Clinician- and Patient-Directed Communication Strategies for Patients With Cancer at High Mortality Risk: A Cluster Randomized Trial.

Importance: Serious illness conversations (SICs) that elicit patients' values, goals, and care preferences reduce anxiety and depression and improve quality of life, but occur infrequently for patients with cancer. Behavioral economic implementation strategies (nudges) directed at clinicians and/or patients may increase SIC completion. Objective: To test the independent and combined effects of clinician and patient nudges on SIC completion. Design, Setting, and Participants: A 2 × 2 factorial, cluster randomized trial was conducted from September 7, 2021, to March 11, 2022, at oncology clinics across 4 hospitals and 6 community sites within a large academic health system in Pennsylvania and New Jersey among 163 medical and gynecologic oncology clinicians and 4450 patients with cancer at high risk of mortality (≥10% risk of 180-day mortality). Interventions: Clinician clusters and patients were independently randomized to receive usual care vs nudges, resulting in 4 arms: (1) active control, operating for 2 years prior to trial start, consisting of clinician text message reminders to complete SICs for patients at high mortality risk; (2) clinician nudge only, consisting of active control plus weekly peer comparisons of clinician-level SIC completion rates; (3) patient nudge only, consisting of active control plus a preclinic electronic communication designed to prime patients for SICs; and (4) combined clinician and patient nudges. Main Outcomes and Measures: The primary outcome was a documented SIC in the electronic health record within 6 months of a participant's first clinic visit after randomization. Analysis was performed on an intent-to-treat basis at the patient level. Results: The study accrued 4450 patients (median age, 67 years [IQR, 59-75 years]; 2352 women [52.9%]) seen by 163 clinicians, randomized to active control (n = 1004), clinician nudge (n = 1179), patient nudge (n = 997), or combined nudges (n = 1270). Overall patient-level rates of 6-month SIC completion were 11.2% for the active control arm (112 of 1004), 11.5% for the clinician nudge arm (136 of 1179), 11.5% for the patient nudge arm (115 of 997), and 14.1% for the combined nudge arm (179 of 1270). Compared with active control, the combined nudges were associated with an increase in SIC rates (ratio of hazard ratios [rHR], 1.55 [95% CI, 1.00-2.40]; P = .049), whereas the clinician nudge (HR, 0.95 [95% CI, 0.64-1.41; P = .79) and patient nudge (HR, 0.99 [95% CI, 0.73-1.33]; P = .93) were not. Conclusions and Relevance: In this cluster randomized trial, nudges combining clinician peer comparisons with patient priming questionnaires were associated with a marginal increase in documented SICs compared with an active control. Combining clinician- and patient-directed nudges may help to promote SICs in routine cancer care. Trial Registration: ClinicalTrials.gov Identifier: NCT04867850.

Prostate Cancer Recurrence: Examining the Role of Salvage Radiotherapy Field and Risk Factors for Regional Disease Recurrence Captured on 18F-DCFPyL PET/CT.

PURPOSE: The role of elective pelvic nodal irradiation in salvage radiotherapy (sRT) remains controversial. Utilizing 18F-DCFPyL PET/CT, this study aimed to investigate differences in disease distribution after whole pelvic (WPRT) or prostate bed (PBRT) radiotherapy and to identify risk factors for pelvic lymph node (LN) relapse. METHODS: This retrospective study included patients with PSA > 0.1 ng/mL post-radical prostatectomy (RP) or post-RP and sRT who underwent 18F-DCFPyL PET/CT. Disease distribution on 18F-DCFPyL PET/CT after sRT was compared using Chi-square tests. Risk factors were tested for association with pelvic LN relapse after RP and salvage PBRT using logistic regression. RESULTS: 979 18F-DCFPyL PET/CTs performed at our institution between 1/1/2022 - 3/24/2023 were analyzed. There were 246 patients meeting criteria, of which 84 received salvage RT after RP (post-salvage RT group) and 162 received only RP (post-RP group). Salvage PBRT patients (n = 58) had frequent pelvic nodal (53.6%) and nodal-only (42.6%) relapse. Salvage WPRT patients (n = 26) had comparatively lower rates of pelvic nodal (16.7%, p = 0.002) and nodal-only (19.2%, p = 0.04) relapse. The proportion of distant metastases did not differ between the two groups. Multiple patient characteristics, including ISUP grade and seminal vesicle invasion, were associated with pelvic LN disease in the post-RP group. CONCLUSION: At PSA persistence or progression, salvage WPRT resulted in lower rates of nodal involvement than salvage PBRT, but did not reduce distant metastases. Certain risk factors increase the likelihood of pelvic LN relapse after RP and can help inform salvage RT field selection.

Association of Remote Patient-Reported Outcomes and Step Counts With Hospitalization or Death Among Patients With Advanced Cancer Undergoing Chemotherapy: Secondary Analysis of the PROStep Randomized Trial.

BACKGROUND: Patients with advanced cancer undergoing chemotherapy experience significant symptoms and declines in functional status, which are associated with poor outcomes. Remote monitoring of patient-reported outcomes (PROs; symptoms) and step counts (functional status) may proactively identify patients at risk of hospitalization or death. OBJECTIVE: The aim of this study is to evaluate the association of (1) longitudinal PROs with step counts and (2) PROs and step counts with hospitalization or death. METHODS: The PROStep randomized trial enrolled 108 patients with advanced gastrointestinal or lung cancers undergoing cytotoxic chemotherapy at a large academic cancer center. Patients were randomized to weekly text-based monitoring of 8 PROs plus continuous step count monitoring via Fitbit (Google) versus usual care. This preplanned secondary analysis included 57 of 75 patients randomized to the intervention who had PRO and step count data. We analyzed the associations between PROs and mean daily step counts and the associations of PROs and step counts with the composite outcome of hospitalization or death using bootstrapped generalized linear models to account for longitudinal data. RESULTS: Among 57 patients, the mean age was 57 (SD 10.9) years, 24 (42%) were female, 43 (75%) had advanced gastrointestinal cancer, 14 (25%) had advanced lung cancer, and 25 (44%) were hospitalized or died during follow-up. A 1-point weekly increase (on a 32-point scale) in aggregate PRO score was associated with 247 fewer mean daily steps (95% CI -277 to -213; P<.001). PROs most strongly associated with step count decline were patient-reported activity (daily step change -892), nausea score (-677), and constipation score (524). A 1-point weekly increase in aggregate PRO score was associated with 20% greater odds of hospitalization or death (adjusted odds ratio [aOR] 1.2, 95% CI 1.1-1.4; P=.01). PROs most strongly associated with hospitalization or death were pain (aOR 3.2, 95% CI 1.6-6.5; P<.001), decreased activity (aOR 3.2, 95% CI 1.4-7.1; P=.01), dyspnea (aOR 2.6, 95% CI 1.2-5.5; P=.02), and sadness (aOR 2.1, 95% CI 1.1-4.3; P=.03). A decrease in 1000 steps was associated with 16% greater odds of hospitalization or death (aOR 1.2, 95% CI 1.0-1.3; P=.03). Compared with baseline, mean daily step count decreased 7% (n=274 steps), 9% (n=351 steps), and 16% (n=667 steps) in the 3, 2, and 1 weeks before hospitalization or death, respectively. CONCLUSIONS: In this secondary analysis of a randomized trial among patients with advanced cancer, higher symptom burden and decreased step count were independently associated with and predictably worsened close to hospitalization or death. Future interventions should leverage longitudinal PRO and step count data to target interventions toward patients at risk for poor outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04616768; https://clinicaltrials.gov/study/NCT04616768. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-054675.

Validation of Biomechanical Computed Tomography for Fracture Risk Classification in Metastatic Hormone-sensitive Prostate Cancer.

BACKGROUND: Guidelines recommend dual-energy x-ray absorptiometry (DXA) screening to assess fracture risk and benefit from antiresorptive therapy in men with metastatic hormone-sensitive prostate cancer (mHSPC) on androgen deprivation therapy (ADT). However, <30% of eligible patients undergo DXA screening. Biomechanical computed tomography (BCT) is a radiomic technique that measures bone mineral density (BMD) and bone strength from computed tomography (CT) scans. OBJECTIVE: To evaluate the (1) correlations between BCT- and DXA-assessed BMD, and (2) associations between BCT-assessed metrics and subsequent fracture. DESIGN, SETTING, AND PARTICIPANTS: A multicenter retrospective cohort study was conducted among patients with mHSPC between 2013 and 2020 who received CT abdomen/pelvis or positron emission tomography/CT within 48 wk before ADT initiation and during follow-up (48-96 wk after ADT initiation). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We used univariate logistic regression to assess the associations between BCT measurements and the primary outcomes of subsequent pathologic and nonpathologic fractures. RESULTS AND LIMITATIONS: Among 91 eligible patients, the median ([interquartile range) age was 67 yr (62-75), 44 (48.4%) were White, and 41 (45.1%) were Black. During the median follow-up of 82 wk, 17 men (18.6%) developed a pathologic and 15 (16.5%) a nonpathologic fracture. BCT- and DXA-assessed femoral-neck BMD T scores were strongly correlated (R2 = 0.93). On baseline CT, lower BCT-assessed BMD (odds ratio [OR] 1.80, 95% confidence interval or CI [1.10, 3.25], p = 0.03) was associated with an increased risk of a pathologic fracture. Lower femoral strength (OR 1.63, 95% CI [0.99, 2.71], p = 0.06) was marginally associated with an increased risk of a pathologic fracture. Neither BMD (OR 1.52, 95% CI [0.95, 2.63], p = 0.11) nor strength (OR 1.14, 95% CI [0.75, 1.80], p = 0.57) was associated with a nonpathologic fracture. BCT identified nine (9.9%) men eligible for antiresorptive therapy, of whom four (44%) were not treated. Limitations include low fracture numbers resulting in lower power to detect fracture associations. CONCLUSIONS: Among men diagnosed with mHSPC, BCT assessments were strongly correlated with DXA, predicted subsequent pathologic fracture, and identified additional men indicated for antiresorptive therapy. PATIENT SUMMARY: We assess whether biomechanical computer tomography (BCT) from routine computer tomography (CT) scans can identify fracture risk among patients recently diagnosed with metastatic prostate cancer. We find that BCT and dual-energy x-ray absorptiometry-derived bone mineral density are strongly correlated and that BCT accurately identifies the risk for future fracture. BCT may enable broader fracture risk assessment and facilitate timely interventions to reduce fracture risk in metastatic prostate cancer patients.

Real-World Adherence to Patient-Reported Outcome Monitoring as a Cancer Care Quality Metric.

PURPOSE: Routine collection of patient-reported outcomes (PROs) for patients with advanced solid malignancies is an evidence-based practice and critical component of high-quality cancer care, but real-world adherence is poorly characterized. We sought to describe real-world adherence to PRO monitoring and its potential predictors. METHODS: We conducted a retrospective cross-sectional study using deidentified electronic health record data from a National Cancer Institute Cancer Center, encompassing one academic and two community sites. Participants included individuals with lung cancer receiving systemic therapy from January 1 to December 31, 2019. The primary outcome was patient-level adherence, defined as the proportion of treatment visits during which a PRO questionnaire (spanning symptoms, functional status, and global quality-of-life domains) was completed within 30 days. Practice-level performance was calculated as unadjusted mean patient-level adherence. We modeled patient-level adherence using multivariable ordinary least squares regression and identified covariates associated with adherence using a significance threshold of P < .05. RESULTS: In 2019, there were 18,604 encounters for 1,105 patients with lung cancer (mean [standard deviation] age 65.8 [10.2] years; 621 [56.2%] female; 216 [19.6%] Black) receiving systemic therapy. The mean patient-level PRO adherence ranged from 27.2% to 70.0% across sites and was 49.4% overall. Advanced age (≥ 65 years) and Black or African American race were negatively associated with PRO adherence (P < .01). CONCLUSION: Across this real-world cohort of patients undergoing treatment for lung cancer, adherence to PRO monitoring lagged that achieved in seminal clinical trials, with potential age- and race-based disparities, demonstrating an implementation gap that could be addressed with standardized reporting of an adherence-based quality metric.

Impact of the COVID-19 Pandemic on Treatment Patterns for Patients With Metastatic Solid Cancer in the United States.

BACKGROUND: The COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic's impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer. METHODS: We used an electronic health record-derived longitudinal database curated via technology-enabled abstraction to identify 14 136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at approximately 280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy. RESULTS: The adjusted probability of treatment within 30 days of diagnosis was similar across periods (January-March 2019 = 41.7%, 95% confidence interval [CI] = 32.2% to 51.1%; April-July 2019 = 42.6%, 95% CI = 32.4% to 52.7%; January-March 2020 = 44.5%, 95% CI = 30.4% to 58.6%; April-July 2020 = 46.8%, 95% CI= 34.6% to 59.0%; adjusted percentage-point difference-in-differences = 1.4%, 95% CI = -2.7% to 5.5%). Among 5962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences = 1.6%, 95% CI = -2.6% to 5.8%). There was no meaningful effect modification by cancer type, race, or age. CONCLUSIONS: Despite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not affect TTI or treatment selection for patients with metastatic solid cancers.

Impact of the COVID-19 pandemic on treatment patterns for US patients with metastatic solid cancer.

BACKGROUND: The COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic's impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer. METHODS: We used an electronic health record-derived longitudinal database curated via technology-enabled abstraction to identify 14,136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at ∼280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy. RESULTS: The adjusted probability of treatment within 30 days of diagnosis [95% confidence interval] was similar across periods: January-March 2019 41.7% [32.2%, 51.1%]; April-July 2019 42.6% [32.4%, 52.7%]; January-March 2020 44.5% [30.4%, 58.6%]; April-July 2020 46.8% [34.6%, 59.0%]; adjusted percentage-point difference-in-differences 1.4% [-2.7%, 5.5%]. Among 5,962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences 1.6% [-2.6%, 5.8%]). There was no meaningful effect modification by cancer type, race, or age. CONCLUSIONS: Despite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not impact time to treatment initiation or treatment selection for patients with metastatic solid cancers.

Behavioral economic implementation strategies to improve serious illness communication between clinicians and high-risk patients with cancer: protocol for a cluster randomized pragmatic trial.

BACKGROUND: Serious illness conversations (SICs) are an evidence-based approach to eliciting patients' values, goals, and care preferences that improve patient outcomes. However, most patients with cancer die without a documented SIC. Clinician-directed implementation strategies informed by behavioral economics ("nudges") that identify high-risk patients have shown promise in increasing SIC documentation among clinicians. It is unknown whether patient-directed nudges that normalize and prime patients towards SIC completion-either alone or in combination with clinician nudges that additionally compare performance relative to peers-may improve on this approach. Our objective is to test the effect of clinician- and patient-directed nudges as implementation strategies for increasing SIC completion among patients with cancer. METHODS: We will conduct a 2 × 2 factorial, cluster randomized pragmatic trial to test the effect of nudges to clinicians, patients, or both, compared to usual care, on SIC completion. Participants will include 166 medical and gynecologic oncology clinicians practicing at ten sites within a large academic health system and their approximately 5500 patients at high risk of predicted 6-month mortality based on a validated machine-learning prognostic algorithm. Data will be obtained via the electronic medical record, clinician survey, and semi-structured interviews with clinicians and patients. The primary outcome will be time to SIC documentation among high-risk patients. Secondary outcomes will include time to SIC documentation among all patients (assessing spillover effects), palliative care referral among high-risk patients, and aggressive end-of-life care utilization (composite of chemotherapy within 14 days before death, hospitalization within 30 days before death, or admission to hospice within 3 days before death) among high-risk decedents. We will assess moderators of the effect of implementation strategies and conduct semi-structured interviews with a subset of clinicians and patients to assess contextual factors that shape the effectiveness of nudges with an eye towards health equity. DISCUSSION: This will be the first pragmatic trial to evaluate clinician- and patient-directed nudges to promote SIC completion for patients with cancer. We expect the study to yield insights into the effectiveness of clinician and patient nudges as implementation strategies to improve SIC rates, and to uncover multilevel contextual factors that drive response to these strategies. TRIAL REGISTRATION: ClinicalTrials.gov , NCT04867850 . Registered on April 30, 2021. FUNDING: National Cancer Institute P50CA244690.

Differences in Cancer Care Expenditures and Utilization for Surgery by Hospital Type Among Patients With Private Insurance.

Importance: With rising expenditures on cancer care outpacing other sectors of the US health system, national attention has focused on insurer spending, particularly for patients with private insurance, for whom price transparency has historically been lacking. The type of hospital at which cancer care is delivered may be an important factor associated with insurer spending for patients with private insurance. Objective: To examine differences in spending and utilization for patients with private insurance undergoing common cancer surgery at National Cancer Institute (NCI) centers vs community hospitals. Design, Setting, and Participants: This retrospective cross-sectional study included adult patients with an incident diagnosis of breast, colon, or lung cancer who underwent cancer-directed surgery from 2011 to 2014. Mean risk-adjusted spending and utilization outcomes were examined for each hospital type using multilevel generalized linear mixed-effects models, adjusting for patient, hospital, and region characteristics. Data were collected from the Health Care Cost Institute's national multipayer commercial claims data set, which encompasses claims paid by 3 of the 5 largest commercial health insurers in the United States (ie, Aetna, Humana, and UnitedHealthcare). Data analyses were conducted from February 2018 to February 2019. Exposures: Hospital type at which cancer surgery was performed: NCI, non-NCI academic, or community. Main Outcomes and Measures: Spending outcomes were surgery-specific insurer prices paid and 90-day postdischarge payments. Utilization outcomes were length of stay (LOS), emergency department (ED) use, and hospital readmission within 90 days of discharge. Results: The study included 66 878 patients (51 569 [77.1%] women; 31 585 [47.2%] aged ≥65 years) with incident breast (35 788 [53.5%]), colon (21 378 [32.0%]), or lung (9712 [14.5%]) cancer undergoing cancer surgery at 2995 hospitals (5522 [8.3%] at NCI centers; 10 917 [16.3%] at non-NCI academic hospitals; 50 439 [75.4%] at community hospitals). Treatment at NCI centers was associated with higher surgery-specific insurer prices paid compared with community hospitals ($18 526 [95% CI, $16 650-$20 403] vs $14 772 [95% CI, $14 339-$15 204]; difference, $3755 [95% CI, $1661-$5849]; P < .001) and 90-day postdischarge payments ($47 035 [95% CI, $43 289-$50 781] vs $41 291 [95% CI, $40 350-$42 231]; difference, $5744 [95% CI, $1659-9829]; P = .006). There were no significant differences in LOS, ED use, or hospital readmission within 90 days of discharge. Conclusions and Relevance: In this cross-sectional study, surgery at NCI centers vs community hospitals was associated with higher insurer spending for a surgical episode without differences in care utilization among patients with private insurance undergoing cancer surgery. A better understanding of the factors associated with prices and spending at NCI cancer centers is needed.

Trends in Patient Volume by Hospital Type and the Association of These Trends With Time to Cancer Treatment Initiation.

Importance: Increasing demand for cancer care may be outpacing the capacity of hospitals to provide timely treatment, particularly at referral centers such as National Cancer Institute (NCI)-designated and academic centers. Whether the rate of patient volume growth has strained hospital capacity to provide timely treatment is unknown. Objective: To evaluate trends in patient volume by hospital type and the association between a hospital's annual patient volume growth and time to treatment initiation (TTI) for patients with cancer. Design, Setting, and Participants: This retrospective, hospital-level, cross-sectional study used longitudinal data from the National Cancer Database from January 1, 2007, to December 31, 2016. Adult patients older than 40 years who had received a diagnosis of 1 of the 10 most common incident cancers and initiated their treatment at a Commission on Cancer-accredited hospital were included. Data were analyzed between December 19, 2019, and March 27, 2020. Exposures: The mean annual rate of patient volume growth at a hospital. Main Outcomes and Measures: The main outcome was TTI, defined as the number of days between diagnosis and the first cancer treatment. The association between a hospital's mean annual rate of patient volume growth and TTI was assessed using a linear mixed-effects model containing a patient volume × time interaction. The mean annual change in TTI over the study period by hospital type was estimated by including a hospital type × time interaction term. Results: The study sample included 4 218 577 patients (mean [SD] age, 65.0 [11.4] years; 56.6% women) treated at 1351 hospitals. From 2007 to 2016, patient volume increased 40% at NCI centers, 25% at academic centers, and 8% at community hospitals. In 2007, the mean TTI was longer at NCI and academic centers than at community hospitals (NCI: 50 days [95% CI, 48-52 days]; academic: 43 days [95% CI, 42-44 days]; community: 37 days [95% CI, 36-37 days]); however, the mean annual increase in TTI was greater at community hospitals (0.56 days; 95% CI, 0.49-0.62 days) than at NCI centers (-0.73 days; 95% CI, -0.95 to -0.51 days) and academic centers (0.14 days; 95% CI, 0.03-0.26 days). An annual volume growth rate of 100 patients, a level observed at less than 1% of hospitals, was associated with a mean increase in TTI of 0.24 days (95% CI, 0.18-0.29 days). Conclusions and Relevance: In this cross-sectional study, from 2007 to 2016, across the studied cancer types, patients increasingly initiated their cancer treatment at NCI and academic centers. Although increases in patient volume at these centers outpaced that at community hospitals, faster growth was not associated with clinically meaningful treatment delays.

Identification of Patient-Reported Outcome Phenotypes Among Oncology Patients With Palliative Care Needs.

PURPOSE: Despite evidence-based guidelines recommending early palliative care, it remains unclear how to identify and refer oncology patients, particularly in settings with constrained access to palliative care. We hypothesize that patient-reported outcome (PRO) data can be used to characterize patients with palliative care needs. To determine if PRO data can identify latent phenotypes that characterize indications for specialty palliative care referral. METHODS: We conducted a retrospective study of self-reported symptoms on the Edmonton Symptom Assessment System collected from solid tumor oncology patients (n = 745) referred to outpatient palliative care. Data were collected as part of routine clinical care from October 2012 to March 2018 at eight community and academic sites. We applied latent profile analysis to identify PRO phenotypes and examined the association of phenotypes with clinical and demographic characteristics using multinomial logistic regression. RESULTS: We identified four PRO phenotypes: (1) Low Symptoms (n = 295, 39.6%), (2) Moderate Pain/Fatigue + Mood (n = 180, 24.2%), (3) Moderate Pain/Fatigue + Appetite + Dyspnea (n = 201, 27.0%), and (4) High Symptoms (n = 69, 9.3%). In a secondary analysis of 421 patients, we found that two brief items assessing social and existential needs aligned with higher severity symptom and psychological distress phenotypes. CONCLUSION: Oncology patients referred to outpatient palliative care in a real-world setting can be differentiated into clinically meaningful phenotypes using brief, routinely collected PRO measures. Latent modeling provides a mechanism to use patient-reported data on a population level to identify distinct subgroups of patients with unmet palliative needs.

Assessment and Management of Cardiovascular Risk Factors Among US Veterans With Prostate Cancer.

Importance: Cardiovascular disease is a leading cause of mortality in patients with prostate cancer, and androgen deprivation therapy (ADT) may worsen cardiovascular risk. Adherence to guideline-recommended assessment and management of cardiovascular risk factors (CVRFs) in patients initiating ADT is unknown. Objective: To describe CVRF assessment and management in men with prostate cancer initiating ADT and overall. Design, Setting, and Participants: A cross-sectional analysis of 90 494 men treated within the US Veterans Health Administration diagnosed with prostate cancer between January 1, 2010, and December 31, 2017, was conducted. Participants included men with a history of atherosclerotic cardiovascular disease (ASCVD), and treatment with ADT within 1 year of diagnosis. Data analysis was conducted from September 10, 2019, to July 1, 2020. Main Outcomes and Measures: Rates of comprehensive CVRF assessment, uncontrolled CVRFs, and untreated CVRFs. Comprehensive CVRF assessment was defined as recorded measures for blood pressure, cholesterol, and glucose levels; CVRF control as blood pressure lower than 140/90 mm Hg, low-density lipoprotein cholesterol 130 mg/dL, and hemoglobin A1c less than 7%; and CVRF treatment as receipt of cardiac risk-reducing medications. Multivariable risk difference regression assessed the association between ASCVD and initiation of ADT and these outcomes. Results: Of 90 494 veterans, median age was 66 years (interquartile range, 62-70 years); and 22 700 men (25.1%) received ADT. Overall, 68.1% (95% CI, 67.8%-68.3%) of the men received comprehensive CVRF assessment; 54.1% (95% CI. 53.7%-54.4%) of those assessed had uncontrolled CVRFs, and 29.6% (95% CI, 29.2%-30.0%) of those with uncontrolled CVRFs were not receiving corresponding cardiac risk-reducing medication. Compared with the reference group of patients without ASCVD not receiving ADT, patients with ASCVD not receiving ADT had a 10.4% (95% CI, 9.5%-11.3%) higher probability of comprehensive CVRF assessment, 4.0% (95% CI, 2.9%-5.1%) lower risk of uncontrolled CVRFs, and 22.2% (95% CI, 21.1%-23.3%) lower risk of untreated CVRFs. Similar differences were observed in patients with ASCVD receiving ADT. In contrast, patients without ASCVD receiving ADT had only a 3.0% (95% CI, 2.1%-3.9%) higher probability of comprehensive CVRF assessment, 2.6% (95% CI, 1.6%-3.5%) higher risk of uncontrolled CVRFs, and 5.4% (95% CI, 4.2%-6.6%) lower risk of untreated CVRFs. Conclusions and Relevance: These findings suggest that veterans with prostate cancer had a high rate of underassessed and undertreated CVRFs, and ADT initiation was not associated with substantial improvements in CVRF assessment or management. These findings highlight gaps in care and the need for interventions to improve CVRF mitigation in this population.

Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic.

Importance: The coronavirus disease 2019 (COVID-19) pandemic has required a shift in health care delivery platforms, necessitating a new reliance on telemedicine. Objective: To evaluate whether inequities are present in telemedicine use and video visit use for telemedicine visits during the COVID-19 pandemic. Design, Setting, and Participants: In this cohort study, a retrospective medical record review was conducted from March 16 to May 11, 2020, of all patients scheduled for telemedicine visits in primary care and specialty ambulatory clinics at a large academic health system. Age, race/ethnicity, sex, language, median household income, and insurance type were all identified from the electronic medical record. Main Outcomes and Measures: A successfully completed telemedicine visit and video (vs telephone) visit for a telemedicine encounter. Multivariable models were used to assess the association between sociodemographic factors, including sex, race/ethnicity, socioeconomic status, and language, and the use of telemedicine visits, as well as video use specifically. Results: A total of 148 402 unique patients (86 055 women [58.0%]; mean [SD] age, 56.5 [17.7] years) had scheduled telemedicine visits during the study period; 80 780 patients (54.4%) completed visits. Of 78 539 patients with completed visits in which visit modality was specified, 35 824 (45.6%) were conducted via video, whereas 24 025 (56.9%) had a telephone visit. In multivariable models, older age (adjusted odds ratio [aOR], 0.85 [95% CI, 0.83-0.88] for those aged 55-64 years; aOR, 0.75 [95% CI, 0.72-0.78] for those aged 65-74 years; aOR, 0.67 [95% CI, 0.64-0.70] for those aged ≥75 years), Asian race (aOR, 0.69 [95% CI, 0.66-0.73]), non-English language as the patient's preferred language (aOR, 0.84 [95% CI, 0.78-0.90]), and Medicaid insurance (aOR, 0.93 [95% CI, 0.89-0.97]) were independently associated with fewer completed telemedicine visits. Older age (aOR, 0.79 [95% CI, 0.76-0.82] for those aged 55-64 years; aOR, 0.78 [95% CI, 0.74-0.83] for those aged 65-74 years; aOR, 0.49 [95% CI, 0.46-0.53] for those aged ≥75 years), female sex (aOR, 0.92 [95% CI, 0.90-0.95]), Black race (aOR, 0.65 [95% CI, 0.62-0.68]), Latinx ethnicity (aOR, 0.90 [95% CI, 0.83-0.97]), and lower household income (aOR, 0.57 [95% CI, 0.54-0.60] for income <$50 000; aOR, 0.89 [95% CI, 0.85-0.92], for $50 000-$100 000) were associated with less video use for telemedicine visits. These results were similar across medical specialties. Conclusions and Relevance: In this cohort study of patients scheduled for primary care and medical specialty ambulatory telemedicine visits at a large academic health system during the early phase of the COVID-19 pandemic, older patients, Asian patients, and non-English-speaking patients had lower rates of telemedicine use, while older patients, female patients, Black, Latinx, and poorer patients had less video use. Inequities in accessing telemedicine care are present, which warrant further attention.

Association of Medicaid Expansion Under the Affordable Care Act With Insurance Status, Cancer Stage, and Timely Treatment Among Patients With Breast, Colon, and Lung Cancer.

Importance: The effect of the Patient Protection and Affordable Care Act's Medicaid expansion on cancer care delivery and outcomes is unknown. Patients with cancer are a high-risk group for whom treatment delays are particularly detrimental. Objective: To examine the association between Medicaid expansion and changes in insurance status, stage at diagnosis, and timely treatment among patients with incident breast, colon, and non-small cell lung cancer. Design, Setting, and Participants: This quasi-experimental, difference-in-differences (DID) cross-sectional study included nonelderly adults (aged 40-64 years) with a new diagnosis of invasive breast, colon, or non-small cell lung cancer from January 1, 2011, to December 31, 2016, in the National Cancer Database, a hospital-based registry capturing more than 70% of incident cancer diagnoses in the United States. Data were analyzed from March 8 to August 15, 2019. Exposures: Residence in a state that expanded Medicaid on January 1, 2014. Main Outcomes and Measures: The primary outcomes were insurance status, cancer stage, and timely treatment within 30 and 90 days of diagnosis. Results: A total of 925 543 patients (78.6% women; mean [SD] age, 55.0 [6.5] years; 14.2% black; and 5.7% Hispanic) had a new diagnosis of invasive breast (58.9%), colon (14.6%), or non-small cell lung (26.5%) cancer; 48.3% resided in Medicaid expansion states and 51.7% resided in nonexpansion states. Compared with nonexpansion states, the percentage of uninsured patients decreased more in expansion states (adjusted DID, -0.7 [95% CI, -1.2 to -0.3] percentage points), and the percentage of early-stage cancer diagnoses rose more in expansion states (adjusted DID, 0.8 [95% CI, 0.3 to 1.2] percentage points). Among the 848 329 patients who underwent cancer-directed therapy within 365 days of diagnosis, the percentage treated within 30 days declined from 52.7% before to 48.0% after expansion in expansion states (difference, -4.7 [95% CI, -5.1 to -4.5] percentage points). In nonexpansion states, this percentage declined from 56.9% to 51.5% (difference, -5.4 [95% CI, -5.6 to -5.1] percentage points), yielding no statistically significant DID in timely treatment associated with Medicaid expansion (adjusted DID, 0.6 [95% CI, -0.2 to 1.4] percentage points). Conclusions and Relevance: This study found that, among patients with incident breast, colon, and lung cancer, Medicaid expansion was associated with a decreased rate of uninsured patients and increased rate of early-stage cancer diagnosis; no evidence of improvement or decrement in the rate of timely treatment was found. Further research is warranted to understand Medicaid expansion's effect on the treatment patterns and health outcomes of patients with cancer.

Developing and Sustaining an Effective and Resilient Oncology Careforce: Opportunities for Action.

Advances in cancer care have led to improved survival, which, coupled with demographic trends, have contributed to rapid growth in the number of patients needing cancer care services. However, with increasing caseload, care complexity, and administrative burden, the current workforce is ill equipped to meet these burgeoning new demands. These trends have contributed to clinician burnout, compounding a widening workforce shortage. Moreover, family caregivers, who have unique knowledge of patient preferences, symptoms, and goals of care, are infrequently appreciated and supported as integral members of the oncology "careforce." A crisis is looming, which will hinder access to timely, high-quality cancer care if left unchecked. Stemming from the proceedings of a 2019 workshop convened by the National Cancer Policy Forum of the National Academies of Sciences, Engineering, and Medicine, this commentary characterizes the factors contributing to an increasingly strained oncology careforce and presents multilevel strategies to improve its efficiency, effectiveness, and resilience. Together, these will enable today's oncology careforce to provide high-quality care to more patients while improving the patient, caregiver, and clinician experience.