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.

End-of-Life Systemic Oncologic Treatment in the Immunotherapy Era: The Role of Race, Insurance, and Practice Setting.

PURPOSE: Receipt of antineoplastic systemic treatment near end of life (EOL) has been shown to harm patient and caregiver experience, increase hospitalizations, intensive care unit and emergency department use, and drive-up costs; yet, these rates have not declined. To understand factors contributing to use of antineoplastic EOL systemic treatment, we explored its association with practice- and patient-level factors. METHODS: We included patients from a real-world electronic health record-derived deidentified database who received systemic therapy for advanced or metastatic cancer diagnosed starting in 2011 and died within 4 years between 2015 and 2019. We assessed use of EOL systemic treatment at 30 and 14 days before death. We divided treatments into three subcategories: chemotherapy alone, chemotherapy and immunotherapy in combination, and immunotherapy (with/without targeted therapy), and estimated conditional odds ratios (ORs) and 95% CIs for patient and practice factors using multivariable mixed-level logistic regression. RESULTS: Among 57,791 patients from 150 practices, 19,837 received systemic treatment within 30 days of death. We observed 36.6% of White patients, 32.7% of Black patients, 43.3% of commercially insured patients, and 37.0% of Medicaid patients received EOL systemic treatment. White patients and those with commercial insurance were more likely to receive EOL systemic treatment than Black patients or those with Medicaid. Treatment at community practices was associated with higher odds of receiving 30-day systemic EOL treatment than treatment at academic centers (adjusted OR, 1.51). We observed large variations in EOL systemic treatment rates across practices. CONCLUSION: In a large real-world population, EOL systemic treatment rates were related to patient race, insurance type, and practice setting. Future work should examine factors that contribute to this usage pattern and its impact on downstream care.[Media: see text].

Outcomes on an inpatient oncology service after the introduction of hospitalist comanagement.

BACKGROUND: Smilow Cancer Hospital (SCH) introduced hospitalist comanagement to the inpatient oncology service to address long lengths of stay and oncologist burnout. OBJECTIVE: To determine the impact of hospitalists on inpatient quality outcomes and oncologist experience. INTERVENTIONS: Hospitalists were introduced to one of two inpatient oncology services at SCH. Patients were assigned to teams equally based on capacity. Outcomes on the oncologist-led, traditional service (TS) were compared with outcomes on the hospitalist service (HS) 6 months after program implementation. MAIN OUTCOMES AND MEASURES: Outcomes included patient volume, length of stay (LOS), early discharge, discharge time, and 30-day readmission rate. Mixed linear or Poisson models that accounted for multiple admissions during the study duration were used. Oncologist experience was measured by survey. RESULTS: During the study period, there were 713 discharges, 400 from the HS and 313 from the TS (p = .0003). There was no difference in demographics or severity of illness (SOI) between services. Following adjustment for age, sex, race/ethnicity, cancer type, and discharge disposition, the average LOS was 4.71 on the HS and 5.47 on the TS (p = .01). Adjusted early discharge rate was 6.22% on the HS and 2.06% on the TS (p = .01). Adjusted mean discharge time was 3:45 p.m. on HS and 4:16 p.m. on TS (p = .009). There was no difference in readmission rates. Oncologists reported less stress (p = .001) and a better ability to manage competing responsibilities (p < .0001) while working on the HS. CONCLUSIONS: Hospitalist comanagement significantly improved LOS, early discharge, time of discharge, and oncologist experience without an increase in 30-day readmissions.

Systemic Anticancer Therapy at the End of Life-Changes in Usage Pattern in the Immunotherapy Era.

This cohort study evaluates the rate of systemic anticancer therapy use among patients dying of cancer.

Clinical Outcomes and Immune Markers by Race in a Phase I/II Clinical Trial of Durvalumab Concomitant with Neoadjuvant Chemotherapy in Early-Stage TNBC.

PURPOSE: The incidence of triple-negative breast cancer (TNBC) is higher among Black or African American (AA) women, yet they are underrepresented in clinical trials. To evaluate safety and efficacy of durvalumab concurrent with neoadjuvant chemotherapy for stage I-III TNBC by race, we enrolled additional AA patients to a Phase I/II clinical trial. PATIENTS AND METHODS: Our study population included 67 patients. The primary efficacy endpoint was pathologic complete response (pCR; ypT0/is, N0) rate. χ2 tests were used to evaluate associations between race and baseline characteristics. Cox proportional hazards models were used to assess association between race and overall survival (OS) and event-free survival (EFS). Multivariate logistic regression analyses were used to evaluate associations between race and pCR, immune-related adverse events (irAE) and recurrence. RESULTS: Twenty-one patients (31%) self-identified as AA. No significant associations between race and baseline tumor stage (P = 0.40), PD-L1 status (0.92), and stromal tumor-infiltrating lymphocyte (sTIL) count (P = 0.57) were observed. pCR rates were similar between AA (43%) and non-AA patients (48%; P = 0.71). Three-year EFS rates were 78.3% and 71.4% in non-AA and AA patients, respectively [HR, 1.451; 95% confidence interval (CI), 0.524-4.017; P = 0.474]; 3-year OS was 87% and 81%, respectively (HR, 1.72; 95% CI, 0.481-6.136; P = 0.405). The incidence of irAEs was similar between AA and non-AA patients and no significant associations were found between irAEs and pathologic response. CONCLUSIONS: pCR rates, 3-year OS and EFS after neoadjuvant immunotherapy and chemotherapy were similar in AA and non-AA patients. Toxicities, including the frequency of irAEs, were also similar.

Self-Reported COVID-19 Infections and Social Mixing Behavior at Oncology Meetings.

PURPOSE: The COVID-19 pandemic largely suspended in-person scientific meetings because of risk of disease spread. In the era of vaccination and social distancing practices, meetings have begun returning to in-person formats. We surveyed attendees and potential attendees of 2 oncology meetings in the United States to identify rates of mixing behavior and the subsequent rate of self-reported COVID-19 infection. METHODS AND MATERIALS: We collected via survey reported social mixing behavior and COVID-19 positivity (within 21 days of meeting conclusion) of actual and potential in-person attendees of the American Society of Clinical Oncology (ASCO) Quality Care Symposium held September 24 to 25, 2021, and the American Society for Radiation Oncology (ASTRO) Annual Meeting held October 24 to 27, 2021. Conference speakers and other participants were identified through publicly available meeting materials and targeted via e-mail when possible. Recruitment of additional attendees and potential attendees was also conducted through a sharable link promoted via oncology newsletters and social media. Descriptive statistics alone were performed owing to low COVID-19 event rates. RESULTS: Response rates from targeted conference participants with publicly available e-mails were 27.4% for the ASCO and 14.3% for the ASTRO meetings. The ASCO survey produced 94 responses (48 in-person attendees). The ASTRO survey produced 370 responses (267 in-person attendees). Across both meetings, 3 of 308 (1.0%) in-person attendees versus 2 of 141 (1.4%) nonattendees tested positive for COVID-19. Low COVID-19 positivity rates were reported among in-person attendees spending more (>20) versus fewer (≤20) hours attending live sessions (2.2% vs 0%) and among indoor social event participants versus nonparticipants (0.8% vs 1.9%). Attendees largely felt comfortable attending additional in-person meetings after experiencing ASCO (87.5%) or ASTRO (91.9%) and felt mask compliance was good or excellent at ASCO (100%) and ASTRO (94.6%) meetings. CONCLUSIONS: In-person meetings do not seem to be contributing to high rates of new COVID-19 infections in the setting of vaccine and social distancing mandates, supporting paths forward for at least partially in-person conferences as COVID-19 becomes endemic.

Impact of a Dedicated Cancer Urgent Care Center on Acute Care Utilization.

PURPOSE: Acute care imposes a significant burden on patients and cancer care costs. We examined whether an advanced practice provider-driven, cancer-specific urgent care center embedded within a large tertiary academic center decreased acute care use among oncology patients on active therapy. MATERIALS AND METHODS: We conducted a quasi-experimental study anchored around the Oncology Extended Care Clinic (OECC) opening date. We evaluated two parallel 4-month periods: a post-OECC period that followed a 5-month run-in phase, and the identical calendar period 1 year earlier. Our primary outcomes included all emergency department (ED) presentations and hospital admissions during the 3-month window following the index provider visit. We used Poisson models to calculate absolute pre-OECC v post-OECC rate differences. RESULTS: Our cohort included 2,095 patients in the pre-OECC period and 2,188 in the post-OECC period. We identified 32.6 ED visits/100 patients and 41.2 hospitalizations/100 patients in the pre-OECC period, versus 28.2 ED visits/100 patients and 26.1 hospitalizations/100 patients post-OECC. After adjusting for age, sex, race and ethnicity, and practice location, we observed a significant decrease of 4.6 ED visits/100 patients during the post-OECC period (95% CI, -8.92/100 to -0.28/100; P = .04) compared with the pre-OECC period. There was no significant association between the OECC opening and hospitalization rate (rate difference: -3.29 admissions/100 patients; 95% CI, -8.24/100 to 1.67/100; P = .19). CONCLUSION: Establishing a cancer-specific urgent care center was significantly associated with a modest decrease in emergency room utilization but not with hospitalization rate. Barriers included clinic capacity, patient awareness, and physician comfort with advanced practice provider autonomy. Optimizing workflow and standardizing clinical pathways can create benchmarks useful for value-based payments.

A Phase II Study Evaluating Orteronel, an Inhibitor of Androgen Biosynthesis, in Patients With Androgen Receptor (AR)-Expressing Metastatic Breast Cancer (MBC).

BACKGROUND: AR is a targetable pathway with AR modulation inhibiting estrogen- and androgen-mediated cell proliferation. Orteronel is an oral, selective, nonsteroidal inhibitor of 17, 20-lyase, a key enzyme in androgen biosynthesis. This study evaluated single-agent orteronel in AR+ metastatic breast cancer (MBC). METHODS: Male/female patients with AR+ MBC were grouped in Cohort 1: AR+ TNBC with l-3 prior chemotherapy regimens or Cohort 2: AR+ HR+ (estrogen [ER+]/ progesterone receptor [PR+] positive) HER2+/- with 1 to 3 prior hormonal and at least 1 prior chemotherapy regimen. Patients with HER2+ MBC must have received at least 2 lines of HER2-targeted therapy. Orteronel was administered at 300 mg BID; response rate was the primary endpoint. RESULTS: Seventy patients were enrolled (Cohort 1, n = 26 and Cohort 2, n = 44). Median treatment duration was 7.1 weeks. Seven patients were on treatment for ≥6 months. One of the 21 evaluated patients in Cohort 1 (4.8%) had an objective response. In Cohort 2, none of the first 23 patients to be evaluated had a response and accrual was stopped. Median progression-free and overall survival were 1.8 and 8.3 months, respectively. Toxicities were predominantly Grade 1 or 2 nausea/vomiting (36%) and fatigue (31%). Grade 3 or 4 events in ≥5% of patients included increased amylase/lipase (10%) and hypertension (6%). CONCLUSIONS: Orteronel demonstrated limited clinical activity in heavily pre-treated AR+ MBC. Further development of orteronel in MBC is not recommended. Further efforts to validate the AR as a therapeutic target should focus on identifying new markers predictive of sensitivity to AR-targeted agents.

Telehealth in Oncology: ASCO Standards and Practice Recommendations.

PURPOSE: To provide standards and practice recommendations specific to telehealth in oncology. METHODS: A systematic review of the literature on telehealth in oncology was performed, including the use of technologies and telecommunications systems, and other electronic methods of care delivery and sharing of information with patients. The evidence base was combined with the opinion of the ASCO Telehealth Expert Panel to develop telehealth standards and guidance. Public comments were solicited and considered in preparation of the final manuscript. RESULTS: The Expert Panel determined that general guidance on implementing telehealth across general and specialty settings has been published previously and these resources are endorsed. A systematic search for studies on topics specific to oncology resulted in the inclusion of two clinical practice guidelines, 12 systematic reviews, and six primary studies. STANDARDS AND GUIDANCE: Standards and guidance are provided for which patients in oncology can be seen via telehealth, establishment of the doctor-physician relationship, role of allied health professionals, role of advanced practice providers, multidisciplinary cancer conferences, and teletrials in oncology. Additional information is available at www.asco.org/standards.

Oncology Medical Home: ASCO and COA Standards.

PURPOSE: To provide Standards on the basis of evidence and expert consensus for a pilot of the Oncology Medical Home (OMH) certification program. The OMH model is a system of care delivery that features coordinated, efficient, accessible, and evidence-based care and includes a process for measurement of outcomes to facilitate continuous quality improvement. The OMH pilot is intended to inform further refinement of Standards for OMH model implementation. METHODS: An Expert Panel was formed, and a systematic review of the literature on the topics of OMH, clinical pathways, and survivorship care plans was performed using PubMed and Google Scholar. Using this evidence base and an informal consensus process, the Expert Panel developed a set of OMH Standards. Public comments were solicited and considered in preparation of the final manuscript. RESULTS: Three comparative peer-reviewed studies of OMH met the inclusion criteria. In addition, the results from 16 studies of clinical pathways and one systematic review of survivorship care plans informed the evidence review. Limitations of the evidence base included the small number of studies of OMH and lack of longer-term outcomes data. More data were available to inform the specific Standards for pathways and survivorship care; however, outcomes were mixed for the latter intervention. The Expert Panel concluded that in the future, practices should be encouraged to publish the results of OMH interventions in peer-reviewed journals to improve the evidence base. STANDARDS: Standards are provided for OMH in the areas of patient engagement, availability and access to care, evidence-based medicine, equitable and comprehensive team-based care, quality improvement, goals of care, palliative and end-of-life care discussions, and chemotherapy safety. Additional information, including a Standards implementation manual, is available at www.asco.org/standards.

Neoadjuvant durvalumab plus weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide in triple-negative breast cancer.

The goal of this Phase I/II trial is to assess the safety and efficacy of administering durvalumab concurrent with weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide (ddAC) neoadjuvant therapy for stages I-III triple-negative breast cancer. The primary endpoint is pathologic complete response (pCR:ypT0/is, ypN0). The response was correlated with PDL1 expression and stromal tumor-infiltrating lymphocytes (sTILs). Two dose levels of durvalumab (3 and 10 mg/kg) were assessed. PD-L1 was assessed using the SP263 antibody; ≥1% immune and tumor cell staining was considered positive; sTILs were calculated as the area occupied by mononuclear inflammatory cells over the total intratumoral stromal area. 59 patients were evaluable for toxicity and 55 for efficacy in the Phase II study (10 mg/kg dose). No dose-limiting toxicities were observed in Phase I. In Phase II, pCR rate was 44% (95% CI: 30-57%); 18 patients (31%) experienced grade 3/4 treatment-related adverse events (AE), most frequently neutropenia (n = 4) and anemia (n = 4). Immune-related grade 3/4 AEs included Guillain-Barre syndrome (n = 1), colitis (n = 2), and hyperglycemia (n = 2). Of the 50 evaluable patients for PD-L1, 31 (62%) were PD-L1 positive. pCR rates were 55% (95% CI: 0.38-0.71) and 32% (95% CI: 0.12-0.56) in the PD-L1 positive and negative groups (p = 0.15), respectively. sTIL counts were available on 52 patients and were significantly higher in the pCR group (p = 0.0167). Concomitant administration of durvalumab with sequential weekly nab-paclitaxel and ddAC neoadjuvant chemotherapy resulted in a pCR rate of 44%; pCR rates were higher in sTIL-high cancers.

Creating and Validating a Predictive Model for Suitability of Hospital at Home for Patients With Solid-Tumor Malignancies.

PURPOSE: Hospital at home (HaH) is a means of providing inpatient-level care at home. Selection of admissions potentially suitable for HaH in oncology is not well studied. We sought to create a predictive model for identifying admissions of patients with cancer, specifically solid-tumor malignancies, potentially suitable for HaH. METHODS: In this observational study, we analyzed admissions of patients with solid-tumor malignancies and unplanned admissions (January 1, 2015, to June 12, 2019) at an academic, urban cancer hospital. Potential suitability for HaH was the primary outcome. Admissions were considered potentially suitable if they did not involve escalation of care, rapid response evaluation, in-hospital death, telemetry, surgical procedure, consultation to a procedural service, advanced imaging, transfusion, restraints, and nasogastric tube placement. Admission source, patient demographics, vital signs, laboratory test results, comorbidities, admission and active cancer diagnoses, and recent hospital utilization were included as candidate variables in a multivariable logistic regression model. RESULTS: Of 3,322 admissions, 905 (27.2%) patients were potentially suitable for HaH. After variable selection in the derivation cohort (n = 1,097), thirteen factors predicted potential suitability: admission source; temperature and respiratory rate at presentation; hemoglobin; breast cancer, GI cancer, or malignancy of secondary or ill-defined origin; admission for genitourinary, musculoskeletal, or neurologic symptoms, intestinal obstruction or ileus, or evaluation of secondary malignancy; and emergency department visit in prior 90 days. Model c-statistics were 0.71 (95% CI, 0.68 to 0.75) and 0.63 (0.59 to 0.67) in the derivation and validation (n = 1,095) cohorts. CONCLUSION: Hospital admissions of patients potentially suitable for HaH may be identifiable using data available at admission.

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.

Cost-Effectiveness of Neoadjuvant-Adjuvant Treatment Strategies for Women With ERBB2 (HER2)-Positive Breast Cancer.

Importance: The neoadjuvant treatment options for ERBB2-positive (also known as HER2-positive) breast cancer are associated with different rates of pathologic complete response (pCR). The KATHERINE trial showed that adjuvant trastuzumab emtansine (T-DM1) can reduce recurrence in patients with residual disease compared with patients treated with trastuzumab; however, T-DM1 and other ERBB2-targeted agents are costly, and understanding the costs and health consequences of various combinations of neoadjuvant followed by adjuvant treatments in the United States is needed. Objective: To examine the costs and disease outcomes associated with selection of various neoadjuvant followed by adjuvant treatment strategies for patients with ERBB2-positive breast cancer. Design, Setting, and Participants: In this economic evaluation, a decision-analytic model was developed to evaluate various neoadjuvant followed by adjuvant treatment strategies for women with ERBB2-positive breast cancer from a health care payer perspective in the United States. The model was informed by the KATHERINE trial, other clinical trials with different regimens from the KATHERINE trial, the Flatiron Health Database, McKesson Corporation data, and other evidence in the published literature. Starting trial median age for KATHERINE patients was 49 years (range, 24-79 years in T-DM1 arm and 23-80 years in trastuzumab arm). The model simulated patients receiving 5 different neoadjuvant followed by adjuvant treatment strategies. Data analyses were performed from March 2019 to August 2020. Exposure: There were 4 neoadjuvant regimens: (1) HP: trastuzumab (H) plus pertuzumab (P), (2) THP: paclitaxel (T) plus H plus P, (3) DDAC-THP: dose-dense anthracycline/cyclophosphamide (DDAC) plus THP, (4) TCHP: docetaxel (T) plus carboplatin (C) plus HP. All patients with pCR, regardless of neoadjuvant regimen, received adjuvant H. Patients with residual disease received different adjuvant therapies depending on the neoadjuvant regimen according to the 5 following strategies: (1) neoadjuvant DDAC-THP followed by adjuvant H, (2) neoadjuvant DDAC-THP followed by adjuvant T-DM1, (3) neoadjuvant THP followed by adjuvant DDAC plus T-DM1, (4) neoadjuvant HP followed by adjuvant DDAC/THP plus T-DM1, or (5) neoadjuvant TCHP followed by adjuvant T-DM1. Main Outcomes and Measures: Lifetime costs in 2020 US dollars and quality-adjusted life-years (QALYs) were estimated for each treatment strategy, and incremental cost-effectiveness ratios were estimated. A strategy was classified as dominated if it was associated with fewer QALYs at higher costs than the alternative. Results: In the base-case analysis, costs ranged from $415 833 (strategy 3) to $518 859 (strategy 4), and QALYs ranged from 9.67 (strategy 1) to 10.73 (strategy 3). Strategy 3 was associated with the highest health benefits (10.73 QALYs) and lowest costs ($415 833) and dominated all other strategies. Probabilistic analysis confirmed that this strategy had the highest probability of cost-effectiveness (>70% at willingness-to-pay thresholds of $0-200,000/QALY) and was associated with the highest net benefit. Conclusions and Relevance: These results suggest that neoadjuvant THP followed by adjuvant H for patients with pCR or followed by adjuvant DDAC plus T-DM1 for patients with residual disease was associated with the highest health benefits and lowest costs for women with ERBB2-positive breast cancer compared with other treatment strategies considered.

Conducting Goals-of-Care Discussions Takes Less Time Than Imagined.

PURPOSE: To describe the length of encounter during visits where goals-of-care (GoC) discussions were expected to take place. METHODS: Oncologists from community, academic, municipal, and rural hospitals were randomly assigned to receive a coaching model of communication skills to facilitate GoC discussions with patients with newly diagnosed advanced solid-tumor cancer with a prognosis of < 2 years. Patients were surveyed after the first restaging visit regarding the quality of the GoC discussion on a scale of 0-10 (0 = worst; 10 = best), with ≥ 8 indicating a high-quality GoC discussion. Visits were audiotaped, and total encounter time was measured. RESULTS: The median face-to-face time oncologists spent during a GoC discussion was 15 minutes (range, 10-20 minutes). Among the different hospital types, there was no significant difference in encounter time. There was no difference in the length of the encounter whether a high-quality GoC discussion took place or not (15 v 14 minutes; P = .9). If there was imaging evidence of cancer progression, the median encounter time was 18 minutes compared with 13 minutes for no progression (P = .03). In a multivariate model, oncologist productivity, patient age, and Medicare coverage affected duration of the encounter. CONCLUSION: Oncologists can complete high-quality GoC discussions in 15 minutes. These data refute the common misperception that discussing such matters with patients with advanced cancer requires significant time.

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.

Adoption of Immune Checkpoint Inhibitors and Patterns of Care at the End of Life.

PURPOSE: As immune checkpoint inhibitors (ICIs) have transformed the care of patients with cancer, it is unclear whether treatment at the end of life (EOL) has changed. Because aggressive therapy at the EOL is associated with increased costs and patient distress, we explored the association between the Food and Drug Administration (FDA) approvals of ICIs and treatment patterns at the EOL. METHODS: We conducted a retrospective, observational study using patient-level data from a nationwide electronic health record-derived database. Patients had advanced melanoma, non-small-cell lung cancer (NSCLC; cancer types with an ICI indication), or microsatellite stable (MSS) colon cancer (a cancer type without an ICI indication) and died between 2013 and 2017. We calculated annual proportions of decedents who received systemic cancer therapy in the final 30 days of life, using logistic regression to model the association between the post-ICI FDA approval time and use of systemic therapy at the EOL, adjusting for patient characteristics. We assessed the use of chemotherapy or targeted/biologic therapies at the EOL, before and after FDA approval of ICIs using Pearson chi-square test. RESULTS: There was an increase in use of EOL systemic cancer therapy in the post-ICI approval period for both melanoma (33.9% to 43.2%; P < .001) and NSCLC (37.4% to 40.3%; P < .001), with no significant change in use of systemic therapy in MSS colon cancer. After FDA approval of ICIs, patients with NSCLC and melanoma had a decrease in the use of chemotherapy, with a concomitant increase in use of ICIs at the EOL. CONCLUSION: The adoption of ICIs was associated with a substantive increase in the use of systemic therapy at the EOL in melanoma and a smaller yet significant increase in NSCLC.

Patient and Family Caregiver Considerations When Selecting Early Breast Cancer Treatment: Implications for Clinical Pathway Development.

BACKGROUND: While clinical pathways have been widely adopted to decrease variation in cancer treatment patterns, they do not always incorporate patient and family caregiver perspectives. We identified shared patient and family caregiver considerations influencing treatment preferences/decision making to inform development of a shared decision pathway. METHODS: We conducted qualitative interviews with women who completed initial definitive treatment for stage I-III breast cancer and their family caregivers. As part of a broader interview, we asked participants what they considered when choosing a treatment option for themselves/their loved one. We coded transcribed interviews, analyzed patient and family caregiver datasets separately, and compared findings. Findings Patients' (n = 22) mean age was 55.7 years, whereas family caregivers' (n = 20) mean age was 59.5 years, with most (65%) being patients' spouses/partners. Considerations reported by both groups included cancer status, treatment issues, physical/psychosocial/family consequences, and provider/health care system issues. Data revealed three key tensions that arise during treatment decision making: (1) having enough information to set expectations but not so much as to be overwhelming; (2) balancing the highest likelihood of cure with potential physical/emotional/social/financial consequences of the chosen treatment; and (3) wanting to make data-driven decisions while having a personalized treatment plan. DISCUSSION: Patients and family caregivers identified several considerations of shared relevance reflecting different perspectives. Efforts to balance considerations can produce tensions that may contribute to decision regret if unaddressed. CONCLUSION: Clinical pathways can increase exposure to decision regret if treatment options are selected without consideration of patients' priorities. A shared decision pathway that incorporates patient-centeredness could facilitate satisfactory decision making.

A clinical pathway is a tool used by doctors and nurses to help them plan how they will take care of patients. Clinical pathways do not always include what is important to patients and their families. We spoke with patients with breast cancer and their family members. We wanted to learn what is important to them when they are making decisions about how the patient will be treated for cancer. They reported thinking about the kind of cancer the patient had and about pros and cons of different treatment choices. They also thought about how much is known about different treatment choices. Other patients' stories were important. Patients and family members wanted to know how a treatment would affect their bodies, feelings, normal roles in life, and families. They also thought about their relationship with their doctors and nurses and about how they would pay for their care. It was seen as hard to balance these things when making decisions. Patients and family members wanted to make decisions they would be happy with later. We will use this information to create a new clinical pathway. This tool will help patients with breast cancer, family members, doctors, and nurses work together to make the best decisions about the patient's cancer.