSION: In the presence of a high baseline symptom burden, a GA intervention for older patients with advanced cancer reduces patient-reported symptomatic toxicity.

Communication About Fall Risk in Community Oncology Practice: The Role of Geriatric Assessment.

PURPOSE: Falls are a modifiable source of morbidity for older adults with cancer, yet are underassessed in oncology practice. In this secondary analysis of a nationwide cluster-randomized controlled trial, we examined characteristics associated with patient-oncologist conversations about falls, and whether oncologist knowledge of geriatric assessment (GA) resulted in more conversations. METHODS: Eligible patients (ClinicalTrials.gov identifier: NCT02107443) were age ≥ 70 years, had stage III/IV solid tumor or lymphoma, were being treated with noncurative treatment intent, and ≥ 1 GA domain impairment. Patients in both arms underwent GA. At practices randomly assigned to the intervention arm, oncologists were provided a GA summary with management recommendations. In both arms, patients had one clinical encounter audio-recorded, transcribed, and coded to categorize whether a conversation about falls occurred. Generalized linear mixed models adjusted for arm, practice site, and other important covariates were used to generate proportions and odds ratios (ORs) from the full sample. RESULTS: Of 541 patients (intervention N = 293 and usual care N = 248, mean age: 77 years, standard deviation: 5.3), 528 had evaluable audio recordings. More patients had conversations about falls in the intervention versus usual care arm (61.3% v 10.3%, P < .001). Controlling for the intervention and practice site, history of falls (OR, 2.1; 95% CI, 1.3 to 3.6; P = .005) and impaired physical performance (OR, 4.7; 95% CI, 1.7 to 12.8; P = .002) were significantly associated with patient-oncologist conversations about falls. CONCLUSION: GA intervention increased conversations about falls. History of falls and impaired physical performance were associated with patient-oncologist conversations about falls in community oncology practice.

Using Geriatric Assessment to Guide Conversations Regarding Comorbidities Among Older Patients With Advanced Cancer.

PURPOSE: Older patients with advanced cancer often have comorbidities that can worsen their cancer and treatment outcomes. We assessed how a geriatric assessment (GA)-guided intervention can guide conversations about comorbidities among patients, oncologists, and caregivers. METHODS: This secondary analysis arose from a nationwide, multisite cluster-randomized trial (ClinicalTrials.gov identifier: NCT02107443). Eligible patients were ≥ 70 years, had advanced cancer (solid tumors or lymphoma), and had impairment in at least one GA domain (not including polypharmacy). Oncology practices (n = 30) were randomly assigned to usual care or intervention. All patients completed a GA; in the intervention arm, a GA summary with recommendations was provided to their oncologist. Patients completed an Older Americans Resources and Services Comorbidity questionnaire at screening. The clinical encounter following GA was audio-recorded, transcribed, and coded for topics related to comorbidities. Linear mixed models examined the effect of the intervention on the outcomes adjusting for practice site as a random effect. RESULTS: Patients (N = 541) were 76.6 ± 5.2 years old; 94.6% of patients had at least one comorbidity with an average of 3.2 ± 1.9. The intervention increased the average number of conversations regarding comorbidities per patient from 0.52 to 0.99 (P < .01). Moreover, there were a greater number of concerns acknowledged (0.52 v 0.32; P = .03) and there was a 2.4-times higher odds of having comorbidity concerns addressed via referral, handout, or other modes (95% CI, 1.3 to 4.3; P = .004). Most oncologists in the intervention arm (76%) discussed comorbidities in light of the treatment plan, and 41% tailored treatment plans. CONCLUSION: Providing oncologists with a GA-guided intervention enhanced communication regarding comorbidities.

Evaluation of geriatric assessment and management on the toxic effects of cancer treatment (GAP70+): a cluster-randomised study.

BACKGROUND: Older adults with advanced cancer are at a high risk for treatment toxic effects. Geriatric assessment evaluates ageing-related domains and guides management. We examined whether a geriatric assessment intervention can reduce serious toxic effects in older patients with advanced cancer who are receiving high risk treatment (eg, chemotherapy). METHODS: In this cluster-randomised trial, we enrolled patients aged 70 years and older with incurable solid tumours or lymphoma and at least one impaired geriatric assessment domain who were starting a new treatment regimen. 40 community oncology practice clusters across the USA were randomly assigned (1:1) to the intervention (oncologists received a tailored geriatric assessment summary and management recommendations) or usual care (no geriatric assessment summary or management recommendations were provided to oncologists) by means of a computer-generated randomisation table. The primary outcome was the proportion of patients who had any grade 3-5 toxic effect (based on National Cancer Institute Common Terminology Criteria for Adverse Events version 4) over 3 months. Practice staff prospectively captured toxic effects. Masked oncology clinicians reviewed medical records to verify. The study was registered with ClinicalTrials.gov, NCT02054741. FINDINGS: Between July 29, 2014, and March 13, 2019, we enrolled 718 patients. Patients had a mean age of 77·2 years (SD 5·4) and 311 (43%) of 718 participants were female. The mean number of geriatric assessment domain impairments was 4·5 (SD 1·6) and was not significantly different between the study groups. More patients in intervention group compared with the usual care group were Black versus other races (40 [11%] of 349 patients vs 12 [3%] of 369 patients; p<0·0001) and had previous chemotherapy (104 [30%] of 349 patients vs 81 [22%] of 369 patients; p=0·016). A lower proportion of patients in the intervention group had grade 3-5 toxic effects (177 [51%] of 349 patients) compared with the usual care group (263 [71%] of 369 patients; relative risk [RR] 0·74 (95% CI 0·64-0·86; p=0·0001). Patients in the intervention group had fewer falls over 3 months (35 [12%] of 298 patients vs 68 [21%] of 329 patients; adjusted RR 0·58, 95% CI 0·40-0·84; p=0·0035) and had more medications discontinued (mean adjusted difference 0·14, 95% CI 0·03-0·25; p=0·015). INTERPRETATION: A geriatric assessment intervention for older patients with advanced cancer reduced serious toxic effects from cancer treatment. Geriatric assessment with management should be integrated into the clinical care of older patients with advanced cancer and ageing-related conditions. FUNDING: National Cancer Institute.

The Relationship Between Frailty and Emotional Health in Older Patients with Advanced Cancer.

BACKGROUND: Aging-related deficits that eventually manifest as frailty may be associated with poor emotional health in older patients with advanced cancer. This study aimed to examine the relationship between frailty and emotional health in this population. METHODS: This was a secondary analysis of baseline data from a nationwide cluster randomized trial. Patients were aged ≥70 years with incurable stage III/IV solid tumors or lymphomas, had ≥1 geriatric assessment (GA) domain impairment, and had completed the Geriatric Depression Scale, Generalized Anxiety Disorder-7, and Distress Thermometer. Frailty was assessed using a Deficit Accumulation Index (DAI; range 0-1) based on GA, which did not include emotional health variables (depression and anxiety), and participants were stratified into robust, prefrail, and frail categories. Multivariate logistic regression models examined the association of frailty with emotional health outcomes. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were reported. RESULTS: Five hundred forty-one patients were included (mean age: 77 years; 70-96). DAI ranged from 0.04 to 0.94; 27% of patients were classified as robust, 42% prefrail, and 31% frail. Compared with robust patients, frail patients had an increased risk of screening positive for depression (aOR = 12.8; 95% CI = 6.1-27.0), anxiety (aOR = 6.6; 95% CI = 2.2-19.7), and emotional distress (aOR = 4.62; 95% CI = 2.9-8.3). Prefrail compared with robust patients also had an increased risk of screening positive for depression (aOR = 2.22; 95% CI = 1.0-4.8) and distress (aOR = 1.71; 95% CI = 1.0-2.8). CONCLUSION: In older patients with advanced cancer, frailty is associated with poorer emotional health, which indicates a need for an integrated care approach to treating these patients. IMPLICATIONS FOR PRACTICE: A relationship exists between frailty and poor emotional health in older adults with advanced cancer. Identifying areas of frailty can prompt screening for emotional health and guide delivery of appropriate interventions. Alternatively, attention to emotional health may also improve frailty.

Caregiving burden of informal caregivers of older adults with advanced cancer: The effects of rurality and education.

OBJECTIVES: Rural-urban disparities in the experiences of caregivers of older adults with advanced cancer may exist. This study examined factors associated with caregiver mastery and burden and explored whether rural-urban disparities in caregiver outcomes differed by education. MATERIALS AND METHODS: Longitudinal data (baseline, 4-6 weeks, and 3 months) on caregivers of older adults (≥ 70) with advanced cancer were obtained from a multicenter geriatric assessment (GA) trial (ClinicalTrials.gov: NCT02107443). Rurality was determined based on 2010 Rural-Urban Commuting Area codes. Caregivers' education was categorized as ≥ some college vs ≤ high school. Caregiver outcomes included Ryff Environmental Mastery (scored 7-35) and Caregiver Reaction Assessment (including self-esteem, disrupted schedules, financial problems, lack of social support, and health problems; each scored 1-5). Separate linear mixed models with interaction term of education and rurality were performed. RESULTS: Of 414 caregivers, 64 (15.5%) were from rural areas and 263 (63.5%) completed ≥ some college. Rurality was significantly associated with more disrupted schedules (ß = 0.21), financial problems (ß = 0.17), and lack of social support (ß = 0.11). A significant interaction between education and rurality was found, with rurality associated with lower mastery (ß = -1.27) and more disrupted schedule (ß = 0.25), financial problems (ß = 0.33), and lack of social support (ß = 0.32) among caregivers with education ≤ high school. CONCLUSION: Our study identifies subgroups of caregivers who are vulnerable to caregiving burden, specifically those from rural areas and with lower education. Multifaceted interventions are needed to improve caregivers' competency and reduce caregiving burden.

Association of Polypharmacy and Potentially Inappropriate Medications With Physical Functional Impairments in Older Adults With Cancer.

BACKGROUND: Polypharmacy and potentially inappropriate medications (PIMs) are prevalent in older adults with cancer, but their associations with physical function are not often studied. This study examined the associations of polypharmacy and PIMs with physical function in older adults with cancer, and determined the optimal cutoff value for the number of medications most strongly associated with physical functional impairment. METHODS: This cross-sectional analysis used baseline data from a randomized study enrolling patients aged ≥70 years with advanced cancer starting a new systemic cancer treatment. We categorized PIM using 2015 American Geriatrics Society Beers Criteria. Three validated physical function measures were used to assess patient-reported impairments: activities of daily living (ADL) scale, instrumental activities of daily living (IADL) scale, and the Older Americans Resources and Services Physical Health (OARS PH) survey. Optimal cutoff value for number of medications was determined by the Youden index. Separate multivariate logistic regressions were then performed to examine associations of polypharmacy and PIMs with physical function measures. RESULTS: Among 439 patients (mean age, 76.9 years), the Youden index identified ≥8 medications as the optimal cutoff value for polypharmacy; 43% were taking ≥8 medications and 62% were taking ≥1 PIMs. On multivariate analysis, taking ≥8 medications was associated with impairment in ADL (adjusted odds ratio [aOR], 1.64; 95% CI, 1.01-2.58) and OARS PH (aOR, 1.73; 95% CI, 1.01-2.98). PIMs were associated with impairments in IADL (aOR, 1.72; 95% CI, 1.09-2.73) and OARS PH (aOR, 1.97; 95% CI, 1.15-3.37). A cutoff of 5 medications was not associated with any of the physical function measures. CONCLUSIONS: Physical function, an important component of outcomes for older adults with cancer, is cross-sectionally associated with polypharmacy (defined as ≥8 medications) and with PIMs. Future studies should evaluate the association of polypharmacy with functional outcomes in this population in a longitudinal fashion.

Associations of Uncertainty With Psychological Health and Quality of Life in Older Adults With Advanced Cancer.

CONTEXT: Older adults with advanced cancer face uncertainty related to their disease and treatment. OBJECTIVES: To evaluate the associations of uncertainty with psychological health and quality of life (QoL) in older adults with advanced cancer. METHODS: Secondary cross-sectional analysis of baseline data from a national clustered geriatric assessment trial. Patients 70 years and older with advanced cancer considering a new line of chemotherapy were recruited. We measured uncertainty using the modified nine-item Mishel Uncertainty in Illness Scale. Dependent variables included anxiety (Generalized Anxiety Disorder-7), depression (Generalized Depression Scale-15), distress (distress thermometer), QoL (Functional Assessment of Cancer Therapy-General), and emotional well-being (Functional Assessment of Cancer Therapy-General subscale). We used multivariate linear regression analyses to evaluate the association of uncertainty with each dependent variable. We conducted a partial least squares analysis with a variable importance in projection (VIP) plot to assess the contribution of individual variables to the model. Variables with a VIP <0.8 were considered less influential. RESULTS: We included 527 patients (median age 76 years; range 70-96). In multivariate analyses, higher levels of uncertainty were significantly associated with greater anxiety (ß = 0.11; SE = 0.04), depression (ß = 0.09; SE = 0.02), distress (ß = 0.12; SE = 0.02), as well as lower QoL (ß = -1.08; SE = 0.11) and emotional well-being (ß = -0.29; SE = 0.03); the effect sizes were considered small. Uncertainty items related to disease and treatment were most strongly associated with psychological health and QoL scores (all VIP >0.8). CONCLUSION: Uncertainty among older patients with advanced cancer is associated with worse psychological health and QoL. Tailored uncertainty management strategies are warranted.

Treatment decision-making in acute myeloid leukemia: a qualitative study of older adults and community oncologists.

Little is known about the characteristics of patients, physicians, and organizations that influence treatment decisions in older patients with AML. We conducted qualitative interviews with community oncologists and older patients with AML to elicit factors that influence their treatment decision-making. Recruitment was done via purposive sampling and continued until theoretical saturation was reached, resulting in the inclusion of 15 patients and 15 oncologists. Participants' responses were analyzed using directed content analysis. Oncologists and patients considered comorbidities, functional status, emotional health, cognition, and social factors when deciding treatment; most oncologists evaluated these using clinical gestalt. Sixty-seven percent of patients perceived that treatment was their only option and that they had not been offered a choice. In conclusion, treatment decision-making is complex and influenced by patient-related factors. These factors can be assessed as part of a geriatric assessment which can help oncologists better determine fitness and guide treatment decision-making.

Assessment of Financial Toxicity Among Older Adults With Advanced Cancer.

Importance: Financial toxicity (FT), unintended and unanticipated financial burden experienced by cancer patients undergoing cancer care, is associated with negative consequences and increased risk of mortality. Older patients (≥70 years) with cancer are at risk for FT, yet data are limited on FT and whether oncologists discuss FT with their patients. Objective: To examine the prevalence of FT in older adults with advanced cancer, its association with health-related quality of life (HRQoL), and cost conversations between oncologists and patients. Design, Setting, and Participants: This cross-sectional secondary analysis was performed on baseline data from the Improving Communication in Older Cancer Patients and Their Caregivers study, a cluster randomized trial from 31 community oncology practices across the US that was conducted from October 29, 2014, to April 28, 2017. Participants included 536 patients with advanced cancer who answered 3 questions regarding financial toxicity. Data were analyzed from September 1, 2019, to May 1, 2020. Exposure: Older patients undergoing cancer care treatments. Main Outcomes and Measures: The main outcome looked at FT and its association with HRQoL. Three questions were used to identify patients 70 years or older experiencing FT. Multivariable linear regression models were used to assess the independent associations of FT with HRQoL. A single audio-recorded clinic transcript was analyzed within 4 weeks of enrollment for patients with FT. The framework method was used to identify frequency and themes related to cost conversations. Results: This study evaluated 536 patients 70 years or older with advanced cancer. Ninety-eight patients (18.3%) reported FT; mean (SD) age was 76.4 (5.4) years; 59 (60.2%) were female, 14 (14.3%) were Black/African American, 91 (92.9%) were not employed, and 29 (29.6%) had Medicare as their sole insurance coverage. On multivariate regression analyses, FT was associated with higher levels of depression (ß = 0.81; 95% CI, 0.15-1.48), anxiety (ß = 1.67; 95% CI, 0.74-2.61), and distress (ß = 0.73; 95% CI, 0.08-1.39) and lower HRQoL (ß = -5.30; 95% CI, -8.92 to -1.69). Among those who reported FT, 49% had a conversation with their health care professional about costs. Most conversations (79%) were initiated by oncologists or patients. Four themes were generated from cost conversations: statements regarding cost of care, ability to afford medical prescriptions, indirect consequences associated with inability to work and provide for family, and cost burden in nontreatment domains. Conclusions and Relevance: In this study, among older adults with advanced cancer, FT is associated with worse HRQoL. Almost half of conversations among patients reporting FT demonstrated costs are being actively discussed. Resources and interventions are needed to manage FT.

Evolution of a community-centred experiential learning module: A mixed-methods approach to promote social accountability and community partnership in undergraduate medical education.

This article was migrated. The article was marked as recommended. Background: Education in social determinants of health (SDH) has become an important part of medical curricula, facilitated increasingly through students' experiential learning with communities. The Community and Workplace Centred Learning Experience (CWCLE) module of the University of Saskatchewan, Canada, intends to integrate and extend second-year medical students' attitudes, skills, and knowledge about SDH and community resources. We aimed to: 1) Solicit students' self-evaluation of their ability to perform module learning objectives, 2) Assess module impact on student attitudes toward SDH, 3) Obtain feedback from community partners and students about their community experiences, and 4) Use feedback to collaboratively develop recommendations to enhance the CWCLE module. Methods: We used a mixed-method approach to combine quantitative data with stories and personal experiences. We developed an online survey for two cohorts of students who had completed the module, soliciting students to self-evaluate their perceived abilities to perform the module's learning objectives and evaluating students' attitudes towards SDH. We invited representatives from community agencies involved in the CWCLE module to participate in focus groups. We also held separate focus groups with students who participated in the online survey to elaborate on their survey comments. Results: In total, 145 students participated in the online survey (response rate=72.5%). Eleven community agency representatives and seven students participated in five focus groups. Our results demonstrate that medical students benefit from community-based experiential learning of SDH and community resources. We trace evaluations and discussions in the ongoing development of this community-based experiential learning module from its initial, primarily medical-school driven designs, towards a substantial involvement of community-based organizations in its operation and continuing redevelopment. Conclusions: Our mixed method offered us a better understanding of module impact and opportunities for improvement. This module evaluation and reform generated opportunities for community partners to influence decisions in medical education and led to a collaborative evolution of a community-centred learning experience. Medical schools should actively engage community partners in teaching behavioural and social components of the curriculum and acknowledge their partners' expertise to promote community engagement and social accountability in medical education.