Oncology hospitalist impact on hospice utilization.

BACKGROUND: Unplanned hospitalizations among patients with advanced cancer are often sentinel events prompting goals of care discussions and hospice transitions. Late referrals to hospice, especially those at the end of life, are associated with decreased quality of life and higher total health care costs. Inpatient management of patients with solid tumor malignancies is increasingly shifting from oncologists to oncology hospitalists. However, little is known about the impact of oncology hospitalists on the timing of transition to hospice. OBJECTIVE: To compare hospice discharge rate and time to hospice discharge on an inpatient oncology service led by internal medicine-trained hospitalists and a service led by oncologists. METHODS: At Smilow Cancer Hospital, internal medicine-trained hospitalists were integrated into one of two inpatient medical oncology services allowing comparison between the new, hospitalist-led service (HS) and the traditional, oncologist-led service (TS). Discharges from July 26, 2021, through January 31, 2022, were identified from the electronic medical record. The odds ratio for discharge disposition by team was calculated by logistic regression using a multinomial distribution. Adjusted length of stay before discharge was assessed using multivariable linear regression. RESULTS: The HS discharged 47/400 (11.8%) patients to inpatient hospice, whereas the TS service discharged 18/313 (5.8%), yielding an adjusted odds ratio of 1.94 (95% CI, 1.07-3.51; p = .03). Adjusted average length of stay before inpatient hospice disposition was 6.83 days (95% CI, 4.22-11.06) for the HS and 16.29 days (95% CI, 7.73-34.29) for the TS (p = .003). CONCLUSIONS: Oncology hospitalists improve hospice utilization and time to inpatient hospice referral on an inpatient medical oncology service. PLAIN LANGUAGE SUMMARY: Patients with advanced cancer are often admitted to the hospital near the end of life. These patients generally have a poor chance of long-term survival and may prefer comfort-focused care with hospice. In this study, oncology hospitalists discharged a higher proportion of patients to inpatient hospice with less time spent in the hospital before discharge.

Patterns of treatment with everolimus exemestane in hormone receptor-positive HER2-negative metastatic breast cancer in the era of targeted therapy.

BACKGROUND: There is currently no clinical trial data regarding the efficacy of everolimus exemestane (EE) following prior treatment with CDK4/6 inhibitors (CDK4/6i). This study assesses the use and efficacy of everolimus exemestane in patients with metastatic HR+ HER2- breast cancer previously treated with endocrine therapy (ET) or endocrine therapy + CDK4/6i. METHODS: Retrospective analysis of electronic health record-derived data for HR+ HER2- metastatic breast cancer from 2012 to 2018. The proportion of patients receiving EE first-line, second-line, or third-line, and the median duration of EE prior to next line of treatment (TTNT) by line of therapy was calculated. OS for patients receiving EE first-line, second-line, or third-line, indexed to the date of first-line therapy initiation and stratified by prior treatment received, was calculated with Kaplan-Meier method with multivariable Cox proportional hazards regression analysis. RESULTS: Six hundred twenty-two patients received EE first-line (n = 104, 16.7%), second-line (n = 273, 43.9%) or third-line (n = 245, 39.4%). Median TTNT was 8.3 months, 5.5 months, and 4.8 months respectively. Median TTNT of EE second-line was longer following prior ET alone compared to prior ET + CDK4/6i (6.2 months (95% CI 5.2, 7.3) vs 4.3 months (95% CI 3.2, 5.7) respectively, p = 0.03). Similarly, EE third-line following ET alone vs ET + CDK4/6i in first- or second-line resulted in median TTNT 5.6 months (95% CI 4.4, 6.9) vs 4.1 months (95% CI 3.6, 6.1) respectively, although this was not statistically significant (p = 0.08). Median OS was longer for patients who received EE following prior ET + CDK4/6i. EE second-line following ET + CDK 4/6i vs ET alone resulted in median OS 37.7 months vs. 32.7 months (p = 0.449). EE third-line following ET + CDK4/6i vs prior ET alone resulted in median OS 59.2 months vs. 40.8 months (p < 0.010). This difference in OS was not statistically significant when indexed to the start of EE therapy. CONCLUSION: This study suggests that EE remains an effective treatment option after prior ET or ET + CDK4/6i use. Median TTNT of EE was longer for patients who received prior ET, whereas median OS was longer for patients who received prior ET + CDK4/6i. However, this improvement in OS was not statistically significant when indexed to the start of EE therapy suggesting that OS benefit is primarily driven by prior CDK4/6i use. EE remains an effective treatment option regardless of prior treatment option.

NCCN Policy Summit: Defining, Measuring, and Applying Quality in an Evolving Health Policy Landscape and the Implications for Cancer Care.

Quality measurement is a critical component of advancing a health system that pays for performance over volume. Although there has been significant attention paid to quality measurement within health systems in recent years, significant challenges to meaningful measurement of quality care outcomes remain. Defining cost can be challenging, but is arguably not as elusive as quality, which lacks standard measurement methods and units. To identify industry standards and recommendations for the future, NCCN recently hosted the NCCN Oncology Policy Summit: Defining, Measuring, and Applying Quality in an Evolving Health Policy Landscape and the Implications for Cancer Care. Key stakeholders including physicians, payers, policymakers, patient advocates, and technology partners reviewed current quality measurement programs to identify success and challenges, including the Oncology Care Model. Speakers and panelists identified gaps in quality measurement and provided insights and suggestions for further advancing quality measurement in oncology. This article provides insights and recommendations; however, the goal of this program was to highlight key issues and not to obtain consensus.

Association between prolonged metastatic free interval and recurrent metastatic breast cancer survival: findings from the SEER database.

PURPOSE: The prevalence of patients living with prolonged interval between initial breast cancer diagnosis and development of subsequent metastatic disease may be increasing with improved treatment. In order to counsel these patients as to their prognosis, we investigated the association between metastatic free interval (MFI) and subsequent survival from newly diagnosed metastatic breast cancer (MBC) in a population-level U.S. cohort. METHODS: The Surveillance, Epidemiology and End Results database was used to identify patients with both an initial stage 1-3 breast cancer diagnosis and subsequent MBC diagnosis recorded from 1988 to 2014. Patients were stratified by MFI (< 5 years, 5-10 years, > 10 years). The association between MFI and metastatic breast cancer-specific mortality (MBCSM) was analyzed with Fine-Gray competing risks regression. RESULTS: Five-year recurrent metastatic breast cancer-specific survival rate was 23%, 26%, and 35% for patients with MFI < 5, 5-10, and > 10 years, respectively. Patients with > 10 year MFI were less likely to die of breast cancer when compared with a referent group with < 5 years MFI (standard hazard ratio (SHR) 0.77 [95% CI 0.65-0.90] P < 0.001). There was no significant difference for patients with MFI of 5-10 years (SHR 0.92 [95% CI 0.81-1.04, P 0.191]) compared to < 5 years. Other prognostic factors like White race, lower tumor grade, and ER/PR-positive receptors were also associated with improved cancer-specific survival after diagnosis of MBC. CONCLUSION: Prolonged MFI greater than 10 years between initial breast cancer diagnosis and subsequent metastatic disease was found to be associated with improved recurrent MBC 5-year survival and decreased risk of breast cancer-specific mortality. This has potential implications for counseling patients as to prognosis, choice of treatment, as well as the stratification of patients considered for MBC clinical trials.

The impact of communication style on patient satisfaction.

BACKGROUND: Communication between patients and health providers influences patient satisfaction, but it is unknown whether similarity in communication styles results in higher patient satisfaction. METHODS: This study was conducted in the Smilow Cancer Hospital Breast Center. During routine follow-up visits, patients completed a Communication Styles Assessment (CSA), health survey (SF-12), Princess Margaret Hospital Satisfaction with Doctor Questionnaire, and brief demographic form. Physicians and Advanced Practice Providers were also asked to complete the CSA. Patients and providers were blinded to each other's responses. A communication styles concordance score was calculated as the Pearson correlation between 80 binary CSA items for each provider/patient pair. Factors affecting patient satisfaction scores were assessed in mixed-effects models. RESULTS: In total, 330 patients were invited to participate; of these 289 enrolled and 245 returned surveys. One hundred seventy-four completed all survey components, and 18 providers completed the CSA. Among the factors considered, physical health score (effect size = 0.0058, 95% CI 0.00051 to 0.0011, p = 0.032) and employment status (0.12, 95% CI - 0.0094 to 0.25, p = 0.069) had the greatest impact on patient satisfaction. However, patients who were not employed and less physically healthy had significantly elevated satisfaction scores when their communication style was more similar to their provider's (1.52, 95% CI 0.66 to 2.38, p = 0.0016). CONCLUSIONS: Patients who were physically healthy and employed were generally more satisfied with their care. The similarity in communication styles of patients and providers had a greater impact on patient satisfaction for patients who were less physically healthy and not employed.

Redefining Quality Measurement in Cancer Care.

Quality measurement in oncology is increasing in significance as payment schemes shift from volume to value. As demand for quality measures increases, challenges in the development of quality measures, standardization across measures, and the limitations of health information technology have become apparent. Moreover, the time and financial burden associated with developing, tracking, and reporting quality measures are substantial. Despite these challenges, best practices and leaders in the field of quality measurement in oncology have emerged. To understand the current challenges and promising practices in quality measurement and to explore future considerations for measure development and measure reporting in oncology, NCCN convened the NCCN Policy Summit: Redefining Quality Measurement in Oncology. The summit included discussion of the current quality landscape and efforts to develop quality measures, use of quality measures in various programs, patient perspective of quality, and challenges and best practices for quality reporting.

Association of Broad-Based Genomic Sequencing With Survival Among Patients With Advanced Non-Small Cell Lung Cancer in the Community Oncology Setting.

Importance: Broad-based genomic sequencing is being used more frequently for patients with advanced non-small cell lung cancer (NSCLC). However, little is known about the association between broad-based genomic sequencing and treatment selection or survival among patients with advanced NSCLC in a community oncology setting. Objective: To compare clinical outcomes between patients with advanced NSCLC who received broad-based genomic sequencing vs a control group of patients who received routine testing for EGFR mutations and/or ALK rearrangements alone. Design, Setting, and Participants: Retrospective cohort study of patients with chart-confirmed advanced NSCLC between January 1, 2011, and July 31, 2016, and who received care at 1 of 191 oncology practices across the United States using the Flatiron Health Database. Patients were diagnosed with stage IIIB/IV or unresectable nonsquamous NSCLC who received at least 1 line of antineoplastic treatment. Exposures: Receipt of either broad-based genomic sequencing or routine testing (EGFR and/or ALK only). Broad-based genomic sequencing included any multigene panel sequencing assay examining more than 30 genes prior to third-line treatment. Main Outcomes and Measures: Primary outcomes were 12-month mortality and overall survival from the start of first-line treatment. Secondary outcomes included frequency of genetic alterations and treatments received. Results: Among 5688 individuals with advanced NSCLC (median age, 67 years [interquartile range, 41-85], 63.6% white, 80% with a history of smoking); 875 (15.4%) received broad-based genomic sequencing and 4813 (84.6%) received routine testing. Among patients who received broad-based genomic sequencing, 4.5% received targeted treatment based on testing results, 9.8% received routine EGFR/ALK targeted treatment, and 85.1% received no targeted treatment. Unadjusted mortality rates at 12 months were 49.2% for patients undergoing broad-based genomic sequencing and 35.9% for patients undergoing routine testing. Using an instrumental variable analysis, there was no significant association between broad-based genomic sequencing and 12-month mortality (predicted probability of death at 12 months, 41.1% for broad-based genomic sequencing vs 44.4% for routine testing; difference -3.6% [95% CI, -18.4% to 11.1%]; P = .63). The results were consistent in the propensity score-matched survival analysis (42.0% vs 45.1%; hazard ratio, 0.92 [95% CI, 0.73 to 1.11]; P = .40) vs unmatched cohort (hazard ratio, 0.69 [95% CI, 0.62 to 0.77]; log-rank P < .001). Conclusions and Relevance: Among patients with advanced non-small cell lung cancer receiving care in the community oncology setting, broad-based genomic sequencing directly informed treatment in a minority of patients and was not independently associated with better survival.

Testing violations of the exponential assumption in cancer clinical trials with survival endpoints.

Personalized cancer therapy requires clinical trials with smaller sample sizes compared to trials involving unselected populations that have not been divided into biomarker subgroups. The use of exponential survival modeling for survival endpoints has the potential of gaining 35% efficiency or saving 28% required sample size (Miller, 1983), making personalized therapy trials more feasible. However, the use of exponential survival has not been fully accepted in cancer research practice due to uncertainty about whether or not the exponential assumption holds. We propose a test for identifying violations of the exponential assumption using a reduced piecewise exponential approach. Compared with an alternative goodness-of-fit test, which suffers from inflation of type I error rate under various censoring mechanisms, the proposed test maintains the correct type I error rate. We conduct power analysis using simulated data based on different types of cancer survival distribution in the SEER registry database, and demonstrate the implementation of this approach in existing cancer clinical trials.

Associations Between End-of-Life Cancer Care Patterns and Medicare Expenditures.

BACKGROUND: The purpose of this study was to examine the extent to which patterns of intensive end-of-life care explain geographic variation in end-of-life care expenditures among cancer decedents. METHODS: Using the SEER-Medicare database, we identified 90,465 decedents who were diagnosed with cancer in 2004-2011. Measures of intensive end-of-life care included chemotherapy received within 14 days of death; more than 1 emergency department visit, more than 1 hospitalization, or 1 or more intensive care unit (ICU) admissions within 30 days of death; in-hospital death; and hospice enrollment less than 3 days before death. Using hierarchical generalized linear models, we estimated risk-adjusted expenditures in the last month of life for each hospital referral region and identified key contributors to variation in expenditures. RESULTS: The mean expenditure per cancer decedent in the last month of life was $10,800, ranging from $8,300 to $15,400 in the lowest and highest expenditure quintile areas, respectively. There was considerable variation in the percentage of decedents receiving intensive end-of-life care intervention, with 41.7% of decedents receiving intensive care in the lowest quintile of expenditures versus 57.9% in the highest quintile. Regional patterns of late chemotherapy or late hospice use explained only approximately 1% of the expenditure difference between the highest and lowest quintile areas. In contrast, the proportion of decedents who had ICU admissions within 30 days of death was a major driver of variation, explaining 37.6% of the expenditure difference. CONCLUSIONS: Promoting appropriate end-of-life care has the potential to reduce geographic variation in end-of-life care expenditures.

Systemic Anticancer Therapy and Overall Survival in Patients With Very Advanced Solid Tumors.

Importance: Two prominent organizations, the American Society of Clinical Oncology and the National Quality Forum (NQF), have developed a cancer quality metric aimed at reducing systemic anticancer therapy administration at the end of life. This metric, NQF 0210 (patients receiving chemotherapy in the last 14 days of life), has been critiqued for focusing only on care for decedents and not including the broader population of patients who may benefit from treatment. Objective: To evaluate whether the overall population of patients with metastatic cancer receiving care at practices with higher rates of oncologic therapy for very advanced disease experience longer survival. Design, Setting, and Participants: This nationwide population-based cohort study used Flatiron Health, a deidentified electronic health record database of patients diagnosed with metastatic or advanced disease, to identify adult patients (aged ≥18 years) with 1 of 6 common cancers (breast cancer, colorectal cancer, non-small cell lung cancer [NSCLC], pancreatic cancer, renal cell carcinoma, and urothelial cancer) treated at health care practices from 2015 to 2019. Practices were stratified into quintiles based on retrospectively measured rates of NQF 0210, and overall survival was compared by disease type among all patients treated in each practice quintile from time of metastatic diagnosis using multivariable Cox proportional hazard models with a Bonferroni correction for multiple comparisons. Data were analyzed from July 2021 to July 2023. Exposure: Practice-level NQF 0210 quintiles. Main Outcome and Measure: Overall survival. Results: Of 78 446 patients (mean [SD] age, 67.3 [11.1] years; 52.2% female) across 144 practices, the most common cancer types were NSCLC (34 201 patients [43.6%]) and colorectal cancer (15 804 patients [20.1%]). Practice-level NQF 0210 rates varied from 10.9% (quintile 1) to 32.3% (quintile 5) for NSCLC and 6.8% (quintile 1) to 28.4% (quintile 5) for colorectal cancer. No statistically significant differences in survival were observed between patients treated at the highest and the lowest NQF 0210 quintiles. Compared with patients seen at practices in the lowest NQF 0210 quintiles, the hazard ratio for death among patients seen at the highest quintiles varied from 0.74 (95% CI, 0.55-0.99) for those with renal cell carcinoma to 1.41 (95% CI, 0.98-2.02) for those with urothelial cancer. These differences were not statistically significant after applying the Bonferroni-adjusted critical P = .008. Conclusions and Relevance: In this cohort study, patients with metastatic or advanced cancer treated at practices with higher NQF 0210 rates did not have improved survival. Future efforts should focus on helping oncologists identify when additional therapy is futile, developing goals of care communication skills, and aligning payment incentives with improved end-of-life care.