Improving the palliative-procedure decision-making process for patients with peritoneal carcinomatosis: A secondary analysis.

BACKGROUND: Peritoneal carcinomatosis (PC) is common in patients with advanced gynecologic and gastrointestinal cancers. Frequently, patients with PC undergo palliative surgery or procedures to manage disease-related complications and side effects. However, there are limited data regarding patients' and family caregivers' decision-making processes about these procedures. Thus, we sought to describe the decision-making experiences of patients with PC who elect to pursue palliative surgical procedures and their family caregivers. METHODS: We conducted a secondary analysis of qualitative data collected during a pilot randomized controlled trial of BOLSTER, a nurse-led telehealth intervention for patients with PC and their caregivers after an acute hospitalization and palliative procedure. Participants in both study arms described their experiences in semi-structured interviews. We re-analyzed coded qualitative data with a focus on understanding decision-making experiences surrounding palliative surgery and procedures using conventional content analysis. RESULTS: Interviews from 32 participants, 23 patients and 9 caregivers, were analyzed. Participants reported their decision-making was complicated by illness uncertainty and a desire for clear, effective communication with surgical and medical oncology teams. Participants requested more information about the impact of palliative procedures on their daily life. Several also noted that, without improved understanding, a misalignment between patient and family caregiver goals and palliative procedures may inadvertently increase suffering. CONCLUSION: Discussions related to patients' goals and preferences can improve the quality of treatment decision-making in patients with PC and their caregivers. Future research should test interventions to improve advanced cancer patients' illness understanding and decision-making surrounding palliative surgery and procedures.

Feasibility and acceptability of a nurse-led telehealth intervention (BOLSTER) to support patients with peritoneal carcinomatosis and their caregivers: A pilot randomized clinical trial.

OBJECTIVE: Patients with advanced gynecologic (GYN) and gastrointestinal (GI) cancers frequently develop peritoneal carcinomatosis (PC), which limits prognosis and diminishes health-related quality of life (HRQoL). Palliative procedures may improve PC symptoms, yet patients and caregivers report feeling unprepared to manage ostomies, catheters, and other complex needs. Our objectives were to (1) assess the feasibility of an efficacy trial of a nurse-led telehealth intervention (BOLSTER) for patients with PC and their caregivers; and (2) assess BOLSTER's acceptability, potential to improve patients' HRQoL and self-efficacy, and potential impact on advance care planning (ACP). METHODS: Pilot feasibility RCT. Recently hospitalized adults with advanced GYN and GI cancers, PC, and a new complex care need and their caregivers were randomized 1:1 to BOLSTER or enhanced discharge planning (EDP). We defined feasibility as a ≥ 50% approach-to-consent ratio and acceptability as ≥70% satisfaction with BOLSTER. We assessed patients' HRQoL and self-efficacy at baseline and six weeks, then compared the proportion experiencing meaningful improvements by arm. ACP documentation was identified using natural language processing. RESULTS: We consented 77% of approached patients. In the BOLSTER arm, 91.0% of patients and 100.0% of caregivers were satisfied. Compared to EDP, more patients receiving BOLSTER experienced improvements in HRQoL (68.4% vs. 40.0%) and self-efficacy for managing symptoms (78.9% vs. 35.0%) and treatment (52.9% vs. 42.9%). The BOLSTER arm had more ACP documentation. CONCLUSIONS: BOLSTER is a feasible and acceptable intervention with the potential to improve patients' HRQoL and promote ACP. An efficacy trial comparing BOLSTER to usual care is underway. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03367247; PI: Wright.

A comparison of adult-child and spousal cancer caregivers' participation in medical decisions.

BACKGROUND: Family caregivers often play a key role in medical decision-making for patients with cancer. Adult-children account for nearly half of caregivers, but often have less experience with serious illness care and decision-making and face unique relational challenges as the patient's child. Yet little research explores the potentially distinctive decision-making, involvement in decisions, and support needs of adult-child caregivers. METHODS: Analysis of survey data of U.S. cancer caregivers conducted by CancerCare® in 2021. Chi-square tests and multivariable regression models assessed whether adult-child and spousal caregivers differed on the type of medical decisions they participated in (e.g., treatment planning, medication management), who made the decision (e.g., caregiver or joint decision), and the resources that informed decisions (e.g., friends and family, education materials). RESULTS: Adult-children (N = 892) were less likely than spouses (N = 314) to participate in treatment planning (beta = -0.41; 95%CI = -0.81,-0.01), but more likely to be involved in decisions about whether to challenge medical authority (e.g., seeking alternative treatment, second opinion) (beta = 0.50; 95%CI = 0.22,0.78). Compared to spouses, adult-children made joint decisions with patients less often (-13.2-percentage points; 95%CI = -19.64,-6.67) and acted as primary decision-maker more frequently (5.60-percentage points; 95%CI = 0.01,10.43). More adult-children than spouses sought help and information regarding decisions from the oncology team (8.42-percentage points; 95%CI = 1.98,14.87) and friends and family (7.91-percentage points; 95%CI = 1.34,14.48). CONCLUSIONS: How cancer caregivers and patients are related to each other shapes caregivers' medical decision-making. Adult-children's and spouses' probabilities of participating in and influencing decisions differed for certain types of decisions while adult-children were more likely to seek information and social support regarding decisions. These findings highlight the importance of the patient's and caregiver's relationship type in medical decision-making, suggesting that decision support programs may be more effective if they tailor programs by relationship type.

Worse Depression Profiles Are Associated With Higher Symptom Burden and Poorer Quality of Life in Patients With Gynecologic Cancer.

BACKGROUND: Depression is a pervasive symptom in patients with gynecological cancer undergoing chemotherapy. OBJECTIVES: Purposes were to identify subgroups of patients with distinct depression profiles and evaluate for differences in demographic and clinical characteristics, severity of common symptoms, and quality of life (QOL) outcomes among these subgroups. METHODS: Patients with gynecological cancer (n = 231) completed the Center for Epidemiologic Studies-Depression Scale 6 times over 2 cycles of chemotherapy. All of the other measures were completed prior to the second or third cycle of chemotherapy. Latent profile analysis was done to identify the distinct depression profiles. Differences were evaluated using parametric and nonparametric tests. RESULTS: Three distinct profiles were identified: low (60.1%), high (35.1%), and very high (4.8%). Compared with low class, the other 2 classes had lower functional status and were more likely to self-report a diagnosis of depression. Patients in the 2 worse profiles reported a higher comorbidity burden, higher levels of trait and state anxiety, sleep disturbance, and fatigue, as well as lower levels of cognitive function and poorer QOL. State and trait anxiety, evening fatigue, and sleep disturbance scores exhibit a "dose-response effect" (ie, as the depression profile worsened, the severity of these symptoms increased). CONCLUSIONS: Almost 40% of our sample experienced high or very high levels of depression across 2 cycles of chemotherapy. IMPLICATIONS FOR PRACTICE: Clinicians can use the identified risk factors to identify high patients risk and provide tailored psychological interventions aimed to decrease symptom burden and prevent decrements in QOL.

Developing a Collaborative Agenda-Setting Intervention (CASI) to promote patient-centered communication in ovarian cancer care: A design thinking approach.

OBJECTIVES: Patient-centered communication (PCC) occurs when clinicians respond to patients' needs, preferences, and concerns. While PCC is associated with better health-related quality of life in patients with cancer, patients with ovarian cancer have reported unmet communication needs. We used design thinking to develop an intervention to promote PCC in ovarian cancer care. METHODS: Following the steps of design thinking, we empathized with stakeholders by reviewing the literature, then created stakeholder and journey maps to define the design challenge. To ideate solutions, we developed a challenge map. Finally, we developed wireframe prototypes and tested them with stakeholders. RESULTS: Empathizing revealed that misaligned visit priorities precipitated suboptimal communication. Defining the design challenge and ideating solutions highlighted the need to normalize preference assessments, promote communication self-efficacy, and enhance visit efficiency. The Collaborative Agenda-Setting Intervention (CASI) elicits patients' needs and preferences and delivers communication guidance at the point of care. Stakeholders approved of the prototype. CONCLUSION: Design thinking provided a systematic approach to empathizing with stakeholders, identifying challenges, and innovating solutions. PRACTICE IMPLICATIONS: To our knowledge, the CASI is the first intervention to set the visit agenda and support communication from within the electronic health record. Future research will assess its usability and acceptability.

Experiences of patients with peritoneal carcinomatosis-related complex care needs and their caregivers.

BACKGROUND: Patients with peritoneal carcinomatosis (PC) frequently undergo palliative procedures, yet these patients and their caregivers report being unprepared to manage ostomies, drains, and other complex care needs at home. The purpose of this study was to characterize the unique needs of these patients and their caregivers during care transitions. METHODS: Patients completed measures of health status and advance care planning, caregivers completed measures of preparedness and burden, and all participants completed measures of depression and anxiety. Participants detailed their experiences in individual, semi-structured interviews. We analyzed data using descriptive statistics and conventional content analysis. RESULTS: Sixty-one patients and 39 caregivers completed baseline measures. Twenty-four (39.3%) patients acknowledged their terminal illness and seven (11.5%) had discussed end-of-life care preferences with clinicians. Most (26/39, 66.7%) caregivers provided daily care. Among caregivers who managed symptoms, few were taught how to do so (6/20, 30%). Seven patients (11.5%) and seven caregivers (17.9%) met case criteria for anxiety, while 15 patients (24.6%) and two caregivers (5.1%) met case criteria for depression. Interview participants described a diagnosis of PC as a turning point for which there is no road map and identified the need for health systems change to minimize suffering. CONCLUSION: Patients with PC and their caregivers are highly burdened by symptoms and care needs. Patients' prognostic understanding and advance care planning are suboptimal. Interventions that train patients with PC and their caregivers to perform clinical care tasks, facilitate serious illness conversations, and provide psychosocial support are needed.

Open-Source, Step-Counting Algorithm for Smartphone Data Collected in Clinical and Nonclinical Settings: Algorithm Development and Validation Study.

BACKGROUND: Step counts are increasingly used in public health and clinical research to assess well-being, lifestyle, and health status. However, estimating step counts using commercial activity trackers has several limitations, including a lack of reproducibility, generalizability, and scalability. Smartphones are a potentially promising alternative, but their step-counting algorithms require robust validation that accounts for temporal sensor body location, individual gait characteristics, and heterogeneous health states. OBJECTIVE: Our goal was to evaluate an open-source, step-counting method for smartphones under various measurement conditions against step counts estimated from data collected simultaneously from different body locations ("cross-body" validation), manually ascertained ground truth ("visually assessed" validation), and step counts from a commercial activity tracker (Fitbit Charge 2) in patients with advanced cancer ("commercial wearable" validation). METHODS: We used 8 independent data sets collected in controlled, semicontrolled, and free-living environments with different devices (primarily Android smartphones and wearable accelerometers) carried at typical body locations. A total of 5 data sets (n=103) were used for cross-body validation, 2 data sets (n=107) for visually assessed validation, and 1 data set (n=45) was used for commercial wearable validation. In each scenario, step counts were estimated using a previously published step-counting method for smartphones that uses raw subsecond-level accelerometer data. We calculated the mean bias and limits of agreement (LoA) between step count estimates and validation criteria using Bland-Altman analysis. RESULTS: In the cross-body validation data sets, participants performed 751.7 (SD 581.2) steps, and the mean bias was -7.2 (LoA -47.6, 33.3) steps, or -0.5%. In the visually assessed validation data sets, the ground truth step count was 367.4 (SD 359.4) steps, while the mean bias was -0.4 (LoA -75.2, 74.3) steps, or 0.1%. In the commercial wearable validation data set, Fitbit devices indicated mean step counts of 1931.2 (SD 2338.4), while the calculated bias was equal to -67.1 (LoA -603.8, 469.7) steps, or a difference of 3.4%. CONCLUSIONS: This study demonstrates that our open-source, step-counting method for smartphone data provides reliable step counts across sensor locations, measurement scenarios, and populations, including healthy adults and patients with cancer.

Pilot randomized trial of an acceptance-based telehealth intervention for women with ovarian cancer and PARP inhibitor-related fatigue.

OBJECTIVE: Poly(ADP-ribose) polymerase inhibitors (PARPi) have dramatically changed treatment for advanced ovarian cancer, but nearly half of patients experience significant fatigue. We conducted a two-site pilot randomized trial to evaluate the feasibility, acceptability, and preliminary efficacy of a brief, acceptance-based telehealth intervention (REVITALIZE) designed to reduce fatigue interference in patients on PARPi. METHODS: From June 2021 to April 2022, 44 participants were randomized 1:1 to REVITALIZE (6 weekly one-on-one sessions+booster) or enhanced usual care. Feasibility was defined as: ≥50% approach-to-consent among potentially eligible patients and ≥70% completion of 12-week follow-up assessment; acceptance was <20% participants reporting burden and <20% study withdrawal. Fatigue, anxiety, depression, and quality of life were assessed at baseline, 4-, 8- and 12-weeks. RESULTS: Among 44 participants (mean age = 62.5 years, 81.8% stage III/IV disease), the study was feasible (56.4% approach-to-consent ratio, 86.3% completion of 12-week assessment) and acceptable (0% reporting burden, 11.3% study withdrawal). At 12-week follow-up, REVITALIZE significantly reduced fatigue interference (Cohen's d = 0.94, p = .008) and fatigue severity (d = 0.54, p = .049), and improved fatigue levels (d = 0.62, p = .04) relative to enhanced usual care. REVITALIZE also showed promise for improved fatigue self-efficacy, fatigue catastrophizing, anxiety, depression, and quality of life (ds = 0.60-0.86, p ≥ .05). Compared with enhanced usual care, REVITALIZE participants had fewer PARPi dose reductions (6.7% vs. 19.0%), and dose delays (6.7% vs. 23.8%). CONCLUSIONS: Among fatigued adults with ovarian cancer on PARPi, a brief, acceptance-based telehealth intervention was feasible, acceptable, and demonstrated preliminary efficacy in improving fatigue interference, severity, and levels. REVITALIZE is a novel, scalable telehealth intervention worthy of further investigation.

Opportunities for Savings in Risk Arrangements for Oncologic Care.

Importance: As the US accelerates adoption of alternative payment through global payment models such as Accountable Care Organizations (ACOs) or Medicare Advantage (MA), high spending for cancer care is a potential target for savings. Objective: To quantify the extent to which ACOs and other risk-bearing organizations operating in a specific geographic area (hospital referral region [HRR]) could achieve savings by steering patients to efficient medical oncology practices. Design, Setting, and Participants: This observational study included serial cross-sections of Medicare beneficiaries with cancer from 2010 to 2018. Data were analyzed from August 2021 to March 2023. Main Outcomes and Measures: Total spending and spending by category in the 1-year period following an index visit for a patient with newly diagnosed (incident) or poor-prognosis cancer. Results: The incident cohort included 1 309 825 patients with a mean age of 74.0 years; the most common cancer types were breast (21.4%), lung (16.7%), and colorectal cancer (10.0%). The poor prognosis cohort included 1 429 973 (mean age, 72.7 years); the most common cancer types were lung (26.6%), lymphoma (11.7%), and leukemia (7.3%). Options for steering varied across markets; the top quartile market had 10 or more oncology practices, but the bottom quartile had 3 or fewer oncology practices. Total spending (including Medicare Part D) in the incident cohort increased from a mean of $57 314 in 2009 to 2010 to $66 028 in 2016 to 2017. Within markets, total spending for practices in the highest spending quartile was 19% higher than in the lowest quartile. Hospital spending was the single largest component of spending in both time periods ($20 390 and $19 718, respectively) followed by Part B (infused) chemotherapy ($8022 and $11 699). Correlations in practice-level spending between the first-year (2009) and second-year (2010) spending were high (>0.90 in all categories with most >0.98), but these attenuated over time. Conclusions and Relevance: These results suggest there may be opportunities for ACOs and other risk-bearing organizations to select or drive referrals to lower-spending oncology practices in many local markets.

Identification of distinct symptom profiles in patients with gynecologic cancers using a pre-specified symptom cluster.

PURPOSE: Pain, fatigue, sleep disturbance, and depression are four of the most common symptoms in patients with gynecologic cancer. The purposes were to identify subgroups of patients with distinct co-occurring pain, fatigue, sleep disturbance, and depression profiles (i.e., pre-specified symptom cluster) in a sample of patients with gynecologic cancer receiving chemotherapy and assess for differences in demographic and clinical characteristics, as well as the severity of other common symptoms and QOL outcomes among these subgroups. METHODS: Patients completed symptom questionnaires prior to their second or third cycle of chemotherapy. Latent profile analysis was used to identify subgroups of patients using the pre-specified symptom cluster. Parametric and nonparametric tests were used to evaluate for differences between the subgroups. RESULTS: In the sample of 233 patients, two distinct latent classes were identified (i.e., low (64.8%) and high (35.2%)) indicating lower and higher levels of symptom burden. Patients in high class were younger, had child care responsibilities, were unemployed, and had a lower annual income. In addition, these women had a higher body mass index, a higher comorbidity burden, and a lower functional status. Patients in the high class reported higher levels of anxiety, as well as lower levels of energy and cognitive function and poorer quality of life scores. CONCLUSIONS: This study identified a number of modifiable and non-modifiable risk factors associated with membership in the high class. Clinicians can use this information to refer patients to dieticians and physical therapists for tailored interventions.

Organization of Cancer Specialists in US Physician Practices and Health Systems.

PURPOSE: To describe the supply of cancer specialists, the organization of cancer care within versus outside of health systems, and the distance to multispecialty cancer centers. METHODS: Using the 2018 Health Systems and Provider Database from the National Bureau of Economic Research and 2018 Medicare data, we identified 46,341 unique physicians providing cancer care. We stratified physicians by discipline (adult/pediatric medical oncologists, radiation oncologists, surgical/gynecologic oncologists, other surgeons performing cancer surgeries, or palliative care physicians), system type (National Cancer Institute [NCI] Cancer Center system, non-NCI academic system, nonacademic system, or nonsystem/independent practice), practice size, and composition (single disciplinary oncology, multidisciplinary oncology, or multispecialty). We computed the density of cancer specialists by county and calculated distances to the nearest NCI Cancer Center. RESULTS: More than half of all cancer specialists (57.8%) practiced in health systems, but 55.0% of cancer-related visits occurred in independent practices. Most system-based physicians were in large practices with more than 100 physicians, while those in independent practices were in smaller practices. Practices in NCI Cancer Center systems (95.2%), non-NCI academic systems (95.0%), and nonacademic systems (94.3%) were primarily multispecialty, while fewer independent practices (44.8%) were. Cancer specialist density was sparse in many rural areas, where the median travel distance to an NCI Cancer Center was 98.7 miles. Distances to NCI Cancer Centers were shorter for individuals living in high-income areas than in low-income areas, even for individuals in suburban and urban areas. CONCLUSION: Although many cancer specialists practiced in multispecialty health systems, many also worked in smaller-sized independent practices where most patients were treated. Access to cancer specialists and cancer centers was limited in many areas, particularly in rural and low-income areas.

Practice-Level Variation in Molecular Testing and Use of Targeted Therapy for Patients With Non-Small Cell Lung Cancer and Colorectal Cancer.

Importance: All patients with newly diagnosed non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) should receive molecular testing to identify those who can benefit from targeted therapies. However, many patients do not receive recommended testing and targeted therapies. Objective: To compare rates of molecular testing and targeted therapy use by practice type and across practices. Design, Setting, and Participants: This cross-sectional study used 100% Medicare fee-for-service data from 2015 through 2019 to identify beneficiaries with new metastatic NSCLC or CRC diagnoses receiving systemic therapy and to assign patients to oncology practices. Hierarchical linear models were used to characterize variation by practice type and across practices. Data analysis was conducted from June 2019 to October 2022. Exposures: Oncology practice providing care. Outcomes: Primary outcomes were rates of molecular testing and targeted therapy use for patients with NSCLC and CRC. Secondary outcomes were rates of multigene testing for NSCLC and CRC. Results: There were 106 228 Medicare beneficiaries with incident NSCLC (31 521 [29.7%] aged 65-69 years; 50 348 [47.4%] female patients; 2269 [2.1%] Asian, 8282 [7.8%] Black, and 91 215 [85.9%] White patients) and 39 512 beneficiaries with incident CRC (14 045 [35.5%] aged 65-69 years; 17 518 [44.3%] female patients; 896 [2.3%] Asian, 3521 [8.9%] Black, and 32 753 [82.9%] White patients) between 2015 and 2019. Among these beneficiaries, 18 435 (12.9%) were treated at National Cancer Institute (NCI)-designated centers, 8187 (5.6%) were treated at other academic centers, and 94 329 (64.7%) were treated at independent oncology practices. Molecular testing rates increased from 74% to 85% for NSCLC and 45% to 65% for CRC. First-line targeted therapy use decreased from 12% to 8% among patients with NSCLC and was constant at 5% for patients with CRC. For NSCLC, molecular testing rates were similar across practice types while rates of multigene panel use (13.2%) and targeted therapy use (16.6%) were highest at NCI-designated cancer centers. For CRC, molecular testing rates were 3.8 (95% CI: 1.2-6.5), 3.3 (95% CI, 0.4-6.1), and 12.2 (95% CI, 9.1-15.3) percentage points lower at hospital-owned practices, large independent practices, and small independent practices, respectively. Rates of targeted therapy use for CRC were similar across practice types. After adjusting for patient characteristics, there was moderate variation in molecular testing and targeted therapy use across oncology practices. Conclusions and Relevance: In this cross-sectional study of Medicare beneficiaries, molecular testing rates for NSCLC and CRC increased in recent years but remained lower than recommended levels. Rates of targeted therapy use decreased for NSCLC and remained stable for CRC. Variation across practices suggests that where a patient was treated may have affected access to recommended testing and efficacious treatments.

Validation of an open-source smartphone step counting algorithm in clinical and non-clinical settings.

Background: Step counts are increasingly used in public health and clinical research to assess wellbeing, lifestyle, and health status. However, estimating step counts using commercial activity trackers has several limitations, including a lack of reproducibility, generalizability, and scalability. Smartphones are a potentially promising alternative, but their step-counting algorithms require robust validation that accounts for temporal sensor body location, individual gait characteristics, and heterogeneous health states. Objective: Our goal was to evaluate an open-source step-counting method for smartphones under various measurement conditions against step counts estimated from data collected simultaneously from different body locations ("internal" validation), manually ascertained ground truth ("manual" validation), and step counts from a commercial activity tracker (Fitbit Charge 2) in patients with advanced cancer ("wearable" validation). Methods: We used eight independent datasets collected in controlled, semi-controlled, and free-living environments with different devices (primarily Android smartphones and wearable accelerometers) carried at typical body locations. Five datasets (N=103) were used for internal validation, two datasets (N=107) for manual validation, and one dataset (N=45) used for wearable validation. In each scenario, step counts were estimated using a previously published step-counting method for smartphones that uses raw sub-second level accelerometer data. We calculated mean bias and limits of agreement (LoA) between step count estimates and validation criteria using Bland-Altman analysis. Results: In the internal validation datasets, participants performed 751.7±581.2 (mean±SD) steps, and the mean bias was -7.2 steps (LoA -47.6, 33.3) or -0.5%. In the manual validation datasets, the ground truth step count was 367.4±359.4 steps while the mean bias was -0.4 steps (LoA -75.2, 74.3) or 0.1 %. In the wearable validation dataset, Fitbit devices indicated mean step counts of 1931.2±2338.4, while the calculated bias was equal to -67.1 steps (LoA -603.8, 469.7) or a difference of 0.3 %. Conclusions: This study demonstrates that our open-source step counting method for smartphone data provides reliable step counts across sensor locations, measurement scenarios, and populations, including healthy adults and patients with cancer.

Using digital phenotyping to understand health-related outcomes: A scoping review.

BACKGROUND: Digital phenotyping may detect changes in health outcomes and potentially lead to proactive measures to mitigate health declines and avoid major medical events. While health-related outcomes have traditionally been acquired through self-report measures, those approaches have numerous limitations, such as recall bias, and social desirability bias. Digital phenotyping may offer a potential solution to these limitations. OBJECTIVES: The purpose of this scoping review was to identify and summarize how passive smartphone data are processed and evaluated analytically, including the relationship between these data and health-related outcomes. METHODS: A search of PubMed, Scopus, Compendex, and HTA databases was conducted for all articles in April 2021 using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Review (PRISMA-ScR) guidelines. RESULTS: A total of 40 articles were included and went through an analysis based on data collection approaches, feature extraction, data analytics, behavioral markers, and health-related outcomes. This review demonstrated a layer of features derived from raw sensor data that can then be integrated to estimate and predict behaviors, emotions, and health-related outcomes. Most studies collected data from a combination of sensors. GPS was the most used digital phenotyping data. Feature types included physical activity, location, mobility, social activity, sleep, and in-phone activity. Studies involved a broad range of the features used: data preprocessing, analysis approaches, analytic techniques, and algorithms tested. 55% of the studies (n = 22) focused on mental health-related outcomes. CONCLUSION: This scoping review catalogued in detail the research to date regarding the approaches to using passive smartphone sensor data to derive behavioral markers to correlate with or predict health-related outcomes. Findings will serve as a central resource for researchers to survey the field of research designs and approaches performed to date and move this emerging domain of research forward towards ultimately providing clinical utility in patient care.

Racial and Ethnic Disparities in Opioid Access and Urine Drug Screening Among Older Patients With Poor-Prognosis Cancer Near the End of Life.

PURPOSE: To characterize racial and ethnic disparities and trends in opioid access and urine drug screening (UDS) among patients dying of cancer, and to explore potential mechanisms. METHODS: Among 318,549 non-Hispanic White (White), Black, and Hispanic Medicare decedents older than 65 years with poor-prognosis cancers, we examined 2007-2019 trends in opioid prescription fills and potency (morphine milligram equivalents [MMEs] per day [MMEDs]) near the end of life (EOL), defined as 30 days before death or hospice enrollment. We estimated the effects of race and ethnicity on opioid access, controlling for demographic and clinical factors. Models were further adjusted for socioeconomic factors including dual-eligibility status, community-level deprivation, and rurality. We similarly explored disparities in UDS. RESULTS: Between 2007 and 2019, White, Black, and Hispanic decedents experienced steady declines in EOL opioid access and rapid expansion of UDS. Compared with White patients, Black and Hispanic patients were less likely to receive any opioid (Black, -4.3 percentage points, 95% CI, -4.8 to -3.6; Hispanic, -3.6 percentage points, 95% CI, -4.4 to -2.9) and long-acting opioids (Black, -3.1 percentage points, 95% CI, -3.6 to -2.8; Hispanic, -2.2 percentage points, 95% CI, -2.7 to -1.7). They also received lower daily doses (Black, -10.5 MMED, 95% CI, -12.8 to -8.2; Hispanic, -9.1 MMED, 95% CI, -12.1 to -6.1) and lower total doses (Black, -210 MMEs, 95% CI, -293 to -207; Hispanic, -179 MMEs, 95% CI, -217 to -142); Black patients were also more likely to undergo UDS (0.5 percentage points; 95% CI, 0.3 to 0.8). Disparities in EOL opioid access and UDS disproportionately affected Black men. Adjustment for socioeconomic factors did not attenuate the EOL opioid access disparities. CONCLUSION: There are substantial and persistent racial and ethnic inequities in opioid access among older patients dying of cancer, which are not mediated by socioeconomic variables.

Adoption of Innovative Therapies Across Oncology Practices-Evidence From Immunotherapy.

Importance: Immunotherapies reflect an important breakthrough in cancer treatment, substantially improving outcomes for patients with a variety of cancer types, yet little is known about which practices have adopted this novel therapy or the pace of adoption. Objective: To assess adoption of immunotherapies across US oncology practices and examine variation in adoption by practice type. Design, Setting, and Participants: This cohort study used data from Medicare fee-for-service beneficiaries undergoing 6-month chemotherapy episodes between 2010 and 2017. Data were analyzed January 19, 2021, to September 28, 2022, for patients with cancer types for which immunotherapy was approved by the US Food and Drug Administration (FDA) during the study period: melanoma, kidney cancer, lung cancer, and head and neck cancer. Exposures: Oncology practice location (rural vs urban), affiliation type (academic system, nonacademic system, independent), and size (1 to 5 physicians vs 6 or more physicians). Main Outcomes and Measures: The primary outcome was whether a practice adopted immunotherapy. Adoption rates for each practice type were estimated using multivariate linear models that adjusted for patient characteristics (age, sex, race and ethnicity, cancer type, Charlson Comorbidity Index, and median household income). Results: Data included 71 659 episodes at 1732 oncology practices. Of these, 264 practices (15%) were rural, 900 (52%) were independent, and 492 (28%) had 1 to 5 physicians. Most practices adopted immunotherapy within 2 years of FDA approval, but there was substantial variation in adoption rates across practice types. After FDA approval, adoption of immunotherapy was 11 (95% CI, -16 to -6) percentage points lower at rural practices than urban practices and 27 (95% CI, -32 to -22) percentage points lower at practices with 1 to 5 physicians than practices with 6 or more physicians. Adoption rates were similar at independent practices and nonacademic systems; however, both practice types had lower adoption than academic systems (independent practice difference, -6 [95% CI, -9 to -3] percentage points; nonacademic systems difference, -9 [95% CI, -11 to -6] percentage points). Conclusions and Relevance: In this cohort study of Medicare claims, practice characteristics, especially practice size and rural location, were associated with adoption of immunotherapy. These findings suggest that there may be geographic disparities in access to important innovations for treating patients with cancer.

Radiation Therapy for Endometrial Cancer: An American Society for Radiation Oncology Clinical Practice Guideline.

PURPOSE: With the results of several recently published clinical trials, this guideline informs on the use of adjuvant radiation therapy (RT) and systemic therapy in the treatment of endometrial cancer. Updated evidence-based recommendations provide indications for adjuvant RT and the associated techniques, the utilization and sequencing of adjuvant systemic therapies, and the effect of surgical staging techniques and molecular tumor profiling. METHODS: The American Society for Radiation Oncology convened a multidisciplinary task force to address 6 key questions that focused on the adjuvant management of patients with endometrial cancer. The key questions emphasized the (1) indications for adjuvant RT, (2) RT techniques, target volumes, dose fractionation, and treatment planning aims, (3) indications for systemic therapy, (4) sequencing of systemic therapy with RT, (5) effect of lymph node assessment on utilization of adjuvant therapy, and (6) effect of molecular tumor profiling on utilization of adjuvant therapy. Recommendations were based on a systematic literature review and created using a predefined consensus-building methodology and system for quality of evidence grading and strength of recommendation. RESULTS: The task force recommends RT (either vaginal brachytherapy or external beam RT) be given based on the patient's clinical-pathologic risk factors to reduce risk of vaginal and/or pelvic recurrence. When external beam RT is delivered, intensity modulated RT with daily image guided RT is recommended to reduce acute and late toxicity. Chemotherapy is recommended for patients with International Federation of Gynecology and Obstetrics (FIGO) stage I to II with high-risk histologies and those with FIGO stage III to IVA with any histology. When sequencing chemotherapy and RT, there is no prospective data to support an optimal sequence. Sentinel lymph node mapping is recommended over pelvic lymphadenectomy for surgical nodal staging. Data on sentinel lymph node pathologic ultrastaging status supports that patients with isolated tumor cells be treated as node negative and adjuvant therapy based on uterine risk factors and patients with micrometastases be treated as node positive. The available data on molecular characterization of endometrial cancer are compelling and should be increasingly considered when making recommendations for adjuvant therapy. CONCLUSIONS: These recommendations guide evidence-based best clinical practices on the use of adjuvant therapy for endometrial cancer.

Cancer Caregivers' Prognostic and End-of-Life Communication Needs and Experiences and their Impact.

CONTEXT: Family caregivers of patients with advanced cancer are integrally involved in communications regarding prognosis and end-of-life (EOL) planning and care. Yet little research has examined caregivers' communication experiences or the impact of these experiences on patients and caregivers at EOL. OBJECTIVES: Investigate cancer caregivers' communication experiences and potential impact on patient and caregiver outcomes. METHODS: Semistructured interviews with bereaved family cancer caregivers (N=19) about their communication needs and experiences as their loved one approached EOL and died. Audiotaped interviews were transcribed and thematically analyzed for communication-related themes. RESULTS: Caregivers described fulfilling many important communication roles including information gathering and sharing, advocating, and facilitating-often coordinating communication with multiple partners (e.g., patient, family, oncology team, hospital team). Caregivers reported that, among the many topics they communicated about, prognosis and EOL were the most consequential and challenging. These challenges arose for several reasons including caregivers' and patients' discordant communication needs, limited opportunity for caregivers to satisfy their personal communication needs, uncertainty regarding their communication needs and responsibilities, and feeling unacknowledged by the care team. These challenges negatively impacted caregivers' abilities to satisfy their patient-related communication responsibilities, which shaped many outcomes including end-of-life decisions, care satisfaction, and bereavement. CONCLUSION: Caregivers often facilitate essential communication for patients with advanced cancers yet face challenges successfully fulfilling their own and patients' communication needs, particularly surrounding prognostic and end-of-life conversations. Future research and interventions should explore strategies to help caregivers navigate uncertainty, create space to ask sensitive questions, and facilitate patient-caregiver discussions about differing informational needs.

A Phase II, Two-Stage Study of Letrozole and Abemaciclib in Estrogen Receptor-Positive Recurrent Endometrial Cancer.

PURPOSE: Estrogen receptor (ER)-positive endometrial cancers (ECs) are characterized by phosphatidylinositol 3-kinase (PI3K) and receptor tyrosine kinase (RTK)/RAS/ß-catenin (CTNNB1) pathway alterations in approximately 90% and 80% of cases, respectively. Extensive cross-talk between ER, PI3K, and RTK/RAS/CTNNB1 pathways leads to both ligand-dependent and ligand-independent ER transcriptional activity as well as upregulation of cyclin D1 which, in complex with cyclin-dependent kinases 4 and 6 (CDK4 and CDK6), is a critical regulator of cell cycle progression and a key mediator of resistance to hormonal therapy. We hypothesized that the combination of the aromatase inhibitor letrozole and CDK4/6 inhibitor abemaciclib would demonstrate promising activity in this setting. METHODS: We conducted a phase II, two-stage study of letrozole/abemaciclib in recurrent ER-positive EC. Eligibility criteria included measurable disease, no limit on prior therapies, and all EC histologies; prior hormonal therapy was allowed. Primary end points were objective response rate by RECIST 1.1 and progression-free survival (PFS) rate at 6 months. RESULTS: At the data cutoff date (December 03, 2021), 30 patients (28 with endometrioid EC) initiated protocol therapy; 15 (50%) patients had prior hormonal therapy. There were nine total responses (eight confirmed), for an objective response rate of 30% (95% CI, 14.7 to 49.4), all in endometrioid adenocarcinomas. Median PFS was 9.1 months, PFS at 6 months was 55.6% (95% CI, 35.1 to 72), and median duration of response was 7.4 months. Most common ≥ grade 3 treatment-related adverse events were neutropenia (20%) and anemia (17%). Responses were observed regardless of grade, prior hormonal therapy, mismatch repair, and progesterone receptor status. Exploratory tumor profiling revealed several mechanistically relevant candidate predictors of response (CTNNB1, KRAS, and CDKN2A mutations) or absence of response (TP53 mutations), which require independent validation. CONCLUSION: Letrozole/abemaciclib demonstrated encouraging and durable evidence of activity in recurrent ER positive endometrioid EC.

Predicting 180-day mortality for women with ovarian cancer using machine learning and patient-reported outcome data.

Contrary to national guidelines, women with ovarian cancer often receive treatment at the end of life, potentially due to the difficulty in accurately estimating prognosis. We trained machine learning algorithms to guide prognosis by predicting 180-day mortality for women with ovarian cancer using patient-reported outcomes (PRO) data. We collected data from a single academic cancer institution in the United States. Women completed biopsychosocial PRO measures every 90 days. We randomly partitioned our dataset into training and testing samples. We used synthetic minority oversampling to reduce class imbalance in the training dataset. We fitted training data to six machine learning algorithms and combined their classifications on the testing dataset into an unweighted voting ensemble. We assessed each algorithm's accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) using testing data. We recruited 245 patients who completed 1319 PRO assessments. The final voting ensemble produced state-of-the-art results on the task of predicting 180-day mortality for ovarian cancer paitents (Accuracy = 0.79, Sensitivity = 0.71, Specificity = 0.80, AUROC = 0.76). The algorithm correctly identified 25 of the 35 women in the testing dataset who died within 180 days of assessment. Machine learning algorithms trained using PRO data offer encouraging performance in predicting whether a woman with ovarian cancer will die within 180 days. This model could be used to drive data-driven end-of-life care and address current shortcomings in care delivery. Our model demonstrates the potential of biopsychosocial PROM information to make substantial contributions to oncology prediction modeling. This model could inform clinical decision-making Future research is needed to validate these findings in a larger, more diverse sample.