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

Treatment Intensification in Metastatic Hormone-Sensitive Prostate Cancer: An Analysis of Real-World Practice Patterns from the CancerLinQ Database

BACKGROUND

In metastatic hormone-sensitive prostate cancer (mHSPC), androgen deprivation therapy and standard of care treatment intensification with docetaxel and/or an androgen receptor signaling inhibitor (ARSI) are associated with improved survival outcomes for appropriate patients.

METHODS

This retrospective study selected patients with de novo mHSPC diagnosed between 2014 and 2023 from CancerLinQ Discovery®, a United States (US)-based, de-identified clinical database. Patient-level data, including clinical characteristics, treatments, and demographics, were collected from CancerLinQ. Treatment intensification was defined as the use of docetaxel, abiraterone, apalutamide, enzalutamide, or docetaxel plus abiraterone or darolutamide. Patient characteristics and treatment intensification data were analyzed descriptively and using multivariable logistic regression.

RESULTS

Of the 3,684 patients with mHSPC, the overall rate of treatment intensification was 58.4% but increased from 32.5% in 2014 to 67.5% in 2023. A relative decline in docetaxel use was accompanied by an increase in ARSI use. Black patients with mHSPC were less likely to receive treatment identification (OR 0.78, 95% CI 0.64-0.95, P = 0.013). Treatment intensification was also less likely for patients of older age and increased ECOG performance status. Despite increasing treatment intensification for Black patients with mHSPC over time, rates of docetaxel use are disproportionately declining relative to White patients.

CONCLUSIONS

Treatment intensification rates are increasing to include the majority of patients with mHSPC. However, treatment disparities exist for Black patients, who are less likely to receive intensification. These findings illustrate the importance of promoting treatment intensification in appropriate patients and addressing racial treatment disparities.

Seeking American Society of Clinical Oncology-Quality Oncology Practice Initiative (ASCO-QOPI) certification in a northern New England rural health system and cancer care network

In 2006 following several years of preliminary study, the American Society of Clinical Oncology (ASCO) launched the Quality Oncology Practice Initiative (QOPI). This cancer-focused quality initiative evolved considerably over the next decade-and-a-half and is expanding globally. QOPI is undoubtedly the leading standard-bearer for quality cancer care and contemporary medical oncology practice. The program garners attention and respect among federal programs, private insurers, and medical oncology practices across the nation. The MaineHealth Cancer Care Network (MHCCN) has undergone expansive growth since 2017. The network provides cancer care to more than 70% of the cases in Maine in a largely rural health system in Northern New England. In fall 2020, the MHCCN QOPI project leadership, following collaborative discussions with the ASCO-QOPI team, elected to proceed with a health system-cancer network-wide QOPI certification. Key themes emerged over the course of our two-year journey including: (1) Developing a highly interprofessional team committed to the project; (2) Capitalizing on a single electronic medical record for data transmission to CancerLinQ; (3) Prior experience, especially policy development, in other cancer-focused accreditation programs across the network; and (4) Building consensus through quarterly stakeholder meetings and awarding Continuing Medical Education (CME) and American Board of Medical Specialists (ABMS) Maintenance of Certification (MOC) credits to oncologists. All participants demonstrated a genuine spirit to work together to achieve certification. We report our successful journey seeking ASCO-QOPI certification across our network, which to our knowledge is the first-of-its-kind endeavor.

EGFR mutation testing, treatment and survival in stage I-III non-small cell lung cancer: CancerLinQ Discovery database retrospective analysis

Aim: To describe real-world biomarker testing, treatment and survival in stage IA-IIIC non-small cell lung cancer (NSCLC). Methods: Electronic records of USA-based patients in the CancerLinQ Discovery® database with stage IA-IIIC NSCLC (diagnosed between 2014 and 2018) were screened; a curated cohort of 14,452 records was identified for further analysis. Results: Of 3121 (21.6%) patients who had EGFR testing, 493 (15.8%) were EGFR-mutation positive. Of 974 patients who underwent surgical resection, 513 (52.7%) received adjuvant therapy. A quarter of patients with EGFR-mutation positive NSCLC received targeted adjuvant therapy. Conclusion: Approximately a fifth of patients underwent EGFR testing; biomarker testing is important to ensure optimal outcomes for patients with stage I-III NSCLC.

Natural History and Real-World Treatment Outcomes for Patients With NSCLC Having EGFR Exon 20 Insertion Mutation: An International Association for the Study of Lung Cancer-American Society of Clinical Oncology CancerLinQ Study

Introduction

EGFR exon 20 insertion (ex20ins) mutations account for approximately 10% of EGFR mutations in lung adenocarcinoma. Patients with ex20ins mutation do not respond to standard EGFR tyrosine kinase inhibitor therapy. In this work, we analyzed the characteristics, treatment patterns, and outcomes in this subgroup of patients with NSCLC.

Methods

The American Society of Clinical Oncology CancerLinQ Discovery data set was queried to identify patients with initial diagnosis of NSCLC between the years 1995 and 2018 and with EGFR ex20ins mutations. Data were extracted on patient demographics, tumor characteristics, treatments, and outcomes, and compared using chi-square and analysis of variance. Kaplan-Meier curves were generated to compare overall survival with log-rank tests. All analyses were performed using Python 3.6 (Python Software Foundation).

Results

A total of 357 patients were eligible. Patient characteristics include a median age of 68 years comprising female sex of 54%, White race of 63%, and Black race of 9%. Approximately 62% of total patients had stage 4 disease, and 30% of all patients had brain metastasis. There were 54% of patients who were treated with chemotherapy and 15% with immune checkpoint inhibitors (ICIs). In patients with brain metastasis, 16% were treated with ICI, 18% with targeted therapy, and 59% with chemotherapy. The median survival of the entire group was 23.8 months. Among patients with stage 4 disease (n = 222): 51% were women, 64% were white, 37% had brain metastasis, 18% were treated with ICI, 14% had targeted therapy, and 60% were treated with chemotherapy. Stage 4 patients treated with targeted therapy had better survival compared with those who did not receive targeted therapy (20.6 versus 16.1 mo, p = 0.02). Univariate and multivariate analyses suggested favorable outcomes for patients treated with immunotherapy.

Conclusions

EGFR ex20ins mutation represents a unique subset of NSCLC; it is associated with a higher propensity for brain metastases and a relatively modest overall survival. Novel treatment approaches are urgently needed to improve patient outcomes.

Real-world treatment patterns of adjuvant endocrine therapy and ovarian suppression in premenopausal HR+/HER2+ breast cancer

BACKGROUND

The optimal adjuvant endocrine therapy (ET) in hormone receptor positive (HR+) and human epidermal growth factor receptor 2 positive (HER2+) premenopausal breast cancer (BC) remains unclear. Moreover, the benefit and clinical indications of ovarian suppression (OS) is poorly elucidated. We described real-world patterns surrounding choice of ET and clinicopathologic features which predicted treatment with OS in a contemporary cohort of premenopausal women with HR+/HER2+ BC.

METHODS

This retrospective analysis included premenopausal patients with nonmetastatic HR+/HER2+ BC from the CancerLinQ Discovery database from January 2010 to May 2020. Women were less than 50 years and received chemotherapy, anti-HER2 therapy, and ET. They were categorized into 1 of 4 groups based on type of ET prescribed at initiation: aromatase inhibitor (AI) + OS, OS, tamoxifen + OS, or tamoxifen. Multivariable logistic regression assessed associations between clinicopathologic features and OS use.

RESULTS

Out of 360,540 patients with BC, 937 were included. The majority (n = 818, 87%) were prescribed tamoxifen, whereas 4 (0.4%), 50 (5.3%), and 65 (6.9%) received OS, tamoxifen + OS and AI + OS, respectively. No clinicopathologic features predicted OS use apart from age; patients <35 years were more likely to receive OS compared with those ≥35 years (odds ratio 2.33, p < 0.001).

CONCLUSIONS

This is the first real-world study evaluating ET treatment patterns in HR+/HER2+ premenopausal BC. OS use was uncommon and the majority received tamoxifen as the preferred ET regardless of most clinicopathologic risk factors. Additional research is needed to optimize ET decisions in young women with this distinct BC subtype.

Generating and using real-world data: A worthwhile uphill battle

The precision oncology paradigm challenges the feasibility and data generalizability of traditional clinical trials. Consequently, an unmet need exists for practical approaches to test many subgroups, evaluate real-world drug value, and gather comprehensive, accessible datasets to validate novel biomarkers. Real-world data (RWD) are increasingly recognized to have the potential to fill this gap in research methodology. Established applications of RWD include informing disease epidemiology, pharmacovigilance, and healthcare quality assessment. Currently, concerns regarding RWD quality and comprehensiveness, privacy, and biases hamper their broader application. Nonetheless, RWD may play a pivotal role in supplementing clinical trials, enabling conditional reimbursement and accelerated drug access, and innovating trial conduct. Moreover, purpose-built RWD repositories may support the extension or refinement of drug indications and facilitate the discovery and validation of new biomarkers. This perspective explores the potential of leveraging RWD to advance oncology, highlights its benefits and challenges, and suggests a path forward in this evolving field.

Prognosis and conditional survival among women with newly diagnosed ovarian cancer

OBJECTIVE

An important question in determining long-term prognosis for women with ovarian cancer is whether risk of death changes the longer a woman lives. Large real-world datasets permit assessment of conditional survival (CS) given both prior overall survival (OS) and real-world progression-free survival (rwPFS).

METHODS

Using a longitudinal dataset from US oncology centers, this study included 6778 women with ovarian cancer. We calculated CS rates as the Kaplan-Meier probability of surviving an additional 1 or 5 years, given no mortality (OS) or disease progression (rwPFS) event in the previous 0.5-5 years since first-line chemotherapy initiation, adjusted for factors associated with OS based on multivariable Cox regression.

RESULTS

Median study follow-up was 9 years (range, 1-44) from first-line initiation to data cutoff (17-Feb-2021). Median OS was 58.0 months (95% CI, 54.9-60.8); median rwPFS was 18.4 months (17.4-19.4). The adjusted 1-year CS rate (ie, rate of 1 year additional survival) did not vary based on time alive, whereas the adjusted 5-year CS rate increased from 48.5% (47.0%-50.1%) for women who had already survived 6 months to 66.4% (63.3%-69.6%) for those already surviving 5 years (thus surviving 10 years total). The adjusted 1-year CS rate increased from 90.4% (89.5%-91.4%) with no rwPFS event at 6 months to 97.6% (96.4%-98.8%) with no rwPFS event at 5 years; adjusted 5-year CS rate increased from 53.7% (52.0%-55.5%) to 85.0% (81.2%-88.9%), respectively.

CONCLUSIONS

This analysis extends the concept of CS by also conditioning on time progression-free. Patients with longer rwPFS experience longer survival than patients with shorter rwPFS.

Leveraging e-health for enhanced cancer care service models in middle-income contexts: Qualitative insights from oncology care providers

Background

Global cancer research has predominantly favoured high-income countries (HICs). The unique challenges in low- and middle-income countries (LMICs) demand tailored research approaches, accentuated further by the disparities highlighted during the COVID-19 pandemic.

Aim and objectives

This research endeavoured to dissect the intricacies of cancer care in LMICs, with Jordan serving as a case study. Specifically, the study aimed to conduct an in-depth analysis of the prevailing cancer care model and assess the transformative potential of eHealth technologies in bolstering cancer care delivery.

Methods

Utilising a qualitative methodology, in-depth semi-structured interviews with oncology healthcare professionals were executed. Data underwent inductive thematic analysis as per Braun and Clarke's guidelines.

Results

From the analysed data, two dominant themes surfaced. Firstly, "The current state of cancer care delivery" was subdivided into three distinct subthemes. Secondly, "Opportunities for enhanced care delivery via e-health" underscored the urgency of digital health reforms.

Conclusion

The need to restrategise cancer care in LMICs is highlighted by this study, using the Jordanian healthcare context as a reference. The transformative potential of e-health initiatives has been illustrated. However, the relevance of this study might be limited by its region-specific approach. Future research is deemed essential for deeper exploration into the integration of digital health within traditional oncology settings across diverse LMICs, emphasising the significance of telemedicine in digital-assisted care delivery reforms.

Multiple Myeloma in Adolescent and Young Adults: An ASCO CancerLinQ and SEER Analysis

BACKGROUND

Multiple myeloma (MM) is exceedingly rare in adolescents and young adults (AYAs) < 45 years of age.

METHODS

Real-world data from ASCO's CancerLinQ DiscoveryⓇ (CLQD) MM dataset and SEER were utilized to characterize demographics and outcomes of AYA MM patients in the United States in the modern treatment era. Frequencies of SPMs, VTEs, and infections were assessed, as were OS and cause of death.

RESULTS

A total of 1946 AYA MM patients from SEER and 1334 from CancerLinQ were included. In terms of SPMs, AYAs were more likely to develop ALL (RR 2.6, P = .003) and AML (RR 1.7, P = .034), and less likely to develop nonmelanoma skin cancer (RR 0.2, P = .001) and prostate cancer (RR 0.1, P = .013) than MM patients ≥ 45. AYAs were at lower risk of VTE (RR 0.75, P = .002) and slightly higher risk of infections (RR 1.11, P = .002). Median OS among AYA MM patients was significantly longer than MM patients ≥ 45 in both datasets. In the SEER cohort, female sex (HR 0.74, P = .003), non-Hispanic ethnicity (HR 0.73, P = .005), and annual household income ≥ $65,000 per year (HR 0.67, P = .001) were associated with lower hazards of mortality. In the CLQD cohort, OS was significantly influenced by female sex (HR 0.6, P = .048). Race did not have a statistically significant impact OS in either cohort. Most AYAs died of MM (68.3%), other primary malignancy (7.5%, mostly leukemia), and cardiovascular events (5.2%). Infections accounted for 3.2% of deaths.

CONCLUSION

This analysis highlights some unique characteristics of AYA MM patients in the United States in the modern era.

Clinical Informatics Approaches to Facilitate Cancer Data Sharing

OBJECTIVES

Despite growing enthusiasm surrounding the utility of clinical informatics to improve cancer outcomes, data availability remains a persistent bottleneck to progress. Difficulty combining data with protected health information often limits our ability to aggregate larger more representative datasets for analysis. With the rise of machine learning techniques that require increasing amounts of clinical data, these barriers have magnified. Here, we review recent efforts within clinical informatics to address issues related to safely sharing cancer data.

METHODS

We carried out a narrative review of clinical informatics studies related to sharing protected health data within cancer studies published from 2018-2022, with a focus on domains such as decentralized analytics, homomorphic encryption, and common data models.

RESULTS

Clinical informatics studies that investigated cancer data sharing were identified. A particular focus of the search yielded studies on decentralized analytics, homomorphic encryption, and common data models. Decentralized analytics has been prototyped across genomic, imaging, and clinical data with the most advances in diagnostic image analysis. Homomorphic encryption was most often employed on genomic data and less on imaging and clinical data. Common data models primarily involve clinical data from the electronic health record. Although all methods have robust research, there are limited studies showing wide scale implementation.

CONCLUSIONS

Decentralized analytics, homomorphic encryption, and common data models represent promising solutions to improve cancer data sharing. Promising results thus far have been limited to smaller settings. Future studies should be focused on evaluating the scalability and efficacy of these methods across clinical settings of varying resources and expertise.

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.

Evaluation of Cost-Effectiveness of Adjuvant Osimertinib in Patients with Resected EGFR Mutation-Positive Non-small Cell Lung Cancer

BACKGROUND

For many patients with resected epidermal growth factor receptor mutation-positive (EGFRm) non-small cell lung cancer (NSCLC), current standard of care (SoC) is adjuvant chemotherapy; however, disease recurrence remains high. Based on positive results from ADAURA (NCT02511106), adjuvant osimertinib was approved for treatment of resected stage IB‒IIIA EGFRm NSCLC.

OBJECTIVE

The aim was to assess the cost-effectiveness of adjuvant osimertinib in patients with resected EGFRm NSCLC.

METHODS

A five-health-state, state-transition model with time dependency was developed to estimate lifetime (38 years) costs and survival of resected EGFRm patients treated with adjuvant osimertinib or placebo (active surveillance), with/without prior adjuvant chemotherapy, using a Canadian Public Healthcare perspective. Transitions between health states were modeled using ADAURA and FLAURA (NCT02296125) data, Canadian life tables, and real-world data (CancerLinQ Discovery^®). The model used a 'cure' assumption: patients remaining disease free for 5 years after treatment completion for resectable disease were deemed 'cured.' Health state utility values and healthcare resource usage estimates were derived from Canadian real-world evidence.

RESULTS

In the reference case, adjuvant osimertinib treatment led to a mean 3.20 additional quality-adjusted life-years (QALYs; (11.77 vs 8.57) per patient, versus active surveillance. The modeled median percentage of patients alive at 10 years was 62.5% versus 39.3%, respectively. Osimertinib was associated with mean added costs of Canadian dollars (C$)114,513 per patient and a cost/QALY (incremental cost-effectiveness ratio) of C$35,811 versus active surveillance. Model robustness was demonstrated by scenario analyses.

CONCLUSIONS

In this cost-effectiveness assessment, adjuvant osimertinib was cost-effective compared with active surveillance for patients with completely resected stage IB‒IIIA EGFRm NSCLC after SoC.

Implementing Innovation: Informatics-Based Technologies to Improve Care Delivery and Clinical Research

Improving technology has promised to improved health care delivery and the lives of patients. The realized benefits of technology, however, are delayed or less than anticipated. Three recent technology initiatives are reviewed: the Clinical Trials Rapid Activation Consortium (CTRAC), minimal Common Oncology Data Elements (mCODE), and electronic Patient-Reported Outcomes. Each initiative is at a different stage of maturity but promises to improve the delivery of cancer care. CTRAC is an ambitious initiative funded by the National Cancer Institute (NCI) to develop processes across multiple NCI-supported cancer centers to facilitate the development of centralized electronic health record (EHR) treatment plans. Facilitating interoperability of treatment regimens has the potential to improve sharing between centers and decrease the time to begin clinical trials. The mCODE initiative began in 2019 and is currently Standard for Trial Use version 2. This data standard provides an abstraction layer on top of EHR data and has been implemented across more than 60 organizations. Patient-reported outcomes have been shown to improve patient care in numerous studies. Best practices for how to leverage these in an oncology practice continue to evolve. These three examples show how innovative has diffused into practice and evolved cancer care delivery and highlight a movement toward patient-centered data and interoperability.

Driving quality improvement through better data: The story of New Zealand's radiation oncology collection

Aotearoa/New Zealand is one of the first nations in the world to develop a comprehensive, high-quality collection of radiation therapy data (the Radiation Oncology Collection, ROC) that is able to report on treatment delivery by health region, patient demographics and service provider. This has been guided by radiation therapy leaders, who have been instrumental in overseeing the establishment of clear and robust data definitions, a centralised database and outputs delivered via an online tool. In this paper, we detail the development of the ROC, provide examples of variation in practice identified from the ROC and how these changed over time, then consider the ramifications of the ROC in the wider context of cancer care quality improvement. In addition to a review of relevant literature, primary data were sourced from the ROC on radiation therapy provided nationally in New Zealand between 2017 and 2020. The total intervention rate, number of fractions and doses are reported for select cancers by way of examples of national variation in practice. Results from the ROC have highlighted areas of treatment variation and have prompted increased uptake of hypofractionation for curative prostate and breast cancer treatment and for palliation of bone metastases. Future development of the ROC will increase its use for quality improvement and ultimately link to a real time cancer services database.

Clinical trial design in the era of precision medicine

Recent rapid biotechnological breakthroughs have led to the identification of complex and unique molecular features that drive malignancies. Precision medicine has exploited next-generation sequencing and matched targeted therapy/immunotherapy deployment to successfully transform the outlook for several fatal cancers. Tumor and liquid biopsy genomic profiling and transcriptomic, immunomic, and proteomic interrogation can now all be leveraged to optimize therapy. Multiple new trial designs, including basket and umbrella trials, master platform trials, and N-of-1 patient-centric studies, are beginning to supplant standard phase I, II, and III protocols, allowing for accelerated drug evaluation and approval and molecular-based individualized treatment. Furthermore, real-world data, as well as exploitation of digital apps and structured observational registries, and the utilization of machine learning and/or artificial intelligence, may further accelerate knowledge acquisition. Overall, clinical trials have evolved, shifting from tumor type-centered to gene-directed and histology-agnostic trials, with innovative adaptive designs and personalized combination treatment strategies tailored to individual biomarker profiles. Some, but not all, novel trials now demonstrate that matched therapy correlates with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To further improve the precision medicine paradigm, the strategy of matching drugs to patients based on molecular features should be implemented earlier in the disease course, and cancers should have comprehensive multi-omic (genomics, transcriptomics, proteomics, immunomic) tumor profiling. To overcome cancer complexity, moving from drug-centric to patient-centric individualized combination therapy is critical. This review focuses on the design, advantages, limitations, and challenges of a spectrum of clinical trial designs in the era of precision oncology.

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.

Retrospective Analysis of Real-World Management of EGFR-Mutated Advanced NSCLC, After First-Line EGFR-TKI Treatment: US Treatment Patterns, Attrition, and Survival Data

BACKGROUND AND OBJECTIVES

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are standard-of-care first-line (1L) treatment for EGFR mutation-positive advanced/metastatic non-small cell lung cancer. In 2015, osimertinib, a third-generation EGFR-TKI, received US accelerated approval for second-line (2L) EGFR T790M-positive non-small cell lung cancer treatment. The objective of this US study was to characterize treatment patterns, attrition, and survival in EGFR mutation-positive non-small cell lung cancer, after 1L first-/second-generation EGFR-TKI treatment.

METHODS

We retrospectively analyzed 1029 patients diagnosed with stage IIIB/IV non-small cell lung cancer from 1 January, 2011 to 31 December, 2018 using the US electronic medical record CancerLinQ Discovery^® database. Demographic/disease characteristics, EGFR mutations, treatments, and death dates were collected.

RESULTS

From 1 January, 2011 to 31 December, 2014 (< 2015 cohort), 519 patients received 1L EGFR-TKIs and 510 between 1 January, 2015 and 31 December, 2018 (≥ 2015 cohort). Median follow-up from advanced diagnosis was 19.8 months (interquartile range: 9.9-33.4 months). Twenty-eight percent of patients (288/1029) died without receiving 2L, and 52% (539/1029) initiated 2L with 35% (186/539) receiving osimertinib; in the < 2015 and ≥ 2015 cohorts, the same proportion initiated 2L (52%; 272/519 vs 267/510, respectively). Median overall survival from advanced diagnosis for patients initially diagnosed with stage I-IIIA disease was 43.3 months (95% confidence interval 30.9-73.7), vs 26.4 months (95% confidence interval 24.4-28.1) for stage IIIB-IV; all-cause mortality hazard ratio: 1.56 (95% confidence interval 1.2-2.0; p = 0.001).

CONCLUSIONS

We identified disease stage, performance status, and central nervous system metastasis as survival predictors, highlighting the importance of optimal 1L treatment selection. Over a quarter of patients died before initiating 2L; half progressed after 1L and received 2L, of whom a third received 2L osimertinib.

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.

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.

Perspectives on emerging technologies, personalised medicine, and clinical research for cancer control in Latin America and the Caribbean

Challenges of health systems in Latin America and the Caribbean include accessibility, inequity, segmentation, and poverty. These challenges are similar in different countries of the region and transcend national borders. The increasing digital transformation of health care holds promise of more precise interventions, improved health outcomes, increased efficiency, and ultimately reduced health-care costs. In Latin America and the Caribbean, the adoption of digital health tools is in early stages and the quality of cancer registries, electronic health records, and structured databases are problematic. Cancer research and innovation in the region are limited due to inadequate academic resources and translational research is almost fully dependent on public funding. Regulatory complexity and extended timelines jeopardise the potential improvement in participation in international studies. Emerging technologies, artificial intelligence, big data, and cancer research represent an opportunity to address the health-care challenges in Latin America and the Caribbean collectively, by optimising national capacities, sharing and comparing best practices, and transferring scientific and technical capabilities.

Survival in the Real World: A National Analysis of Patients Treated for Early-Stage Breast Cancer

PURPOSE

Many patient population groups are not proportionally represented in clinical trials, including patients of color, at age extremes, or with comorbidities. It is therefore unclear how treatment outcomes may differ for these patients compared with those who are well-represented in trials.

METHODS

This retrospective cohort study included women diagnosed with stage I-III breast cancer between 2005 and 2015 in the national CancerLinQ Discovery electronic medical record-based data set. Patients with comorbidities or concurrent cancer were considered unrepresented in clinical trials. Non-White patients and/or those age < 45 or ≥ 70 years were considered under-represented. Patients who were White, age 45-69 years, and without comorbidities were considered well-represented. Cox proportional hazards models were used to evaluate 5-year mortality by representation group and patient characteristics, adjusting for cancer stage, subtype, chemotherapy, and diagnosis year.

RESULTS

Of 11,770 included patients, 48% were considered well-represented in trials, 45% under-represented, and 7% unrepresented. Compared with well-represented patients, unrepresented patients had almost three times the hazard of 5-year mortality (adjusted hazard ratio [aHR], 2.71; 95% CI, 2.08 to 3.52). There were no significant differences in the hazard of 5-year mortality for under-represented patients compared with well-represented patients (aHR, 1.19; 95% CI, 0.98 to 1.45). However, among under-represented patients, those age < 45 years had a lower hazard of 5-year mortality (aHR, 0.63; 95% CI, 0.48 to 0.84) and those age ≥ 70 years had a higher hazard of 5-year mortality (aHR, 2.21; 95% CI, 1.76 to 2.77) compared with those age 45-69 years.

CONCLUSION

More than half of the patients were under-represented or unrepresented in clinical trials, because of age, comorbidity, or race. Some of these groups experienced poorer survival compared with those well-represented in trials. Trialists should ensure that study participants reflect the disease population to support evidence-based decision making for all individuals with cancer.

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.

A 25-year perspective on advances in the study of the epidemiology, disparities, and outcomes of urologic cancers

In this narrative review, key developments in epidemiologic and clinical outcomes-based research from eminent historical data sources over the past quarter century are summarized. We then describe the rise of secondary and administrative datasets (AD), summarizing the predominant types of available secondary datasets for contemporary research and describe the benefits and inherent limitations in working with secondary data. We review the methodological advances that permit researchers to capitalize on the full capability of secondary data while also addressing the limitations inherent in utilizing these data for the purposes of epidemiologic and outcomes research. Finally, we present candidate strategies to perpetuate this momentum towards optimizing the development of clinical research infrastructure that harnesses the full potential of the ADs to further clinical and epidemiological research, advancing data analysis, and address the many unanswered questions that remain.