Health Data Sharing Perspectives of Patients Receiving Care in CancerLinQ-Participating Oncology Practices

PURPOSE

CancerLinQ seeks to use data sharing technology to improve quality of care, improve health outcomes, and advance evidence-based research. Understanding the experiences and concerns of patients is vital to ensure its trustworthiness and success.

METHODS

In a survey of 1,200 patients receiving care in four CancerLinQ-participating practices, we evaluated awareness and attitudes regarding participation in data sharing.

RESULTS

Of 684 surveys received (response rate 57%), 678 confirmed cancer diagnosis and constituted the analytic sample; 54% were female, and 70% were 60 years and older; 84% were White. Half (52%) were aware of the existence of nationwide databases focused on patients with cancer before the survey. A minority (27%) indicated that their doctors or staff had informed them about such databases, 61% of whom indicated that doctors or staff had explained how to opt out of data sharing. Members of racial/ethnic minority groups were less likely to be comfortable with research (88% v 95%; P = .002) or quality improvement uses (91% v 95%; P = .03) of shared data. Most respondents desired to know how their health information was used (70%), especially those of minority race/ethnicity (78% v 67% of non-Hispanic White respondents; P = .01). Under half (45%) felt that electronic health information was sufficiently protected by current law, and most (74%) favored an official body for data governance and oversight with representation of patients (72%) and physicians (94%). Minority race/ethnicity was associated with increased concern about data sharing (odds ratio [OR], 2.92; P < .001). Women were less concerned about data sharing than men (OR, 0.61; P = .001), and higher trust in oncologist was negatively associated with concern (OR, 0.75; P = .03).

CONCLUSION

Engaging patients and respecting their perspectives is essential as systems like CancerLinQ evolve.

Challenges to Using Big Data in Cancer

Big data in healthcare can enable unprecedented understanding of diseases and their treatment, particularly in oncology. These data may include electronic health records, medical imaging, genomic sequencing, payor records, and data from pharmaceutical research, wearables, and medical devices. The ability to combine datasets and use data across many analyses is critical to the successful use of big data and is a concern for those who generate and use the data. Interoperability and data quality continue to be major challenges when working with different healthcare datasets. Mapping terminology across datasets, missing and incorrect data, and varying data structures make combining data an onerous and largely manual undertaking. Data privacy is another concern addressed by the Health Insurance Portability and Accountability Act, the Common Rule, and the General Data Protection Regulation. The use of big data is now included in the planning and activities of the FDA and the European Medicines Agency. The willingness of organizations to share data in a precompetitive fashion, agreements on data quality standards, and institution of universal and practical tenets on data privacy will be crucial to fully realizing the potential for big data in medicine.

Case studies for overcoming challenges in using big data in cancer

The analysis of big healthcare data has enormous potential as a tool for advancing oncology drug development and patient treatment, particularly in the context of precision medicine. However, there are challenges in organizing, sharing, integrating, and making these data readily accessible to the research community. This review presents five case studies illustrating various successful approaches to addressing such challenges. These efforts are CancerLinQ, the American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange, Project Data Sphere, the National Cancer Institute Genomic Data Commons, and the Veterans Health Administration Clinical Data Initiative. Critical factors in the development of these systems include attention to the use of robust pipelines for data aggregation, common data models, data de-identification to enable multiple uses, integration of data collection into physician workflows, terminology standardization and attention to interoperability, extensive quality assurance and quality control activity, incorporation of multiple data types, and understanding how data resources can be best applied. By describing some of the emerging resources, we hope to inspire consideration of the secondary use of such data at the earliest possible step to ensure the proper sharing of data in order to generate insights that advance the understanding and treatment of cancer.

Incidence of Severe Acute Respiratory Syndrome Coronavirus 2 and Subsequent Mortality in a Multisite Cohort of Patients With Cancer in the CancerLinQ Discovery Database

PURPOSE:

Understanding risks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and subsequent mortality among patients with cancer may help inform treatment decisions during the COVID-19 pandemic.

METHODS:

CancerLinQ is an electronic health record database from US oncology practices. We identified a cohort of patients with malignancy and 2+ encounters at CancerLinQ practices in the 12 months before the study period (January 1, 2020-January 31, 2021). We identified a SARS-CoV-2 subcohort as having a positive SARS-CoV-2 test or International Classification of Diseases, 10th Revision, code. We examined predictors of SARS-CoV-2 infection and mortality including sex, race, ethnicity, age, malignancy type, and prior therapy. Unadjusted and adjusted incidence rate ratios (aIRRs) and 95% CIs were estimated from Poisson regression models for SARS-CoV-2 infections and mortality.

RESULTS:

The cancer cohort included 629,128 patients, and the SARS-CoV-2 subcohort included 12,300 patients. Higher incidence of SARS-CoV-2 was seen among patients who were male (incidence rate ratio [IRR], 1.14; 95% CI, 1.10 to 1.18), Black (IRR, 1.48; 95% CI, 1.41 to 1.56), Hispanic (IRR, 2.02; 95% CI, 1.91 to 2.14), age < 50 years (IRR, 1.34; 95% CI, 1.26 to 1.42), with hematologic malignancies (IRR, 1.07; 95% CI, 1.02 to 1.12), and with recent chemotherapy (IRR, 1.30, 95% CI, 1.22 to 1.40). In the adjusted analysis, higher incidence was seen in patients who were male (aIRR, 1.17; 95% CI, 1.13 to 1.21), Hispanic (aIRR, 2.01; 95% CI, 1.88 to 2.14), and with recent chemotherapy (aIRR, 1.17; 95% CI, 1.09 to 1.25). There were 182 all-cause deaths within the SARS-CoV-2 subcohort. Higher mortality was seen among patients who were male (IRR, 1.39; 95% CI, 1.04 to 1.86), unknown race (IRR, 2.64; 95% CI, 1.42 to 4.91), other/unknown ethnicity (IRR, 1.99; 95% CI, 1.20 to 3.29), age 60-69 years (IRR, 2.76; 95% CI, 1.23 to 6.19), age 70-79 years (IRR, 5.28; 95% CI, 2.42 to 11.5), age 80+ years (IRR, 7.31; 95% CI, 3.31 to 16.1), or with recent chemotherapy (IRR, 1.52, 95% CI, 1.01 to 2.29). In the adjusted analysis, higher mortality was seen with increased age and receipt of chemotherapy.

CONCLUSION:

Patients with increased risk of SARS-CoV-2 infection must balance the competing risks of their cancer diagnosis/treatment and SARS-CoV-2 infection.

Reaching beyond maximum grade: progress and future directions for modernising the assessment and reporting of adverse events in haematological malignancies

Remarkable improvements in outcomes for many haematological malignancies have been driven primarily by a proliferation of novel therapeutics over the past two decades. Targeted agents, immune and cellular therapies, and combination regimens have adverse event profiles distinct from conventional finite cytotoxic chemotherapies. In 2018, a Commission comprising patient advocates, clinicians, clinical investigators, regulators, biostatisticians, and pharmacists representing a broad range of academic and clinical cancer expertise examined issues of adverse event evaluation in the context of both newer and existing therapies for haematological cancers. The Commission proposed immediate actions and long-term solutions in the current processes in adverse event assessment, patient-reported outcomes in haematological malignancies, toxicities in cellular therapies, long-term toxicity and survivorship in haematological malignancies, issues in regulatory approval from an international perspective, and toxicity reporting in haematological malignancies and the real-world setting. In this follow-up report, the Commission describes progress that has been made in these areas since the initial report.

Association of treatment-emergent symptoms identified by patient-reported outcomes with adjuvant endocrine therapy discontinuation

Many patients discontinue endocrine therapy for breast cancer due to intolerance. Identification of patients at risk for discontinuation is challenging. The minimal important difference (MID) is the smallest change in a score on a patient-reported outcome (PRO) that is clinically significant. We evaluated the association between treatment-emergent symptoms detected by worsening PRO scores in units equal to the MID with discontinuation. We enrolled females with stage 0-III breast cancer initiating endocrine therapy in a prospective cohort. Participants completed PROs at baseline, 3, 6, 12, 24, 36, 48, and 60 months. Measures included PROMIS pain interference, fatigue, depression, anxiety, physical function, and sleep disturbance; Endocrine Subscale of the FACT-ES; and MOS-Sexual Problems (MOS-SP). We evaluated associations between continuous PRO scores in units corresponding to MIDs (PROMIS: 4-points; FACT-ES: 5-points; MOS-SP: 8-points) with time to endocrine therapy discontinuation using Cox proportional hazards models. Among 321 participants, 140 (43.6%) initiated tamoxifen and 181 (56.4%) initiated aromatase inhibitor (AI). The cumulative probability of discontinuation was 23% (95% CI 18-27%) at 48 months. For every 5- and 4-point worsening in endocrine symptoms and sleep disturbance respectively, participants were 13 and 14% more likely to discontinue endocrine therapy respectively (endocrine symptoms HR 1.13, 95% CI 1.02-1.25, p = 0.02; sleep disturbance HR 1.14, 95% CI 1.01-1.29, p = 0.03). AI treatment was associated with greater likelihood of discontinuation than tamoxifen. Treatment-emergent endocrine symptoms and sleep disturbance are associated with endocrine therapy discontinuation. Monitoring for worsening scores meeting or exceeding the MID on PROs may identify patients at risk for discontinuation.

Cancer Registry Data Linkage of Electronic Health Record Data From ASCO's CancerLinQ: Evaluation of Advantages, Limitations, and Lessons Learned

PURPOSE

To evaluate the completeness of information for research and quality assessment through a linkage between cancer registry data and electronic health record (EHR) data refined by ASCO's health technology platform CancerLinQ.

METHODS

A probabilistic data linkage between Iowa Cancer Registry (ICR) and an Iowa oncology clinic through CancerLinQ data was conducted for cases diagnosed between 2009 and 2018. Demographic, cancer, and treatment variables were compared between data sources for the same patients, all of whom were diagnosed with one primary cancer. Treatment data and compliance with quality measures were compared among those with breast or prostate cancer; SEER-Medicare data served as a comparison. Variables captured only in CancerLinQ data (smoking, pain, and height/weight) were evaluated for completeness.

RESULTS

There were 6,175 patients whose data were linked between ICR and CancerLinQ data sets. Of those, 4,291 (70%) were diagnosed with one primary cancer and were included in analyses. Demographic variables were comparable between data sets. Proportions of people receiving hormone therapy (30% v 26%, P < .0001) or immunotherapy (22% v 12%, P < .0001) were significantly higher in CancerLinQ data compared with ICR data. ICR data contained more complete TNM stage, human epidermal growth factor receptor 2 testing, and Gleason score information. Compliance with quality measures was generally highest in SEER-Medicare data followed by the combined ICR-CancerLinQ data. CancerLinQ data contained smoking, pain, and height/weight information within one month of diagnosis for 88%, 52%, and 76% of patients, respectively.

CONCLUSION

Linking CancerLinQ EHR data with cancer registry data led to more complete data for each source respectively, as registry data provides definitive diagnosis and more complete stage information and laboratory results, whereas EHR data provide more detailed treatment data and additional variables not captured by registries.

Real-world clinical outcomes of patients with BRCA-mutated, human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer: a CancerLinQ® study

Purpose

To investigate real-world clinical outcomes in patients with BRCA-mutated (BRCAm), HER2-negative metastatic breast cancer (mBC) according to BRCA and hormone receptor (HR) status.

Methods

Patients diagnosed with HER2-negative mBC between 01 January 2010 and 31 December 2018 were retrospectively identified from the American Society of Clinical Oncology’s CancerLinQ Discovery® database. Time to first subsequent therapy or death (TFST) from date of mBC diagnosis and start of first-line treatment for mBC and overall survival (OS) from date of mBC diagnosis were investigated according to BRCA status (BRCAm, BRCA wild type [BRCAwt] or unknown BRCA [BRCAu]) and HR status (positive/triple negative breast cancer [TNBC]). Follow-up continued until 31 August 2019 (i.e. minimum of 8 months).

Results

3744 patients with HER2-negative mBC were identified (BRCAwt, n = 460; BRCAm, n = 83; BRCAu, n = 3201) (HR-positive, n = 2738). Median (Q1, Q3) age was 63.0 (54.0, 73.0) years. Median (95% confidence interval [CI]) TFST (months) from mBC diagnosis was as follows: HR-positive, 7.7 (5.0, 11.2), 8.3 (6.6, 10.2) and 9.4 (8.7, 10.1); TNBC, 5.4 (3.9, 12.4), 5.6 (4.7, 6.6) and 5.4 (5.0, 6.2) for BRCAm, BRCAwt and BRCAu, respectively. Median (95% CI) OS (months) was as follows: HR-positive, 41.1 (31.5, not calculable), 55.1 (43.5, 65.5) and 33.0 (31.3, 34.8); TNBC, 13.7 (11.1, not calculable), 14.4 (10.7, 17.0) and 11.7 (10.3, 12.8) for BRCAm, BRCAwt and BRCAu, respectively.

Conclusion

When stratified by HR status, TFST and OS were broadly similar for patients with HER2-negative mBC, irrespective of BRCA status. Further global real-world studies are needed to study outcomes of this patient population.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-022-06541-3.

Quantitating and assessing interoperability between electronic health records

OBJECTIVES

Electronic health records (EHRs) contain a large quantity of machine-readable data. However, institutions choose different EHR vendors, and the same product may be implemented differently at different sites. Our goal was to quantify the interoperability of real-world EHR implementations with respect to clinically relevant structured data.

MATERIALS AND METHODS

We analyzed de-identified and aggregated data from 68 oncology sites that implemented 1 of 5 EHR vendor products. Using 6 medications and 6 laboratory tests for which well-accepted standards exist, we calculated inter- and intra-EHR vendor interoperability scores.

RESULTS

The mean intra-EHR vendor interoperability score was 0.68 as compared to a mean of 0.22 for inter-system interoperability, when weighted by number of systems of each type, and 0.57 and 0.20 when not weighting by number of systems of each type.

DISCUSSION

In contrast to data elements required for successful billing, clinically relevant data elements are rarely standardized, even though applicable standards exist. We chose a representative sample of laboratory tests and medications for oncology practices, but our set of data elements should be seen as an example, rather than a definitive list.

CONCLUSIONS

We defined and demonstrated a quantitative measure of interoperability between site EHR systems and within/between implemented vendor systems. Two sites that share the same vendor are, on average, more interoperable. However, even for implementation of the same EHR product, interoperability is not guaranteed. Our results can inform institutional EHR selection, analysis, and optimization for interoperability.

Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality

PURPOSE

The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) requires eligible clinicians to report clinical quality measures (CQMs) in the Merit-Based Incentive Payment System (MIPS) to maximize reimbursement. To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS CQMs, EHR data aggregated by ASCO's CancerLinQ platform were analyzed.

MATERIALS AND METHODS

Using the CancerLinQ health technology platform, 19 Oncology MIPS (oMIPS) CQMs were evaluated to determine the presence of data elements (DEs) necessary to satisfy each CQM and the DE percent population with patient data (fill rates). At the time of this analysis, the CancerLinQ network comprised 63 active practices, representing eight different EHR vendors and containing records for more than 1.63 million unique patients with one or more malignant neoplasms (1.73 million cancer cases).

RESULTS

Fill rates for the 63 oMIPS-associated DEs varied widely among the practices. The average site had at least one filled DE for 52% of the DEs. Only 35% of the DEs were populated for at least one patient record in 95% of the practices. However, the average DE fill rate of all practices was 23%. No data were found at any practice for 22% of the DEs. Since any oMIPS CQM with an unpopulated DE component resulted in an inability to compute the measure, only two (10.5%) of the 19 oMIPS CQMs were computable for more than 1% of the patients.

CONCLUSION

Although EHR systems had relatively high DE fill rates for some DEs, underfilling and inconsistency of DEs in EHRs render automated oncology MIPS CQM calculations impractical.

Digital symptom monitoring with patient-reported outcomes in community oncology practices: A U.S. national cluster randomized trial

349527

Background: Symptoms are common during cancer care but often go undetected. Digital systems that elicit patient-reported outcomes (PRO) surveys may detect symptoms early and prompt clinicians to intervene, thereby alleviating suffering and averting complications. Methods: In a cluster-randomized trial, U.S.-based community oncology practices were randomized 1:1 to digital symptom monitoring with PRO surveys, or to usual care control. Patients receiving systemic treatment for metastatic cancer were eligible. At PRO practices, participants were invited to complete a weekly survey via web or automated telephone system for up to one year, including questions about nine common symptoms, performance status, and falls. Severe or worsening symptoms triggered electronic alerts to care team nurses, and reports showing longitudinal symptom data were available to oncologists at visits. Pre-specified secondary outcomes included impact on physical function, symptom control, and health-related quality of life (HRQL). The primary outcome of survival is not yet mature. Results: At 52 practices, 1,191 patients were eligible and enrolled (593 PRO; 598 control). Clinically meaningful benefits were experienced in physical function by 13.8% more patients with PRO versus control (P=0.009); symptom control by 16.1% (P=0.003); and HRQL by 13.4% (P=0.006). Mean changes from baseline were superior with PRO versus control for physical function (mean difference 2.47, 95% CI 0.41-4.53; P=0.02), symptom control (2.56, 0.95-4.17; P=0.002), and HRQL (2.43, 0.90-3.96; P=0.002). Patients completed 20,565/22,486 (91.5%) of expected weekly PRO surveys. Conclusions: Digital symptom monitoring during cancer treatment confers clinical benefits. Clinical trial information: NCT03249090.

Improving Cancer Data Interoperability: The Promise of the Minimal Common Oncology Data Elements (mCODE) Initiative

PURPOSE

Because of expanding interoperability requirements, structured patient data are increasingly available in electronic health records. Many oncology data elements (eg, staging, biomarkers, documentation of adverse events and cancer outcomes) remain challenging. The Minimal Common Oncology Data Elements (mCODE) project is a consensus data standard created to facilitate transmission of data of patients with cancer.

METHODS

In 2018, mCODE was developed through a work group convened by ASCO, including oncologists, informaticians, researchers, and experts in terminologies and standards. The mCODE specification is organized by 6 high-level domains: patient, laboratory/vital, disease, genomics, treatment, and outcome. In total, 23 mCODE profiles are composed of 90 data elements.

RESULTS

A conceptual model was published for public comment in January 2019 and, after additional refinement, the first public version of the mCODE (version 0.9.1) Fast Healthcare Interoperability Resources (FHIR) implementation guide (IG) was presented at the ASCO Annual Meeting in June 2019. The specification was approved for balloting by Health Level 7 International (HL7) in August 2019. mCODE passed the HL7 ballot in September 2019 with 86.5% approval. The mCODE IG authors worked with HL7 reviewers to resolve all negative comments, leading to a modest expansion in the number of data elements and tighter alignment with FHIR and other HL7 conventions. The mCODE version 1.0 FHIR IG Standard for Trial Use was formally published on March 18, 2020.

CONCLUSION

The mCODE project has the potential to offer tremendous benefits to cancer care delivery and research by creating an infrastructure to better share patient data. mCODE is available free from www.mCODEinitiative.org. Pilot implementations are underway, and a robust community of stakeholders has been assembled across the oncology ecosystem.

Summary of the 12 Most Common Cancers in the CancerLinQ Discovery (CLQD) Database

PURPOSE

In 2014, the ASCO developed CancerLinQ (CLQ), a health technology platform for oncology. The CLQ Discovery (CLQD) database was created to make data available for research and this paper provides a summary of this database.

METHODS

This study described the clinical and demographic characteristics of the 12 most common cancers in the CLQD database. We included patients with a new malignant tumor diagnosis between January 1, 2013, and December 31, 2018, of the following cancers: breast, lung and bronchus, prostate, colon and rectum, melanoma of the skin, bladder, non-Hodgkin lymphoma, kidney and renal pelvis, uterus, leukemia, pancreas, and thyroid. Patients with an in-situ diagnosis were excluded. Summary statistics and Kaplan-Meier survival estimates were calculated for each tumor.

RESULTS

From 2013 to 2018, 491,360 patients were diagnosed with the study tumors. Breast cancer (139,506) was the most common, followed by lung and bronchus (70,959), prostate (63,303), and colon and rectum (53,504). The median age at diagnosis (years) was 61, 68, 68, and 64 in breast, lung and bronchus, prostate, and colon and rectum cohorts, respectively. Compared to the SEER 5-year overall survival estimates for several tumor types were higher in the CLQD database, possibly because of incomplete mortality capture in electronic health records.

CONCLUSION

This paper presents the first description of the CLQD database since its inception. CLQ will continue to evolve over time, and the breadth and depth of this data asset will continue to grow. ASCO and CLQ's long-term goal is to improve the quality of patient care and create a sustainable database for oncology researchers. These results demonstrate that CLQ built a scalable database that can be used for oncology research.

Identification of Transgender People With Cancer in Electronic Health Records: Recommendations Based on CancerLinQ Observations

PURPOSE

Cancer prevalence and outcomes data, necessary to understand disparities in transgender populations, are significantly hampered because gender identity data are not routinely collected. A database of clinical data on people with cancer, CancerLinQ, is operated by the ASCO and collected from practices across the United States and multiple electronic health records.

METHODS

To attempt to identify transgender people with cancer within CancerLinQ, we used three criteria: (1) International Classification of Diseases 9/10 diagnosis (Dx) code suggestive of transgender identity; (2) male gender and Dx of cervical, endometrial, ovarian, fallopian tube, or other related cancer; and (3) female gender and Dx of prostate, testicular, penile, or other related cancer. Charts were abstracted to confirm transgender identity.

RESULTS

Five hundred fifty-seven cases matched inclusion criteria and two hundred and forty-two were abstracted. Seventy-six percent of patients with Dx codes suggestive of transgender identity were transgender. Only 2% and 3% of the people identified by criteria 2 and 3 had evidence of transgender identity, respectively. Extrapolating to nonabstracted data, we would expect to identify an additional four individuals in category 2 and an additional three individuals in category 3, or a total of 44. The total population in CancerLinQ is approximately 1,300,000. Thus, our methods could identify 0.003% of the total population as transgender.

CONCLUSION

Given the need for data regarding transgender people with cancer and the deficiencies of current data resources, a national concerted effort is needed to prospectively collect gender identity data. These efforts will require systemic efforts to create safe healthcare environments for transgender people.

Updated Results of TBCRC026: Phase II Trial Correlating Standardized Uptake Value With Pathological Complete Response to Pertuzumab and Trastuzumab in Breast Cancer

PURPOSE

Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake value corrected for lean body mass (SULmax) on 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) would predict pathologic complete response (pCR) to pertuzumab and trastuzumab (PT).

PATIENTS AND METHODS

Patients with stage II or III, estrogen receptor-negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percent change in SULmax by C1D15 predicting pCR is ≤ 0.65, with a one-sided type I error rate of 10%.

RESULTS

Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 22%. Receiver operator characteristic analysis of percent change in SULmax by C1D15 yielded an area under the curve of 0.72 (80% CI, 0.64 to 0.80; one-sided P = .12), which did not reject the null hypothesis. However, between patients who obtained pCR and who did not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 41.8%; P = .004) and SULmax reduction ≥ 40% was more prevalent (83% v 52%; P = .03; positive predictive value, 31%). Participants not obtaining a 40% reduction in SULmax by C1D15 were unlikely to obtain pCR (negative predictive value, 91%).

CONCLUSION

Although the primary objective was not met, early changes in SULmax predict response to PT in estrogen receptor-negative and HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate tailoring of therapy in this setting.

Recommendations for patient similarity classes: results of the AMIA 2019 workshop on defining patient similarity

Defining patient-to-patient similarity is essential for the development of precision medicine in clinical care and research. Conceptually, the identification of similar patient cohorts appears straightforward; however, universally accepted definitions remain elusive. Simultaneously, an explosion of vendors and published algorithms have emerged and all provide varied levels of functionality in identifying patient similarity categories. To provide clarity and a common framework for patient similarity, a workshop at the American Medical Informatics Association 2019 Annual Meeting was convened. This workshop included invited discussants from academics, the biotechnology industry, the FDA, and private practice oncology groups. Drawing from a broad range of backgrounds, workshop participants were able to coalesce around 4 major patient similarity classes: (1) feature, (2) outcome, (3) exposure, and (4) mixed-class. This perspective expands into these 4 subtypes more critically and offers the medical informatics community a means of communicating their work on this important topic.

Abstract PS7-66: Real-world clinical outcomes of patients with BRCA-mutated (BRCAm) HER2-negative metastatic breast cancer: A CancerLinQ® study

Background: Limited epidemiological data exist on the real-world outcomes in patients with BRCA-mutated (BRCAm), HER2− metastatic breast cancer (mBC). This study describes clinical outcomes in this population according to germline BRCA mutation (gBRCAm) and hormone receptor (HR) status. Methods: Patients diagnosed with HER2− mBC between January 1, 2010 and December 31, 2018 were retrospectively selected from the American Society of Clinical Oncology (ASCO)’s CancerLinQ Discovery® database. The primary objective was to describe, as a surrogate for progression-free survival, the time to first subsequent therapy or death (TFST; whichever came first), calculated from date of mBC diagnosis, according to gBRCAm status (gBRCAm, gBRCA wild-type [gBRCAwt] or unknown gBRCA [gBRCAu]) and HR status (+/−). TFST was also calculated from first-line systemic therapy initiation. The secondary objective was to describe overall survival (OS), calculated from date of mBC diagnosis. Kaplan-Meier medians and 95% confidence intervals (CIs) were estimated. Results: 3744 patients with HER2− mBC were identified (gBRCAwt, n=460; gBRCAm, n=83; gBRCAu, n=3201); 2738 patients were HR+. Median (Q1, Q3) age was 63.0 (54.0, 73.0) years. Median (95% CI) TFST (months), calculated from date of mBC diagnosis, was 9.2 (8.6, 9.9) in HR+ patients, 5.4 (5.1, 6.0) in HR− patients, and 7.1 (5.0, 9.2), 6.9 (6.1, 8.1) and 8.4 (7.9, 9.1) in gBRCAm, gBRCAwt and gBRCAu cohorts, respectively. Median (95% CI) OS (months) was 34.30 (32.70, 36.40) in HR+ patients, 12.0 (11.1, 13.3) in HR− patients, and 31.5 (23.1, 42.8), 34.7 (28.9, 44.5), 27.6 (26.1, 29.5) in gBRCAm, gBRCAwt and gBRCAu cohorts, respectively. Median TFST and OS stratified by both HR and BRCA mutation status are shown in Table 1.

Conclusions: When stratified by HR status, median TFST and OS were broadly similar for patients with mBC, regardless of BRCA mutation status, as captured in the CancerLinQ Discovery® database. Outcomes may have been affected by class of first-line treatment received in a time preceding poly (ADP-ribose) polymerase inhibitor introduction as a targeted treatment for BRCAm patients. Further studies will be required to support these findings. Funding: This study was funded by AstraZeneca.

Table 1. Median TFST and OSCohort TFST, n (events)a,bMedian TFST from mBC diagnosis, months (95% CI)Median TFST from first-line treatment initiation, months (95% CI)OS, n (events)aMedian OS, months(95% CI)gBRCAm, HR+(n=47)45 (40)7.7 (5.0, 11.2)6.6 (3.2, 9.0)47 (21)41.1 (31.5, NR)gBRCAm, HR−(n=29)20 (19)5.4 (3.9, 12.4)3.1 (2.2, 8.9)29 (18)13.7 (11.1, NR)gBRCAwt, HR+(n=296)277 (234)8.3 (6.6, 10.2)6.5 (5.7, 8.7)296 (128)55.1 (43.5, 65.5)gBRCAwt, HR−(n=130)113 (101)5.6 (4.7, 6.6)4.1 (3.4, 5.2)130 (91)14.4 (10.7, 17.0)gBRCAu, HR+(n=2395)2174 (1949)9.4 (8.7, 10.1)7.3 (6.9, 8.0)2395 (1431)33.0 (31.3, 34.8)gBRCAu, HR−(n=609)466 (425)5.4 (5.0, 6.2)4.2 (3.7, 4.6)609 (448)11.7 (10.3, 12.8)an refers to the number of patients at risk.bFor patients with no indication of a further line of therapy or death, TFST was censored at the last activity date.CI, confidence interval; gBRCAm, germline BRCA-mutated; gBRCAu, unknown germline BRCA mutation; gBRCAwt, germline BRCA wild-type; HR, hormone receptor; NR, not reached; OS, overall survival; TFST, time to first subsequent therapy or death.

Citation Format: Robert S Miller, Stella Mokiou, Aliki Taylor, Miao Jiang, Ping Sun, Susan McCutcheon. Real-world clinical outcomes of patients with BRCA-mutated (BRCAm) HER2-negative metastatic breast cancer: A CancerLinQ® study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-66.

Impact of Broadening Trial Eligibility Criteria for Patients with Advanced Non-Small Cell Lung Cancer: Real-World Analysis of Select ASCO-Friends Recommendations

PURPOSE

Cancer clinical trials often accrue slowly or miss enrollment targets. Strict eligibility criteria are a major reason. Restrictive criteria also limit opportunities for patient participation while compromising external validity of trial results. We examined the impact of broadening select eligibility criteria on characteristics and number of patients eligible for trials, using recommendations of the American Society of Clinical Oncology (ASCO) and Friends of Cancer Research.

EXPERIMENTAL DESIGN

A retrospective, observational analysis used electronic health record data from ASCO's CancerLinQ Discovery database. Study cohort included patients with advanced non-small cell lung cancer treated from 2011 to 2018. Patients were grouped by traditional criteria [no brain metastases, no other malignancies, and creatinine clearance (CrCl) ≥ 60 mL/minute] and broadened criteria (including brain metastases, other malignancies, and CrCl ≥ 30 mL/minute).

RESULTS

The analysis cohort included 10,500 patients. Median age was 68 years, and 73% of patients were White. Most patients had stage IV disease (65%). A total of 5,005 patients (48%) would be excluded from trial participation using the traditional criteria. The broadened criteria, however, would allow 98% of patients (10,346) to be potential participants. Examination of patients included by traditional criteria (5,495) versus those added (4,851) by broadened criteria showed that the number of women, patients aged 75+ years, and those with stage IV cancer was significantly greater using broadened criteria.

CONCLUSIONS

This analysis of real-world data demonstrated that broadening three common eligibility criteria has the potential to double the eligible patient population and include trial participants who are more representative of those encountered in practice.See related commentary by Giantonio, p. 2369.

Disproportionate impact of COVID-19 disease among racial and ethnic minorities in the U.S. cancer population as seen in CancerLinQ Discovery data

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Background: Patients with cancer may face difficult care decisions during the COVID-19 outbreak in the US. Understanding COVID-19 risk factors may help patients and oncologists identify high-risk patients and plan for the best cancer treatment in a timely fashion. This analysis provides an assessment of racial and ethnic risk factors for COVID-19 disease within the CancerLinQ (CLQ) Discovery database. Methods: CLQ is a health technology platform developed by ASCO, which collects and aggregates longitudinal electronic health record (EHR) data from oncology practices throughout the United States. Patients with a diagnosis of a malignant neoplasm and at least two encounters in the past year at a reporting CLQ practice were defined as the underlying cancer patient population at risk for SARS-CoV-2 infection. COVID-19 cases were identified via a positive RT-PCR test for SARS-CoV-2 RNA and/or an ICD-10 code for coronavirus (e.g., B97.29, U07.1, or U07.2). Relative risks and 95% CI were calculated using SAS. Results: We identified 232,428 patients with cancer. From 1/1/2020-4/30/2020, we identified 223 COVID-19 cases in patients with cancer. Of these, 203 had a positive RT-PCR, 26 had an ICD-10 diagnosis code for SARS-CoV-2, and 6 had both. SARS-CoV-2 cases were identified from 19 of the 35 CLQ practices (52.8%) reporting data during the study period. Compared to white patients, African Americans were approximately 2 times more likely to have COVID-19 disease (RR = 1.95; 95% CI = 1.40-2.71), and Hispanics were more than 4 times more likely (RR = 4.65; 95% CI = 3.36-6.43). Patients with hematologic cancers were 1.5 times as likely to be diagnosed with COVID-19 (RR = 1.53; 95% CI = 1.09-2.16) compared to patients with solid tumors. At the time of this abstract, 10 patients (4.5%) died. Conclusions: These results are based on data from a sample of CLQ practices and represent an initial analysis of COVID-19 in the CLQ population. The elevated risk for COVID-19 among African Americans and Hispanics with cancer is noteworthy, particularly since these patients often suffer poorer cancer outcomes. The elevated risk among patients with hematologic cancers is also worth noting because these patients often have compromised immune systems and are already susceptible to many other types of infection. Because the US is in the midst of an active outbreak, we are continuing to analyze new cases and additional risk factors, such as geographical location, anti-cancer treatments, and other cancer variables (e.g. stage).

Impact of curated data on electronic quality measure capture rates within CancerLinQ

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Background: Accurate calculation of key quality measures is critical for informing high-quality, value-based cancer care that is consistent with clinical guidelines. The American Society of Clinical Oncology (ASCO)’s CancerLinQ enables oncology organizations around the US to view near-real time quality measure dashboards sourced from structured electronic medical record (EMR) data; however, use of structured data in key fields is highly variable. Unstructured content, such as progress notes, contains important clinical information on treatment and disease status, which can then undergo curation. This process involves trained data abstractors searching for key data elements through a combination of manual review and natural language processing (NLP) to extract structured data from unstructured content. We hypothesize inclusion of curated data substantially augments structured data alone by more accurately representing the patient journey, thus improving validity of quality measures across EMRs. Methods: A total of 96,399 records across 57,232 patients from 4 EMRs vendors were analyzed from 2018-2019 across structured EMR and curated data. Each record represents 1 of 7 key data elements used to calculate the Staging Documented within One Month of First Office Visit quality measure. Structured documentation of these data elements determines if a patient is concordant with the measure, meaning they were staged within 31 days of their first visit after diagnosis, or non-concordant, meaning they were not staged within the appropriate window. Results: More than a quarter of records from patients concordant or non-concordant with the measure (28.85%) had key data elements sourced from curation. In total, 33% of all records among concordant patients were sourced from curation. Relying on structured data alone would show only 67% concordance versus 97.5% concordance among curated records. This demonstrates that appropriate care may often be delivered but documentation may be missing in a significant fraction of structured EMR data, thus limiting accurate reporting capabilities. Conclusions: NLP-assisted curation can meaningfully supplement structured EMR data by providing a more accurate picture of care rendered, which can have substantial impacts on clinical care, quality reporting, and business operations. [Table: see text]

Development of CancerLinQ, a Health Information Learning Platform From Multiple Electronic Health Record Systems to Support Improved Quality of Care

PURPOSE

ASCO, through its wholly owned subsidiary, CancerLinQ LLC, developed CancerLinQ, a learning health system for oncology. A learning health system is important for oncology patients because less than 5% of patients with cancer enroll in clinical trials, leaving evidence gaps for patient populations not enrolled in trials. In addition, clinical trial populations often differ from the overall cancer population with respect to age, race, performance status, and other clinical parameters.

MATERIALS AND METHODS

Working with subscribing practices, CancerLinQ accepts data from electronic health records and transforms the local representation of a patient's care into a standardized representation on the basis of the Quality Data Model from the National Quality Forum. CancerLinQ provides this information back to the subscribing practice through a series of tools that support quality improvement. CancerLinQ also creates de-identified data sets for secondary research use.

RESULTS

As of March 2020, CancerLinQ includes data from 63 organizations across the United States that use nine different electronic health records. The database includes 1,426,015 patients with a primary cancer diagnosis, of which 238,680 have had additional information abstracted from unstructured content.

CONCLUSION

As CancerLinQ continues to onboard subscribing practices, the breadth of potential applications for a learning health care system widen. Future practice-facing tools could include real-world data visualization, recommendations for treatment of patients with actionable genetic variations, and identification of patients who may be eligible for clinical trials. Feeding these insights back into oncology practice ensures that we learn how to treat patients with cancer not just on the basis of the selective experience of the 5% that enroll in clinical trials, but from the real-world experience of the entire spectrum of patients with cancer in the United States.

Low rates of BRCA1 and BRCA2 testing for patients with ovarian cancer in ASCO's CancerLinQ, a real-world database

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Background: Ovarian cancer is the deadliest gynecological cancer and has limited screening options for early stage diagnosis. Genetic mutations in genes such as BRCA1 and BRCA2 increase the risk of ovarian cancer, and if identified, patients can undergo risk-reducing surgery. It is recommended and well accepted to test any new ovarian cancer patient for genetic mutations, particulary BRCA1 and BRCA2. If a BRCA1/2 mutation is found in a patient (somatic or germ line), this information can be used to guide therapy. We sought to analyze the characteristics of genetic testing in a real-world database, ASCO’s CancerLinQ. Methods: We performed a retrospective cohort study using the CancerLinQ Discovery database. Women with ovarian, fallopian tube, or primary peritoneal cancer were identified using ICD9 and ICD10 codes. We included patients diagnosed between 1/1/11 to 12/31/18 and age >18. We included all epithelial histologies including carcinosarcomas and excluded patients without a known histology. Results: Of the 2654 patients meeting inclusion criteria, 600 had been tested for a BRCA1/2 mutation (22.6%). Of those tested, 63% were stage III/IV, 14% stage I/II, and 21.8% an unknown stage. The majority of the histologies were serous (76%), followed by undifferentiated (21.2%). The majority of patients tested were white (69.9%), with 18.8% unknown, and 9.9% black. The rate of a positive BRCA1 or BRCA2 mutation in this population was 17.2%. Of the patients with a BRCA1/2 mutation, the majority had serous histology (87%), followed by 18.5% undifferentiated, and 3.9% transitional cell. The majority of the patients found to have a BRCA1/2 mutation were age >50 (57.3%). Conclusions: Since 2008 evidence-based guidelines have recommended that all ovarian cancer patients be tested for BRCA1 and BRCA2 mutations, but in this real-world database only 22.6% have a recorded test. Of those tested, we found a BRCA1 or BRCA2 mutation rate of 17.2%. Our data is limited by what is recorded in the database and may not represent the true number of patients tested because of data missing from the EHR; however, these percentages appear similar to previous studies. Not only is testing important for cancer prevention for family members of patients, it now impacts the type of treatments for which these patients are eligible. Since genetic testing remains low at only 22.6% in this population, significant opportunities exist to impact cancer prevention and treatment.

Identification of transgender people with cancer in electronic health records (EHR): Recommendations based on CancerLinQ observations

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Background: Data regarding people who are gender minorities are not well-captured in oncology practices or large cohorts. Given this, collection of cancer prevalence and outcomes data, which are necessary to understand disparities in this population, are significantly hampered. Real-world data may be the most readily available source to explore outcomes in transgender populations. A database of EHR data on people with cancer, CancerLinQ is housed by the American Society of Clinical Oncology and collected from nation-wide practices and multiple EHRs. Methods: In order to identify people with cancer who may be transgender within CancerLinQ, we used three criteria: 1. ICD 9/10 diagnosis (Dx) code indicating likely transgender or non-binary gender conforming status 2. Male gender and Dx of cervical, endometrial, ovarian, or Fallopian tube cancers 3. Female gender and Dx of prostate, testicular, or penile cancers . We reviewed medical records for gender, cancer diagnosis, Dx indicating transgender identity and surgical history of transition-related surgeries, in other words surgeries that align bodies with identities and constructed a de-identified dataset of people who met one of the three criteria listed above. People without evidence of transgender identity were assigned as: (1) likely Dx error, because the person had either (a) no cancer, (b) an alternate cancer Dx consistent with sex assigned at birth, or (c) a cancer not listed in the above criteria (e.g. lung); or (2) likely error in gender data, if the cancer Dx was confirmed, but gender data was not; or (3) unknown. Results: Of ~1.3 million records in CancerLinQ at time of case selection, 557 matched inclusion criteria and 242 were abstracted. 76% of patients with ICD9/10 gender related Dx codes had evidence confirming transgender identity. By contrast, only 2% and 3% of the people identified by criteria 2 and 3 had evidence of transgender identity, respectively. Conclusions: Given the need for data regarding transgender people with cancer and the deficiencies of current data resources, a national concerted effort is needed to broaden terminology in EHRs to include whether people are transgender or not as routine and required data elements, provided by patients at their discretion. [Table: see text]

Status Update on Data Required to Build a Learning Health System

Wide adoption of electronic health records (EHRs) has raised the expectation that data obtained during routine clinical care, termed "real-world" data, will be accumulated across health care systems and analyzed on a large scale to produce improvements in patient outcomes and the use of health care resources. To facilitate a learning health system, EHRs must contain clinically meaningful structured data elements that can be readily exchanged, and the data must be of adequate quality to draw valid inferences. At the present time, the majority of EHR content is unstructured and locked into proprietary systems that pose significant challenges to conducting accurate analyses of many clinical outcomes. This article details the current state of data obtained at the point of care and describes the changes necessary to use the EHR to build a learning health system.

The Effects of a Remote-based Weight Loss Program on Adipocytokines, Metabolic Markers, and Telomere Length in Breast Cancer Survivors: the POWER-Remote Trial

PURPOSE

We initiated a clinical trial to determine the proportion of breast cancer survivors achieving ≥5% weight loss using a remotely delivered weight loss intervention (POWER-remote) or a self-directed approach, and to determine the effects of the intervention on biomarkers of cancer risk including metabolism, inflammation, and telomere length.

EXPERIMENTAL DESIGN

Women with stage 0-III breast cancer, who completed local therapy and chemotherapy, with a body mass index ≥25 kg/m² were randomized to a 12-month intervention (POWER-remote) versus a self-directed approach. The primary objective was to determine the number of women who achieved at least 5% weight loss at 6 months. We assessed baseline and 6-month change in a panel of adipocytokines (adiponectin, leptin, resistin, HGF, NGF, PAI1, TNFα, MCP1, IL1β, IL6, and IL8), metabolic factors (insulin, glucose, lipids, hs-CRP), and telomere length in peripheral blood mononuclear cells.

RESULTS

From 2013 to 2015, 96 women were enrolled, and 87 were evaluable for the primary analysis; 45 to POWER-remote and 42 to self-directed. At 6 months, 51% of women randomized to POWER-remote lost ≥5% of their baseline body weight, compared with 12% in the self-directed arm [OR, 7.9; 95% confidence interval (CI), 2.6-23.9; P = 0.0003]; proportion were similar at 12 months (51% vs 17%, respectively, P = 0.003). Weight loss correlated with significant decreases in leptin, and favorable modulation of inflammatory cytokines and lipid profiles. There was no significant change in telomere length at 6 months.

CONCLUSIONS

A remotely delivered weight loss intervention resulted in significant weight loss in breast cancer survivors, and favorable effects on several biomarkers.

Next-Generation Sequencing and the Clinical Oncology Workflow: Data Challenges, Proposed Solutions, and a Call to Action

PURPOSE

Next-generation sequencing (NGS) of tumor and germline DNA is foundational for precision oncology, with rapidly expanding diagnostic, prognostic, and therapeutic implications. Although few question the importance of NGS in modern oncology care, the process of gathering primary molecular data, integrating it into electronic health records, and optimally using it as part of a clinical workflow remains far from seamless. Numerous challenges persist around data standards and interoperability, and clinicians frequently face difficulties in managing the growing amount of genomic knowledge required to care for patients and keep up to date.

METHODS

This review provides a descriptive analysis of genomic data workflows for NGS data in clinical oncology and issues that arise from the inconsistent use of standards for sharing data across systems. Potential solutions are described.

RESULTS

NGS technology, especially for somatic genomics, is well established and widely used in routine patient care, quality measurement, and research. Available genomic knowledge bases play an evolving role in patient management but lack harmonization with one another. Questions about their provenance and timeliness of updating remain. Potentially useful standards for sharing genomic data, such as HL7 FHIR and mCODE, remain primarily in the research and/or development stage. Nonetheless, their impact will likely be seen as uptake increases across care settings and laboratories. The specific use case of ASCO CancerLinQ, as a clinicogenomic database, is discussed.

CONCLUSION

Because the electronic health records of today seem ill suited for managing genomic data, other solutions are required, including universal data standards and applications that use application programming interfaces, along with a commitment on the part of sequencing laboratories to consistently provide structured genomic data for clinical use.

Development and testing of patient-reported outcome performance measures (PRO-PMs) for oncology practice

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Background: Symptom management is a cornerstone of quality oncology practice. ASCO established a Working Group to develop patient-reported outcome performance measures (PRO-PMs) for assessing symptom management. We describe multi-center testing funded by PCORI. Methods: Multi-stakeholder consensus and literature review identified 11 symptoms for testing as potential PRO-PMs. For these symptoms, questions from the NCI’s PRO-CTCAE tool were administered at 6 US academic and community oncology practices. Patients across cancer types completed questions electronically on days 5-15 of chemotherapy cycles. PRO-CTCAE mapped scores were dichotomized to delineate clinically meaningful thresholds (0-1 vs ≥2), and rates were tabulated between practices. Symptoms were selected to become PRO-PMs if clinically actionable and with prevalence ≥20%; between-practice variation was evaluated using χ2. Twelve candidate sociodemographic and clinical risk adjustment (RA) variables were evaluated via Akaike information criterion testing. Risk-adjusted PRO-PM rates were calculated using observed:expected ratios via generalized linear mixed modeling. Results: Among 653 enrolled patients, 607 (93%) completed questionnaires. Four of 11 symptoms met criteria for PRO-PM development: nausea, constipation, insomnia, pain. Four RA variables met inclusion criteria: age, gender, cancer type, insurance type. The Table shows raw and risk-adjusted rates of symptom burden (scores ≥2) for each PRO-PM across practices. Risk-adjustment yielded a modest impact on scores. Conclusions: Oncology PRO-PMs have been developed to quantify the burden of actionable symptoms at the practice level. Collection from patients is feasible. Further refinement is underway prior to submission for endorsement by the National Quality Forum.

[Table: see text]

Impact of broadening clinical trial eligibility criteria for advanced non-small cell lung cancer patients: Real-world analysis

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Background: Restrictive trial eligibility criteria limit data generalizability and patient opportunity to participate. We compared numbers and characteristics of patients (pts) eligible using traditional vs expanded criteria recommended by ASCO and Friends of Cancer Research. Methods: A retrospective, observational analysis used deidentified EHR data from ASCO’s CancerLinQ database. Study cohort included adult aNSCLC pts with ≥2 visits and ≥1 dose of systemic treatment post-advanced-disease diagnosis from 2011-2018. Recorded creatinine clearance (CrCl) or Cockcroft-Gault variables were required. Pts were grouped by traditional criteria (no brain metastases, no other malignancies and CrCl >60 mL/min) and expanded criteria (brain metastases and other malignancies allowed and CrCl >30 mL/min). Results: 10,500 pts were identified (Table). Median age 67.6 years [IQR 60.3-74.4]. 56% were male, and 65% white. 60% were Stage IV, 80% former or current smokers. 5005 (47.7%) pts were excluded by traditional exclusion criteria, while only 154 (1.5%) pts were excluded by expanded criteria. Expanded criteria patients were older (67.5 v 66.1, p<0.001); and more likely to be female (44% v 40%), Stage IV (60% v 55%), have non-squamous histology (47% v 45%), and never smokers (16% v 13%). Additional analysis is needed to differentiate treated/stable vs. active brain metastases. Conclusions: Use of the ASCO-Friends expanded criteria would enable nearly twice as many aNSCLC pts to be considered for trial participation (4,851 patients, 46.2%). Narrower criteria should only be used based on compelling scientific rationale for exclusion. [Table: see text]

Characteristics of patients receiving immune checkpoint inhibitors (ICI) in ASCO’s CancerLinQ

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Background: ICI’s have demonstrated significant clinical benefit since the first FDA approval in 2011 of ipilimumab for metastatic melanoma. Five additional ICI therapies have since been approved across several indications. The objectives of this study were to describe the clinical and demographic features of patients receiving ICI treatment along with utilization patterns in real-world settings. Methods: We conducted a retrospective, observational cohort study using statistically de-identified data from January 2011 to November 2018 in CancerLinQ, ASCO’s real-world oncology database, which now contains EHR data from 49 diverse oncology practices in the U.S. Adult patients diagnosed with any cancer type who received ≥1 dose of an ICI (see Table) and had ≥2 clinical visits were eligible for inclusion. Patients were excluded if they received an ICI prior to its first FDA approval date to avoid inclusion of clinical trial patients. Descriptive statistics were used to examine treatment patterns and clinical characteristics of patients receiving ICIs. Results: This analysis included 12,712 patients who received an ICI. Median patient age was 67.4 years [IQR 59.3, 75.3]; 58% were male. White race made up the highest percent (83%) of ICI patients, followed by Black race (9%) and Other (8%). The most common primary cancers at the start of treatment were lung cancer (36%), melanoma (8%), urothelial cancer (2%) and renal cell carcinoma (2%). Of the 8,444 patients with known disease stage, 5,446 (64%) had Stage IV cancer. Breakdown of ICI treatment patterns can be found in the accompanying table. Uptake of ICIs was the most rapid for nivolumab, which had the highest use (49%), followed by pembrolizumab for rapid adoption and use (30%). Conclusions: This analysis gives insights into patient characteristics and real-world treatment patterns for ICIs. ICIs were used most widely in males, lung cancer patients and patients with advanced disease. These baseline characteristics inform our analyses of ICI use in patients with autoimmune disease, also reported herein.[Table: see text]

Quantifying interoperability: An analysis of oncology practice electronic health record data variability

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Background: Implementation of electronic health records (EHRs) has engendered a large quantity of machine-readable data. However, different practices choose different EHR vendors and the same vendor product may be implemented differently at each practice. Motivated by the desire to facilitate appropriate integration of data, our goal was to describe and quantify the consistency and variation of structured data within EHRs. Methods: De-identified and aggregated CancerLinQ data from 47 practices regarding the standards and variability of structured data including race, diagnoses, encounters, cancer staging, selected cancer-relevant medications, lab values and biomarkers were analyzed. EHR represented included ARIA, MOSAIQ, Allscripts, Centricity, Epic, Intellidose, NextGen, and OncoEMR. Results: De-identified EHR implementations included 23 A, 12 B, C and 5 other vendors. Only 6 practices (13%) used non-standard race representation. All practices used ICD-9/10 for diagnoses. There was variability in coding of encounters. Sixteen practices always used CPT, 5 practices always used SNOMED CT and 26 practices used multiple standards. Multiple staging systems were used. An average of 48% (range 11%-; including patients staged more than once) of patient records included coded staging information. Only one practice used a standard (LOINC) for laboratory data. No standards were used for medications ordered/administered or biomarkers. The table shows the number of distinct names for selected lab tests, medications and biomarkers across systems. Conclusions: In this cross-sectional sample, standards are used consistently for diagnoses and encounter data, often for race and rarely for medications, laboratory tests or biomarkers.[Table: see text]

NCI and ASCO CancerLinQ collaboration to advance quality of cancer care and surveillance

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Background: The National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program curates population-based cancer data representing 34% of the US population. CancerLinQ is an ASCO initiative that collects and analyzes electronic health record (EHR) data to give oncologists opportunities to improve the quality of patient care. With the shared goal of understanding care delivery, NCI SEER and CancerLinQ launched a pilot linkage. Purpose: Establish data exchange between registries and oncology practices to a) provide clinicians with SEER data to more effectively evaluate care within their practices, and b) enhance ability of SEER registries to capture cancer-related data and facilitate compliance of legally mandated public health reporting requirements while supporting metrics for quality reporting to providers. Methods: The SEER Iowa Cancer Registry is developing bidirectional linkages with CancerLinQ practices. The initial pilot in Iowa establishes connectivity and a data pipeline to capture discrete data elements in EHRs. The linkage methods are securely conducted by IMS, an honest broker for the Registry and ASCO. Patterns of care will be evaluated in the matched patient population. Analysis of shared data elements will provide comparative validation of data captured electronically (EHR) and manually (abstraction). Enhancing the patient care quality through efficient utilization of shared data was paramount when selecting treatment-related Quality Oncology Practice Initiative (QOPI) measures for calculation focusing on breast (QPP 449, QPP 450) and prostate cancer (QPP 102, QPP 104). Results: Publicly available SEER data for cohort evaluation is available to providers via SEERLinQ. The two-way exchange data pipeline complies with reporting requirements. Validation of shared data elements, statistics for matched patients, improved data completeness measures, and automated calculation of QOPI measures will be demonstrated. Conclusions: This collaboration builds an initial foundation of curated Registry-EHR linked data to automate cancer reporting to lower the physician burden, improve SEER evaluation of clinical care patterns, and enhance patient care quality.

Real-world characteristics and outcomes of patients with advanced non-small cell lung cancer (aNSCLC) receiving immune checkpoint inhibitor

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Background: Immune Checkpoint Inhibitors (ICIs) were first approved for the treatment of aNSCLC in 2014, and since this time have seen rapid adoption in the marketplace. We sought to describe the characteristics of patients with aNSCLC receiving ICIs in the real-world, as well as to examine treatment patterns and outcomes in the time since initial ICI approval. Methods: We conducted a retrospective, observational cohort study using statistically de-identified data from January 2011 to November 2018 in CancerLinQ, ASCO’s real-world oncology database. Adult patients with a curated diagnosis of Stage III or IV NSCLC who received ≥1 dose of an ICI and had ≥2 clinical visits were eligible for inclusion. Stage III patients were excluded if they received any local therapy < 1 year prior to receiving ICI. Patients were also excluded if they received ICI prior to the first FDA approval date. Demographic and clinical characteristics of aNSCLC patients receiving ICI are reported. Outcomes including time to treatment discontinuation (TTD), time to next treatment (TTNT), real-world progression free survival (rwPFS) and overall survival (OS) were examined via the Kaplan Meier method. Results: Among 2,425 aNSCLC ICI patients included in this analysis, median age was 68.0 years (IQR 60.7, 75.2], 54% were male and 73% of patients were white. Non-squamous histology accounted for 64% of aNSCLC ICI users, and 81% had Stage IV disease. Eastern Cooperative Oncology Group (ECOG) performance status was 0-1 in 77% and 2+ in 23% of patients, and 70% were current or former smokers. The majority (75%) of patients received ICI as second-line or later therapy. Treatment outcomes and survival are reported in the Table. Conclusions: This analysis demonstrates that aNSCLC patients receiving ICI therapy in the real-world are older than what was reported in some clinical trials, though survival outcomes were similar. Further research to examine impact of covariates on outcomes is warranted. [Table: see text]

Real-world prevalence of autoimmune disease (AD) among patients (pts) receiving immune checkpoint inhibitors (ICI) in ASCO’s CancerLinQ database

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Background: Although pts with AD are routinely excluded from ICI clinical trials, evidence suggests they may be receiving ICI therapy once approved. We sought to understand the prevalence of AD among all pts receiving ICIs in real world clinical care, as well as in advanced non-small cell lung cancer (aNSCLC) alone, and to describe the characteristics of ICI pts with and without evidence of AD. Methods: We conducted a retrospective, observational cohort study using statistically de-identified data from January 2011 to November 2018 in CancerLinQ, ASCO’s real-world oncology database. Adult pts who received ≥ 1 dose of an ICI and had ≥ 2 clinical visits were eligible for inclusion. A sub-analysis examining only aNSCLC pts was also carried out. To reduce the likelihood of capturing pts who may have been on a clinical trial, pts were excluded if they received the ICI prior to its first FDA approval date. AD status was determined by the presence of select ICD-9/ICD-10 codes or a medication used to treat autoimmune disease (including steroids) prior to ICI treatment start date. Symphony claims data were linked to CLQ via tokenization to build out cohorts. Characteristics of pts with and without autoimmune disease were compared using Chi-square or Fisher’s exact tests. Results: Prevalence of AD was 23% (538/2425 pts) in the aNSCLC population and 27% (3407/12712 pts) in the all ICI patient population. Median age did not differ between AD pts and those with no evidence of AD (All ICI: 67.6 v 67.3 years; aNSCLC: 68.5 v 67.9). AD pts were more likely to be female (All ICI: 46% v 40%, p < 0.001; aNSCLC: 55% v 44%, p < 0.001). Among all ICI pts, AD pts were less likely to be Stage IV (62% v 65%) or to have melanoma (4.6% versus 8.7%) compared to pts with no evidence of AD. The most common ADs among all ICI and aNSCLC patients were glucocorticoid deficiency (6.3% and 3.9%), rheumatoid arthritis (4.2% and 5.8%), and sacroiliitis (2.7% and 3.9%), respectively. Conclusions: This analysis of real-world data finds that a large proportion of pts receiving ICI may have pre-existing AD. Further examination is warranted to examine how AD status may impact outcomes.

Hypertension and use of bevacizumab among patients treated in community settings

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Background: CancerLinQ Discovery (CLQD) is a real-world dataset (RWD) derived from electronic health records across the US. This analysis builds on the prior observation of cautioned use of bevacizumab (Bev) among older adults using Medicare claims data. The goals of this study are to estimate the prevalence and incidence of hypertension (HT) and blood pressure (BP) patterns among patients (pts) with breast cancer (BC) or lung cancer (LC) treated with Bev. Methods: The cohort consists of all BC and LC pts in the platform at the time of CLQD dataset creation. At least one administration of Bev was required for inclusion as was diagnosis date and date of first Bev use. Elevated BP was defined as > 140 mmHg for systolic and > 90 mmHg for diastolic BP; elevated and max BP within 90 days of first Bev and 120 after were calculated for each pt. Summary statistics and proportions were calculated within these subgroups: baseline HT, race, age, and ECOG performance status (PS). Results: Overall, 1941 pts with BC and 4590 pts with LC treated from 2005 to 2017 were included. Baseline characteristics included % female (99 BC, 48 LC); % white (71 BC, 81 LC); % age > 65 years (34 BC, 52 LC). PS was available for N = 2118; most pts were PS 0-1 (88% BC, 82% LC). At baseline, more than half of pts were hypertensive (57% BC, 52% LC). An increase of at least 10mmHg in systolic BP within 120 days of treatment occurred in over half of pts with a normal baseline BP (54% BC, 56% LC) and in one-third of those with baseline HT (34% BC, 32% LC.) A significant proportion experienced at least a 20mmHg increase in systolic BP among those normotensive (29% BC, 32% LC) or hypertensive at baseline (16% BC, 16% LC). A majority of pts > 65 years had at least one elevated BP prior to Bev treatment (81% BC, 72% LC) although there were no clinically significant differences in rates of post treatment HT by age, race or PS. Conclusions: RWD provides important insights regarding the use and safety of medications outside the clinical trial population. Bev administration among pts with baseline (or pre-existent) HT is common in these practices. BP elevation post Bev exposure is also common, particularly among those with normal BP at baseline.

Real-world outcomes of patients with advanced non-small cell lung cancer (aNSCLC) and autoimmune disease (AD) receiving immune checkpoint inhibitors (ICIs)

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Background: Anecdotal and early evidence suggest ICIs are being used in patients with advanced malignancies and history of AD, despite such patients being typically excluded from traditional clinical trials. We compared the outcomes of patients with or without AD, all of whom had ICI treatment for aNSCLC. Methods: We conducted a retrospective, observational cohort study using de-identified, curated data in ASCO’s CancerLinQ. Patients with Stage III or IV NSCLC who received ≥1 dose of an ICI and had ≥2 visits from Jan 2011 to Nov 2018 were included. AD status prior to ICI treatment was identified using ICD-9/ICD-10 codes or AD medications (including steroids). Symphony claims data were linked via tokenization to build cohorts. Time to treatment discontinuation (TTD), time to next treatment (TTNT), real-world progression-free survival (rwPFS) and overall survival (OS) were compared across the two cohorts using the log-rank test. Cox Proportional Hazards Model was used to adjust for covariates. Adverse events (AEs) were compared using Chi-Square and Fisher’s Exact Test. Active AD was defined as evidence of autoimmune disease in the year prior to starting ICIs. Results: Among 2425 patients with aNSCLC treated with ICIs, AD was present in 22% (N=538). Median OS in all patients was 12.4 months (95% CI 11.3-13.5). TTD, TTNT, rwPFS and OS did not differ between the two cohorts (Table). There was no association between AD status and outcomes. There was no increased incidence of AEs in the AD group; however a sub-analysis among patients with active AD showed higher rates of select AEs including endocrine, GI and blood disorders. Conclusions: This analysis demonstrates that patients with evidence of AD prior to receiving ICI have similar outcomes compared to patients with no evidence of AD. Further research is needed to better understand the impact of active AD on the risk of AEs and patient outcomes. [Table: see text]

Electronic but overly eclectic: Disciplined EHR data management is needed to automate MIPS reporting

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Background: Physician reimbursement for care delivered to Medicare beneficiaries fundamentally changed with the 2015 MACRA legislation, requiring eligible clinicians to report quality measures in the Merit-Based Incentive Payment System (MIPS). To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS results, EHR data ingested by ASCO’s CancerLinQ (CLQ) was analyzed. Methods: Nineteen MIPS measures specified for medical oncology, including 8 shared by other specialties, were retrieved from qpp.cms.gov and systematically evaluated to determine data elements necessary to satisfy each measure. The existence of corresponding data fields and completion of these fields with clinical data was analyzed according to EHR implementation in de-identified and aggregated CLQ data. Results: Five clinician informaticists reviewed the 19 oncology MIPS measures, and identified a consensus list of 52 discrete EHR data elements (DEs) that would be needed. CLQ-processed data from 4 commercial EHR systems implemented at 47 CLQ practices found structured data fields for 84% (43 of 52) of the DE, but fewer than half (46%) of these fields were ever populated and only 32% (17 of 52) of DE were recorded for > 20% of cases. Only 3-5 of 19 MIPS measures could be reliably reported based on data element availability by most practices in this sample set. There were minimal differences between the EHRs ability to encode MIPS DE. Elements most likely to be encoded were those for registration (birthdate, gender), billing (diagnosis, meds), vital signs and smoking status, while those seldom or never encoded related to care plans (tobacco, alcohol, pain management). Other DE rarely encoded were patient events occurring outside the oncology practice (receipt/completion of consultations, dates of hospice enrollment and death), which would be dependent on data exchange between work units and practice entities or, more likely, re-entry by oncology practices. Conclusions: Only a minority of DE required to satisfy MIPS criteria are available as discrete data fields in current EHRs, limiting automated reporting efforts. Improved data quality and completeness is needed to satisfy mandated reporting.

TBCRC026: Phase II Trial Correlating Standardized Uptake Value With Pathologic Complete Response to Pertuzumab and Trastuzumab in Breast Cancer

PURPOSE

Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake values corrected for lean body mass (SULmax) on [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography would predict pathologic complete response (pCR) to neoadjuvant pertuzumab and trastuzumab (PT).

PATIENTS AND METHODS

Patients with stage II/III, estrogen receptor-negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. [¹⁸F]Fluorodeoxyglucose positron emission tomography/computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percentage of change in SULmax by C1D15 predicting pCR is less than or equal to 0.65, with a one-sided type I error rate of 10%.

RESULTS

Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 34%. Receiver operating characteristic analysis yielded an area under the curve of 0.76 (90% CI, 0.67 to 0.85), which rejected the null hypothesis. Between patients who obtained pCR versus not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 33.5%; P < .001), an SULmax reduction greater than or equal to 40% was more prevalent (86% v 46%; P < .001; negative predictive value, 88%; positive predictive value, 49%), and a significant difference in median C1D15 SULmax (1.6 v 3.9; P < .001) and higher proportion of C1D15 SULmax less than or equal to 3 (93% v 38%; P < .001; negative predictive value, 94%; positive predictive value, 55%) were observed.

CONCLUSION

Early changes in SULmax predict response to four cycles of PT in estrogen receptor-negative, HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate a more tailored approach to therapy in this setting.

Assessment and Stratification of High-Impact Data Elements in Electronic Clinical Quality Measures: A Joint Data Quality Initiative Between CancerLinQ® and Cancer Treatment Centers of America

PURPOSE

A joint data quality initiative between the Cancer Treatment Centers of America and the ASCO big data health technology platform CancerLinQ® was initiated to document and codify the steps taken to evaluate, stratify, and determine the potential effect of data elements used for electronic clinical quality measures as captured within structured fields in electronic health records.

METHODS

The processes involved the identification of clinical concepts required in measure population criteria and then to map these to the corresponding components of the CancerLinQ data model. A quantitative assessment of mappings between electronic clinical quality measure clinical concepts and attributes from the CancerLinQ clinical database was performed. In parallel, a qualitative analysis of high-impact data elements from the Cancer Treatment Centers of America clinical measures was made using local, expert consensus.

RESULTS

An impact assessment was derived using a count of the data elements across measures and the specific population criteria affected.

CONCLUSION

A list of putative high-impact data elements can provide guidance for clinicians to facilitate specific data element capture related to quality metrics in an electronic environment.

Beyond maximum grade: modernising the assessment and reporting of adverse events in haematological malignancies

Tremendous progress in treatment and outcomes has been achieved across the whole range of haematological malignancies in the past two decades. Although cure rates for aggressive malignancies have increased, nowhere has progress been more impactful than in the management of typically incurable forms of haematological cancer. Population-based data have shown that 5-year survival for patients with chronic myelogenous and chronic lymphocytic leukaemia, indolent B-cell lymphomas, and multiple myeloma has improved markedly. This improvement is a result of substantial changes in disease management strategies in these malignancies. Several haematological malignancies are now chronic diseases that are treated with continuously administered therapies that have unique side-effects over time. In this Commission, an international panel of clinicians, clinical investigators, methodologists, regulators, and patient advocates representing a broad range of academic and clinical cancer expertise examine adverse events in haematological malignancies. The issues pertaining to assessment of adverse events examined here are relevant to a range of malignancies and have been, to date, underexplored in the context of haematology. The aim of this Commission is to improve toxicity assessment in clinical trials in haematological malignancies by critically examining the current process of adverse event assessment, highlighting the need to incorporate patient-reported outcomes, addressing issues unique to stem-cell transplantation and survivorship, appraising challenges in regulatory approval, and evaluating toxicity in real-world patients. We have identified a range of priority issues in these areas and defined potential solutions to challenges associated with adverse event assessment in the current treatment landscape of haematological malignancies.

A phase II study evaluating the efficacy of zoledronic acid in prevention of aromatase inhibitor-associated musculoskeletal symptoms: the ZAP trial

PURPOSE

Aromatase inhibitor-associated musculoskeletal symptoms (AIMSS) are common adverse events of AIs often leading to drug discontinuation. We initiated a prospective clinical trial to evaluate whether bisphosphonates are associated with reduced incidence of AIMSS.

METHODS

In the single-arm trial, the Zoledronic Acid Prophylaxis (ZAP) trial, we compared the incidence of AIMSS against historical controls from the Exemestane and Letrozole Pharmacogenomics (ELPh) trial. Eligible women were postmenopausal with stage 0-III breast cancer planning to receive adjuvant AIs. AIMSS was assessed using the Health Assessment Questionnaire and Visual Analog Scale over 12 months in both trials. Participants in the ZAP trial received zoledronic acid prior to initiating letrozole and after 6 months; ELPh participants included in the analysis were taking letrozole but not bisphosphonates. We analyzed patient-reported outcomes (PROs) and bone density in the ZAP trial using mixed-effects linear regression models and paired t tests, respectively.

RESULTS

From 2011 to 2013, 59 postmenopausal women enrolled in ZAP trial. All 59 (100%) women received baseline and 52 (88%) received 6-month zoledronic acid, and had similar characteristics to historical controls from the ELPh trial (n = 206). Cumulatively during the first year of AI, 37 and 67% of ZAP and ELPh participants reported AIMSS (p < 0.001), respectively. Within the ZAP trial, we did not observe significant changes in other PROs; however, we report improvements in bone mineral density.

CONCLUSIONS

Compared to historical controls, zoledronic acid administered concomitantly with adjuvant AIs was associated with a reduced incidence of AIMSS. A randomized controlled trial is required to confirm these findings.

Ovarian markers and irregular menses among women with type 1 diabetes in the Epidemiology of Diabetes Interventions and Complications study

OBJECTIVE

Women with type 1 diabetes have increased risk of infertility compared to women without diabetes even after adjustment for irregular menses, but aetiologies are incompletely understood. Our aim was to examine the prevalence of abnormalities in ovarian markers consistent with polycystic ovary syndrome in women with type 1 diabetes and associations with irregular menses and diabetes-specific variables.

DESIGN, PATIENTS AND MEASUREMENTS

We conducted a secondary analysis of women in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC), a randomized trial and observational follow-up of intensive insulin therapy for type 1 diabetes. We included women with anti-Müllerian hormone (AMH) measurements among women not using oral contraceptives (n = 187). Initial AMH and testosterone measures were performed between EDIC years 1 and 4. History of irregular menses was assessed annually.

RESULTS

The median age of women was 35 (interquartile ratio 29, 40) years; 133 (35%) had elevated AMH and 62 (17%) reported irregular menses. Twelve per cent of women had relative elevations in total testosterone. In multivariable models, lower insulin dosages were associated with higher AMH concentrations (P = .0027), but not diabetes duration, glycemic control, body mass index or irregular menses. Neither irregular menses nor diabetes-specific variables were associated with testosterone concentrations.

CONCLUSIONS

Among women with type 1 diabetes in their thirties, abnormalities in ovarian markers are common and not associated with irregular menses and thus may partially account for decreased fecundity in women with type 1 diabetes.

Abstract P3-12-02: Predictors of adherence to adjuvant endocrine therapy (ET) for early breast cancer (BC) in a prospective clinic-based cohort

Background: Adjuvant ET is associated with improved survival in women with hormone receptor-positive early BC. Nonetheless, more than a quarter of women are non-adherent or discontinue therapy early. We aimed to identify whether baseline characteristics and changes in weight and patient-reported outcomes (PRO) early during the course of ET are associated with medication adherence behavior (MAB) in a prospective cohort.

Methods: We enrolled women initiating or switching adjuvant ET for stage 0-III BC in a prospective clinic-based cohort. Participants completed PRO questionnaires at baseline, and 3, 6, and 12 months (mo) after initiating ET. PRO questionnaires included FACT-ES, the NIH PROMIS measures for pain interference, fatigue, depression, anxiety, physical function, and sleep disturbance, and the MOS Sexual Functioning Scale. MAB was assessed by the Medication Adherence Questionnaire (MAQ). MAB was defined as high (MAQ score=0), or medium/low (MAQ score&gt;0). Questionnaires were administered through the PatientViewpoint web-based interface. We tested changes in mean PRO scores from baseline to follow-up time points with paired t-tests. We explored associations between baseline characteristics, and changes in weight and PRO at 6 mo with MAB at 12 mo using Fisher's exact test, Wilcoxan rank sum tests and t-tests. P-values &lt;0.05 were considered significant.

Results: From March 2012 to December 2016, 336 women enrolled in the cohort. Mean age was 60 (range 26-90), 84% were Caucasian, and 67% were post-menopausal. Overall, 57% received an aromatase inhibitor, 43% received tamoxifen, and 28% received prior taxane chemotherapy. Median follow-up was 12 mo. At baseline, 61% were overweight/obese, and 21% gained &gt;5% of baseline weight by 12 mo. Mean baseline and follow-up scores at 3, 6 and 12 mo were within 1 standard deviation of reference population means for all PRO measures. Compared to baseline, endocrine symptoms were increased at 3, 6 and 12 mo (p&lt;0.05), while sexual function and depression did not differ between baseline and any follow-up time point (p&gt;0.05). At 6 mo, anxiety was reduced, physical function was improved and pain impact was reduced compared to baseline (p&lt;0.05). MAB was high for 71% of participants at 12 mo. Preliminary data demonstrate that, compared to those with high MAB at 12 mo, women with medium/low MAB at 12 mo took fewer concomitant medications at baseline, and had more improvement in anxiety and sexual function at 6 mo. MAB at 12 mo did not differ according to race, type of ET, baseline weight or PRO measures, or 6 mo change in weight or other PRO measures.

Conclusions: Early changes in anxiety and sexual function during the course of adjuvant ET and the number of baseline concomitant medications may separate women with subsequent high versus medium/low MAB risk. Weight loss interventions and symptom management are needed for women receiving adjuvant ET during the first year of treatment. Our data will be used to create a model to predict MAB for validation studies and as the basis to devise interventions to improve adherence to adjuvant ET.

Citation Format: Smith KL, Yeruva SLH, Blackford A, Huang C-Y, Westbrook KE, Harding BA, Smith A, Fetting J, Wolff AC, Jelovac D, Miller RS, Connolly R, Armstrong D, Nunes R, Visvanathan K, Stearns V. Predictors of adherence to adjuvant endocrine therapy (ET) for early breast cancer (BC) in a prospective clinic-based cohort [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-12-02.

Improving Oncology Quality Measurement in Accountable Care: Filling Gaps with Cross-Cutting Measures

Payment for health care services, including oncology services, is shifting from volume-based fee-for-service to value-based accountable care. The objective of accountable care is to support providers with flexibility and resources to reform care delivery, accompanied by accountability for maintaining or improving outcomes while lowering costs. These changes depend on health care payers, systems, physicians, and patients having meaningful measures to assess care delivery and outcomes and to balance financial incentives for lowering costs while providing greater value. Gaps in accountable care measure sets may cause missed signals of problems in care and missed opportunities for improvement. Measures to balance financial incentives may be particularly important for oncology, where high cost and increasingly targeted diagnostics and therapeutics intersect with the highly complex and heterogeneous needs and preferences of cancer patients. Moreover, the concept of value in cancer care, defined as the measure of outcomes achieved per costs incurred, is rarely incorporated into performance measurement. This article analyzes gaps in oncology measures in accountable care, discusses challenging measurement issues, and offers strategies for improving oncology measurement. Discern Health analyzed gaps in accountable care measure sets for 10 cancer conditions that were selected based on incidence and prevalence; impact on cost and mortality; a diverse range of high-cost diagnostic procedures and treatment modalities (e.g., genomic tumor testing, molecularly targeted therapies, and stereotactic radiotherapy); and disparities or performance gaps in patient care. We identified gaps by comparing accountable care set measures with high-priority measurement opportunities derived from practice guidelines developed by the National Comprehensive Cancer Network and other oncology specialty societies. We found significant gaps in accountable care measure sets across all 10 conditions. For each gap, we searched for available measures not already being used in programs. Where existing measures did not cover gaps, we recommended refinements to existing measures or proposed measures for development. We shared the results of the measure gap analysis with a roundtable of national experts in cancer care and oncology measurement. During a web meeting and an in-person meeting, the roundtable reviewed the gap analysis and identified priority opportunities for improving measurement. The group determined that overreliance on condition-specific process measures is problematic because of rapidly changing evidence and increasing personalization of cancer care. The group's primary recommendation for enhancing measure sets was to prioritize and develop effective cross-cutting measures that assess clinical and patient-reported outcomes, including shared decision making, care planning, and symptom control. The group also prioritized certain safety and structural measures to complement condition-specific process measures. Further, the group explored strategies for using clinical pathways and devising layered measurement approaches to improve measurement for accountable care. This article presents the roundtable's conclusions and recommendations for next steps.

DISCLOSURES

Funding for this project was provided by the National Pharmaceutical Council (NPC). Westrich and Dubois are employees of the NPC. Valuck is a partner with Discern Health. Blaisdell and Dugan are employed by Discern Health. McClellan reports fees for serving on the Johnson & Johnson Board of Directors. Dugan reports consulting fees from the National Committee for Quality Assurance and Pharmacy Quality Alliance. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article. Study concept and design were contributed by Blaisdell, Valuck, Dugan, and Westrich. Blaisdell took the lead in data collection, along with Valuck and Dugan, and data interpretation was performed by Valuck, Blaisdell, Westrich, and Dubois. The manuscript was written by Blaisdell, along with Valuck and Dugan, and revised by Valuck, Westrich, Miller, and McClellan.