Breast cancer treatment across health care systems: linking electronic medical records and state registry data to enable outcomes research

Breast cancer learning health system: Patient information from a data and analytics platform characterizes care provided

Purpose

In a learning health system (LHS), data gathered from clinical practice informs care and scientific investigation. To demonstrate how a novel data and analytics platform can enable an LHS at a regional cancer center by characterizing the care provided to breast cancer patients.

Methods

Socioeconomic information, tumor characteristics, treatments and outcomes were extracted from the platform and combined to characterize the patient population and their clinical course. Oncologists were asked to identify examples where clinical practice guidelines (CPGs) or policy changes had varying impacts on practice. These constructs were evaluated by extracting the corresponding data.

Results

Breast cancer patients (5768) seen at the Juravinski Cancer Centre between January 2014 and June 2022 were included. The average age was 62.5 years. The commonest histology was invasive ductal carcinoma (74.6%); 77% were estrogen receptor-positive and 15.5% were HER2 Neu positive. Breast-conserving surgery (BCS) occurred in 56%. For the 4294 patients who received systemic therapy, the initial indications were adjuvant (3096), neoadjuvant (828) and palliative (370). Metastases occurred in 531 patients and 495 patients died. Lowest-income patients had a higher mortality rate. For the adoption of CPGs, the uptake for adjuvant bisphosphonate was very low, 8% as predicted, compared to 64% for pertuzumab, a HER2 targeted agent and 40.2% for CD4/6 inhibitors in metastases. During COVID-19, the provincial cancer agency issued a policy to shorten the duration of radiation after BCS. There was a significant reduction in the average number of fractions to the breast by five fractions.

Conclusion

Our platform characterized care and the clinical course of breast cancer patients. Practice changes in response to regulatory developments and policy changes were measured. Establishing a data platform is important for an LHS. The next step is for the data to feedback and change practice, that is, close the loop.

Implementing a Biomedical Data Warehouse From Blueprint to Bedside in a Regional French University Hospital Setting: Unveiling Processes, Overcoming Challenges, and Extracting Clinical Insight

Background

Biomedical data warehouses (BDWs) have become an essential tool to facilitate the reuse of health data for both research and decisional applications. Beyond technical issues, the implementation of BDWs requires strong institutional data governance and operational knowledge of the European and national legal framework for the management of research data access and use.

Objective

In this paper, we describe the compound process of implementation and the contents of a regional university hospital BDW.

Methods

We present the actions and challenges regarding organizational changes, technical architecture, and shared governance that took place to develop the Nantes BDW. We describe the process to access clinical contents, give details about patient data protection, and use examples to illustrate merging clinical insights.

Unlabelled

More than 68 million textual documents and 543 million pieces of coded information concerning approximately 1.5 million patients admitted to CHUN between 2002 and 2022 can be queried and transformed to be made available to investigators. Since its creation in 2018, 269 projects have benefited from the Nantes BDW. Access to data is organized according to data use and regulatory requirements.

Conclusions

Data use is entirely determined by the scientific question posed. It is the vector of legitimacy of data access for secondary use. Enabling access to a BDW is a game changer for research and all operational situations in need of data. Finally, data governance must prevail over technical issues in institution data strategy vis-à-vis care professionals and patients alike.

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

BACKGROUND

Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research.

OBJECTIVE

The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences.

METHODS

We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results.

RESULTS

We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized.

CONCLUSIONS

The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

Early Ascertainment of Breast Cancer Diagnoses Comparing Self-Reported Questionnaires and Electronic Health Record Data Warehouse: The WISDOM Study

PURPOSE

The goal of this study was to use real-world data sources that may be faster and more complete than self-reported data alone, and timelier than cancer registries, to ascertain breast cancer cases in the ongoing screening trial, the WISDOM Study.

METHODS

We developed a data warehouse procedural process (DWPP) to identify breast cancer cases from a subgroup of WISDOM participants (n = 11,314) who received breast-related care from a University of California Health Center in the period 2012-2021 by searching electronic health records (EHRs) in the University of California Data Warehouse (UCDW). Incident breast cancer diagnoses identified by the DWPP were compared with those identified by self-report via annual follow-up online questionnaires.

RESULTS

Our study identified 172 participants with confirmed breast cancer diagnoses in the period 2016-2021 by the following sources: 129 (75%) by both self-report and DWPP, 23 (13%) by DWPP alone, and 20 (12%) by self-report only. Among those with International Classification of Diseases 10th revision cancer diagnostic codes, no diagnosis was confirmed in 18% of participants.

CONCLUSION

For diagnoses that occurred ≥20 months before the January 1, 2022, UCDW data pull, WISDOM self-reported data via annual questionnaire achieved high accuracy (96%), as confirmed by the cancer registry. More rapid cancer ascertainment can be achieved by combining self-reported data with EHR data from a health system data warehouse registry, particularly to address self-reported questionnaire issues such as timing delays (ie, time lag between participant diagnoses and the submission of their self-reported questionnaire typically ranges from a month to a year) and lack of response. Although cancer registry reporting often is not as timely, it does not require verification as does the DWPP or self-report from annual questionnaires.

Antimicrobial exposure is associated with decreased survival in triple-negative breast cancer

Antimicrobial exposure during curative-intent treatment of triple-negative breast cancer (TNBC) may lead to gut microbiome dysbiosis, decreased circulating and tumor-infiltrating lymphocytes, and inferior outcomes. Here, we investigate the association of antimicrobial exposure and peripheral lymphocyte count during TNBC treatment with survival, using integrated electronic medical record and California Cancer Registry data in the Oncoshare database. Of 772 women with stage I-III TNBC treated with and without standard cytotoxic chemotherapy - prior to the immune checkpoint inhibitor era - most (654, 85%) used antimicrobials. Applying multivariate analyses, we show that each additional total or unique monthly antimicrobial prescription is associated with inferior overall and breast cancer-specific survival. This antimicrobial-mortality association is independent of changes in neutrophil count, is unrelated to disease severity, and is sustained through year three following diagnosis, suggesting antimicrobial exposure negatively impacts TNBC survival. These results may inform mechanistic studies and antimicrobial prescribing decisions in TNBC and other hormone receptor-independent cancers.

Breast Cancer Diagnosis, Treatment, and Outcomes of Patients From Sex and Gender Minority Groups

Importance

Sexual orientation and gender identity data are not collected by most hospitals or cancer registries; thus, little is known about the quality of breast cancer treatment for patients from sex and gender minority (SGM) groups.

Objective

To evaluate the quality of breast cancer treatment and recurrence outcomes for patients from SGM groups compared with cisgender heterosexual patients.

Design, Setting, and Participants

Exposure-matched retrospective case-control study of 92 patients from SGM groups treated at an academic medical center from January 1, 2008, to January 1, 2022, matched to cisgender heterosexual patients with breast cancer by year of diagnosis, age, tumor stage, estrogen receptor status, and ERBB2 (HER2) status.

Main Outcomes and Measures

Patient demographic and clinical characteristics, as well as treatment quality, as measured by missed guideline-based breast cancer screening, appropriate referral for genetic counseling and testing, mastectomy vs lumpectomy, receipt of chest reconstruction, adjuvant radiation therapy after lumpectomy, neoadjuvant chemotherapy for stage III disease, antiestrogen therapy for at least 5 years for estrogen receptor-positive disease, ERBB2-directed therapy for ERBB2-positive disease, patient refusal of an oncologist-recommended treatment, time from symptom onset to tissue diagnosis, time from diagnosis to first treatment, and time from breast cancer diagnosis to first recurrence. Results were adjusted for multiple hypothesis testing. Compared with cisgender heterosexual patients, those from SGM groups were hypothesized to have disparities in 1 or more of these quality metrics.

Results

Ninety-two patients from SGM groups were matched to 92 cisgender heterosexual patients (n = 184). The median age at diagnosis for all patients was 49 years (IQR, 43-56 years); 74 were lesbian (80%), 12 were bisexual (13%), and 6 were transgender (6%). Compared with cisgender heterosexual patients, those from SGM groups experienced a delay in time from symptom onset to diagnosis (median time to diagnosis, 34 vs 64 days; multivariable adjusted hazard ratio, 0.65; 95% CI, 0.42-0.99; P = .04), were more likely to decline an oncologist-recommended treatment modality (35 [38%] vs 18 [20%]; multivariable adjusted odds ratio, 2.27; 95% CI, 1.09-4.74; P = .03), and were more likely to experience a breast cancer recurrence (multivariable adjusted hazard ratio, 3.07; 95% CI, 1.56-6.03; P = .001).

Conclusions and Relevance

This study found that among patients with breast cancer, those from SGM groups experienced delayed diagnosis, with faster recurrence at a 3-fold higher rate compared with cisgender heterosexual patients. These results suggest disparities in the care of patients from SGM groups and warrant further study to inform interventions.

Developing a Data and Analytics Platform to Enable a Breast Cancer Learning Health System at a Regional Cancer Center

PURPOSE

This study documents the creation of automated, longitudinal, and prospective data and analytics platform for breast cancer at a regional cancer center. This platform combines principles of data warehousing with natural language processing (NLP) to provide the integrated, timely, meaningful, high-quality, and actionable data required to establish a learning health system.

METHODS

Data from six hospital information systems and one external data source were integrated on a nightly basis by automated extract/transform/load jobs. Free-text clinical documentation was processed using a commercial NLP engine.

RESULTS

The platform contains 141 data elements of 7,019 patients with newly diagnosed breast cancer who received care at our regional cancer center from January 1, 2014, to June 3, 2022. Daily updating of the database takes an average of 56 minutes. Evaluation of the tuning of NLP jobs found overall high performance, with an F1 of 1.0 for 19 variables, with a further 16 variables with an F1 of > 0.95.

CONCLUSION

This study describes how data warehousing combined with NLP can be used to create a prospective data and analytics platform to enable a learning health system. Although upfront time investment required to create the platform was considerable, now that it has been developed, daily data processing is completed automatically in less than an hour.

Fragmentation of Care in Pancreatic Cancer: Effects on Receipt of Care and Survival

BACKGROUND

The impact of fragmentation of care (FC), i.e., receipt of care at > 1 institution, on treatment of pancreatic cancer is unknown. The purpose of this study was to determine factors associated with FC in curative-intent treatment of pancreatic cancer (PDAC) patients and evaluate how FC affects survival outcomes.

METHODS

Using the National Cancer Database (NCDB), data on stage I-III PDAC patients diagnosed 2006-2016 were extracted. Multiple logistic regression analyses were performed to identify factors predictive of FC and survival.

RESULTS

Of the 20,013 patients identified, 24.1% had FC. Factors predictive of FC were stage-III tumors (odds ratio [OR] 1.36; p = 0.014), higher median-income [third quartile (OR 1.38; p = 0.006) and highest-quartile (OR 1.50; p = 0.003)], care at high-volume facility (OR 1.47; p < 0.001), and receipt of multi-modal therapy (OR 1.69; p < 0.001). In contrast, age > 80 years (OR 0.82; p = 0.018), Black (OR 0.85; p = 0.013) or Asian race (OR 0.76; p = 0.033), Charlson comorbidity-index 2 (OR 0.85; p = 0.033), treatment at non-academic facility (OR 0.87; p = 0.041), and non-private insurance were negatively predictive of FC. FC independently predicted decreased 30-day [OR 0.57; p < 0.001] and 90-day mortality [OR 0.61; p < 0.001] and improved overall survival [hazard ratio 0.91; p < 0.001].

DISCUSSION

Sociodemographic factors are significantly associated with FC in curative-intent treatment of PDAC patients. FC was found to predict improved 30-day, 90-day, and overall survival outcomes.

Fragmentation of care and colorectal cancer survival in South Korea: comparisons according to treatment at multiple hospitals

PURPOSE

Fragmented cancer care (FC) means that patients visit multiple providers for treatment, which is common in cancer care. While FC is associated with poor health outcomes in patients with colorectal cancer (CRC) worldwide, there is still a lack of evidence in South Korea. We investigated the association between FC and 5-year morality in patients with CRC using population-based claims data.

METHODS

The study population was followed up from 2002 to 2015. Data were collected from Korea National Health Insurance claims. Participants comprised patients with CRC diagnosed with International Classification of Diseases (ICD)-10 (C18.x-C20.x) and a special claim code for cancer (V193). Data were analyzed using the Kaplan-Meier curve with a log-rank test and Cox proportional hazard model. The effect of FC on patients' 5-year survival was examined.

RESULTS

Of 3467 patients with CRC, 20.0% had experienced FC. FC was significantly associated with an increased risk of 5-year mortality (hazard ratio 1.516, 95% confidence interval 1.274-1.804). FC was prevalent in those who had a low income level, underwent chemotherapy, did not undergo radiation therapy, and did not visit a tertiary hospital for their first treatment.

CONCLUSION

Efforts to decrease FC and integrate complex cancer care within appropriate healthcare delivery systems may improve survivorship among patients with CRC.

Capitalizing on Central Registries for Expanded Cancer Surveillance and Research

BACKGROUND

State central cancer registries are an essential component of cancer surveillance and research that can be enriched through linkages to other databases. This study identified and described state central registry linkages to external data sources and assessed the potential for a more comprehensive data infrastructure with registries at its core.

METHODS

We identified peer-reviewed papers describing linkages to state central cancer registries in all 50 states, Washington, DC, and Puerto Rico, published between 2010 and 2020. To complement the literature review, we surveyed registrars to learn about unpublished linkages. Linkages were grouped by medical claims (public and private insurers), medical records, other registries (eg, human immunodeficiency virus/acquired immunodeficiency syndrome registries, birth certificates, screening programs), and data from specific cohorts (eg, firefighters, teachers).

RESULTS

We identified 464 data linkages with state central cancer registries. Linkages to cohorts and other registries were most common. Registries in predominately rural states reported the fewest linkages. Most linkages are not ongoing, maintained, or available to researchers. A third of linkages reported by registrars did not result in published papers.

CONCLUSIONS

Central cancer registries, often in collaboration with researchers, have enriched their data through linkages. These linkages demonstrate registries' ability to contribute to a data infrastructure, but a coordinated and maintained approach is needed to leverage these data for research. Sparsely populated states reported the fewest linkages, suggesting possible gaps in our knowledge about cancer in these states. Many more linkages exist than have been reported in the literature, highlighting potential opportunities to further use the data for research purposes.

Limited English Proficiency and Disparities in Health Care Engagement Among Patients With Breast Cancer

PURPOSE

Race and ethnicity have been shown to affect quality of cancer care, and patients with low English proficiency (LEP) have increased risk for serious adverse events. We sought to assess the impact of primary language on health care engagement as indicated by clinical trial screening and engagement, use of genetic counseling, and communication via an electronic patient portal.

METHODS

Clinical and demographic data on patients with breast cancer diagnosed and treated from 2013 to 2018 within the Stanford University Health Care system were compiled via linkage of electronic health records, an internal clinical trial database, and the California Cancer Registry. Logistic and linear regression models were used to evaluate for association of clinical trial engagement and patient portal message rates with primary language group.

RESULTS

Patients with LEP had significantly lower rates of clinical trial engagement compared with their English-speaking counterparts (adjusted odds ratio [OR], 0.29; 95% CI, 0.16 to 0.51). Use of genetic counseling was similar between language groups. Rates of patient portal messaging did not differ between English-speaking and LEP groups on multivariable analysis; however, patients with LEP were less likely to have a portal account (adjusted OR, 0.89; 95% CI, 0.83 to 0.96). Among LEP subgroups, Spanish speakers were significantly less likely to engage with the patient portal compared with English speakers (estimated difference in monthly rate: OR, 0.43; 95% CI, 0.24 to 0.77).

CONCLUSION

We found that patients with LEP had lower rates of clinical trial engagement and odds of electronic patient portal enrollment. Interventions designed to overcome language and cultural barriers are essential to optimize the experience of patients with LEP.

Benchmark Method for Cost Computations Across Health Care Systems: Cost of Care per Patient per Day in Breast Cancer Care

PURPOSE

To estimate the value of cancer care and to compare value among episodes of care, a transparent, reproducible, and standardized cost computation methodology is needed. Charges, claims, and reimbursements are related to cost but are nontransparent and proprietary. We developed a method to measure the cost of the following phases of care: (1) initial treatment with curative intent, (2) surveillance and survivorship care, and (3) relapse and end-of-life care.

METHODS

We combined clinical data from our electronic health record, the state cancer registry, and the Social Security Death Index. We analyzed the care of patients with breast cancer and mapped Common Procedural Terminology (CPT) codes to the corresponding cost conversion factor and date in the CMS Medicare fee schedule. To account for varying duration of episodes of care, we computed a cost of care per day (CCPD) for each patient.

RESULTS

Median CCPD for initial treatment was $29.45 in US dollars (USD), the CCPD for surveillance and survivorship care was $2.45 USD, and the CCPD for relapse care was $13.80 USD. Among the three breast cancer types (hormone receptor-positive or human epidermal growth factor receptor 2 [HER2]-negative, HER2-positive, and triple-negative), there was no difference in CCPD. Relapsed patients in the most expensive surveillance CCPD group had significantly shorter survival.

CONCLUSION

We developed a method to identify high-value oncology care-cost of care per patient per day (CCPD)-in episodes of initial, survivorship, and relapse care. The methodology can help identify positive deviants (who have developed best practices) delivering high-value care. Merging our data with claims data from third-party payers can increase the accuracy and validity of the CCPD.

Development and Use of Natural Language Processing for Identification of Distant Cancer Recurrence and Sites of Distant Recurrence Using Unstructured Electronic Health Record Data

PURPOSE

Large-scale analysis of real-world evidence is often limited to structured data fields that do not contain reliable information on recurrence status and disease sites. In this report, we describe a natural language processing (NLP) framework that uses data from free-text, unstructured reports to classify recurrence status and sites of recurrence for patients with breast and hepatocellular carcinomas (HCC).

METHODS

Using two cohorts of breast cancer and HCC cases, we validated the ability of a previously developed NLP model to distinguish between no recurrence, local recurrence, and distant recurrence, based on clinician notes, radiology reports, and pathology reports compared with manual curation. A second NLP model was trained and validated to identify sites of recurrence. We compared the ability of each NLP model to identify the presence, timing, and site of recurrence, when compared against manual chart review and International Classification of Diseases coding.

RESULTS

A total of 1,273 patients were included in the development and validation of the two models. The NLP model for recurrence detects distant recurrence with an area under the curve of 0.98 (95% CI, 0.96 to 0.99) and 0.95 (95% CI, 0.88 to 0.98) in breast and HCC cohorts, respectively. The mean accuracy of the NLP model for detecting any site of distant recurrence was 0.9 for breast cancer and 0.83 for HCC. The NLP model for recurrence identified a larger proportion of patients with distant recurrence in a breast cancer database (11.1%) compared with International Classification of Diseases coding (2.31%).

CONCLUSION

We developed two NLP models to identify distant cancer recurrence, timing of recurrence, and sites of recurrence based on unstructured electronic health record data. These models can be used to perform large-scale retrospective studies in oncology.

Fragmentation of Care Among Black Women With Breast Cancer and Comorbidities: The Role of Health Systems

PURPOSE

Black women are disproportionately burdened by comorbidities and breast cancer. The complexities of coordinating care for multiple health conditions can lead to adverse consequences. Care coordination may be exacerbated when care is received outside the same health system, defined as care fragmentation. We examine types of practice setting for primary and breast cancer care to assess care fragmentation.

MATERIALS AND METHODS

We analyzed data from a prospective cohort of Black women diagnosed with breast cancer in New Jersey who also had a prior diagnosis of diabetes and/or hypertension (N = 228). Following breast cancer diagnosis, we examined types of practice setting for first primary care visit and primary breast surgery, through medical chart abstraction, and identified whether care was used within or outside the same health system. We used multivariable logistic regression to explore sociodemographic and clinical factors associated with care fragmentation.

RESULTS

Diverse primary care settings were used: medical groups (32.0%), health systems (29.4%), solo practices (23.7%), Federally Qualified Health Centers (8.3%), and independent hospitals (6.1%). Surgical care predominately occurred in health systems (79.8%), with most hospitals being Commission on Cancer-accredited. Care fragmentation was experienced by 78.5% of Black women, and individual-level factors (age, health insurance, cancer stage, and comorbidity count) were not associated with care fragmentation (P > .05).

CONCLUSION

The majority of Black breast cancer survivors with comorbidities received primary care and surgical care in different health systems, illustrating care fragmentation. Strategies for care coordination and health care delivery across health systems and practice settings are needed for health equity.

Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer

PURPOSE

Electronic medical records (EMRs) and population-based cancer registries contain information on cancer outcomes and treatment, yet rarely capture information on the timing of metastatic cancer recurrence, which is essential to understand cancer survival outcomes. We developed a natural language processing (NLP) system to identify patient-specific timelines of metastatic breast cancer recurrence.

PATIENTS AND METHODS

We used the OncoSHARE database, which includes merged data from the California Cancer Registry and EMRs of 8,956 women diagnosed with breast cancer in 2000 to 2018. We curated a comprehensive vocabulary by interviewing expert clinicians and processing radiology and pathology reports and progress notes. We developed and evaluated the following two distinct NLP approaches to analyze free-text notes: a traditional rule-based model, using rules for metastatic detection from the literature and curated by domain experts; and a contemporary neural network model. For each 3-month period (quarter) from 2000 to 2018, we applied both models to infer recurrence status for that quarter. We trained the NLP models using 894 randomly selected patient records that were manually reviewed by clinical experts and evaluated model performance using 179 hold-out patients (20%) as a test set.

RESULTS

The median follow-up time was 19 quarters (5 years) for the training set and 15 quarters (4 years) for the test set. The neural network model predicted the timing of distant metastatic recurrence with a sensitivity of 0.83 and specificity of 0.73, outperforming the rule-based model, which had a specificity of 0.35 and sensitivity of 0.88 (P < .001).

CONCLUSION

We developed an NLP method that enables identification of the occurrence and timing of metastatic breast cancer recurrence from EMRs. This approach may be adaptable to other cancer sites and could help to unlock the potential of EMRs for research on real-world cancer outcomes.

Population-Based Registry Linkages to Improve Validity of Electronic Health Record-Based Cancer Research

BACKGROUND

There is tremendous potential to leverage the value gained from integrating electronic health records (EHR) and population-based cancer registry data for research. Registries provide diagnosis details, tumor characteristics, and treatment summaries, while EHRs contain rich clinical detail. A carefully conducted cancer registry linkage may also be used to improve the internal and external validity of inferences made from EHR-based studies.

METHODS

We linked the EHRs of a large, multispecialty, mixed-payer health care system with the statewide cancer registry and assessed the validity of our linked population. For internal validity, we identify patients that might be "missed" in a linkage, threatening the internal validity of an EHR study population. For generalizability, we compared linked cases with all other cancer patients in the 22-county EHR catchment region.

RESULTS

From an EHR population of 4.5 million, we identified 306,554 patients with cancer, 26% of the catchment region patients with cancer; 22.7% of linked patients were diagnosed with cancer after they migrated away from our health care system highlighting an advantage of system-wide linkage. We observed demographic differences between EHR patients and non-EHR patients in the surrounding region and demonstrated use of selection probabilities with model-based standardization to improve generalizability.

CONCLUSIONS

Our experiences set the foundation to encourage and inform researchers interested in working with EHRs for cancer research as well as provide context for leveraging linkages to assess and improve validity and generalizability.

IMPACT

Researchers conducting linkages may benefit from considering one or more of these approaches to establish and evaluate the validity of their EHR-based populations.See all articles in this CEBP Focus section, "Modernizing Population Science."

Genomic landscape of ductal carcinoma in situ and association with progression

PURPOSE

The detection rate of breast ductal carcinoma in situ (DCIS) has increased significantly, raising the concern that DCIS is overdiagnosed and overtreated. Therefore, there is an unmet clinical need to better predict the risk of progression among DCIS patients. Our hypothesis is that by combining molecular signatures with clinicopathologic features, we can elucidate the biology of breast cancer progression, and risk-stratify patients with DCIS.

METHODS

Targeted exon sequencing with a custom panel of 223 genes/regions was performed for 125 DCIS cases. Among them, 60 were from cases having concurrent or subsequent invasive breast cancer (IBC) (DCIS + IBC group), and 65 from cases with no IBC development over a median follow-up of 13 years (DCIS-only group). Copy number alterations in chromosome 1q32, 8q24, and 11q13 were analyzed using fluorescence in situ hybridization (FISH). Multivariable logistic regression models were fit to the outcome of DCIS progression to IBC as functions of demographic and clinical features.

RESULTS

We observed recurrent variants of known IBC-related mutations, and the most commonly mutated genes in DCIS were PIK3CA (34.4%) and TP53 (18.4%). There was an inverse association between PIK3CA kinase domain mutations and progression (Odds Ratio [OR] 10.2, p < 0.05). Copy number variations in 1q32 and 8q24 were associated with progression (OR 9.3 and 46, respectively; both p < 0.05).

CONCLUSIONS

PIK3CA kinase domain mutations and the absence of copy number gains in DCIS are protective against progression to IBC. These results may guide efforts to distinguish low-risk from high-risk DCIS.

Using natural language processing to construct a metastatic breast cancer cohort from linked cancer registry and electronic medical records data

Objectives

Most population-based cancer databases lack information on metastatic recurrence. Electronic medical records (EMR) and cancer registries contain complementary information on cancer diagnosis, treatment and outcome, yet are rarely used synergistically. To construct a cohort of metastatic breast cancer (MBC) patients, we applied natural language processing techniques within a semisupervised machine learning framework to linked EMR-California Cancer Registry (CCR) data.

Materials and Methods

We studied all female patients treated at Stanford Health Care with an incident breast cancer diagnosis from 2000 to 2014. Our database consisted of structured fields and unstructured free-text clinical notes from EMR, linked to CCR, a component of the Surveillance, Epidemiology and End Results Program (SEER). We identified de novo MBC patients from CCR and extracted information on distant recurrences from patient notes in EMR. Furthermore, we trained a regularized logistic regression model for recurrent MBC classification and evaluated its performance on a gold standard set of 146 patients.

Results

There were 11 459 breast cancer patients in total and the median follow-up time was 96.3 months. We identified 1886 MBC patients, 512 (27.1%) of whom were de novo MBC patients and 1374 (72.9%) were recurrent MBC patients. Our final MBC classifier achieved an area under the receiver operating characteristic curve (AUC) of 0.917, with sensitivity 0.861, specificity 0.878, and accuracy 0.870.

Discussion and Conclusion

To enable population-based research on MBC, we developed a framework for retrospective case detection combining EMR and CCR data. Our classifier achieved good AUC, sensitivity, and specificity without expert-labeled examples.

Comparative effectiveness of first-line nab-paclitaxel versus paclitaxel monotherapy in triple-negative breast cancer

Aim: This observational study evaluated the effectiveness of nab-paclitaxel versus paclitaxel monotherapy as first-line (1L) treatment for metastatic triple-negative breast cancer (mTNBC). Materials & methods: 200 patients from the US Flatiron Health electronic health record-derived database (mTNBC diagnosis, January 2011-October 2016) who received 1L nab-paclitaxel (n = 105) or paclitaxel (n = 95) monotherapy were included. Overall survival and time to next treatment were evaluated. Results: The adjusted overall survival hazard ratio was 0.98 (95% CI: 0.67-1.44), indicating a similar risk of death between groups. Adjusted time to next treatment hazard ratio was 0.89 (95% confidence interval: 0.62-1.29). Conclusion: Nab-paclitaxel and paclitaxel monotherapy showed similar efficacy, suggesting their interchangeability as 1L treatments for mTNBC.

Effect of fragmentation of cancer care on treatment use and survival in hepatocellular carcinoma

BACKGROUND

Fragmented cancer care (FC), or care received from multiple institutions, increases systemic health care costs and potentiates cancer care disparities. There is a paucity of data on mechanisms contributing to FC and the resulting effect on patient outcomes. This study characterized patient- and hospital-level factors associated with FC, time to treatment (TTT), and overall survival (OS) in patients with hepatocellular carcinoma (HCC).

METHODS

Patients newly diagnosed with HCC from 2004 to 2015 and receiving treatment were identified in the Texas Cancer Registry. Patient- and hospital-level factors were compared across 2 cohorts: an FC treatment group and a nonfragmented cancer care (NFC) treatment group. Covariate-adjusted treatment use and OS were compared between the 2 treatment groups.

RESULTS

Among 4329 patients with HCC, 1185 (27.4%) received FC, and 3144 (72.6%) received NFC. Compared with NFC patients, FC patients had larger tumors (median size ≥4 cm, 52.6% vs 35.2%; P < .001), and a higher proportion had a regional/metastatic stage (35.9% vs 26.7%; P < .001). Among patients with localized disease, FC was associated with decreased odds of curative therapy (odds ratio, 0.83; 95% confidence interval [CI], 0.7-0.9). FC was associated with worse OS (hazard ratio [HR], 1.14; 95% CI, 1.05-1.24) and increased TTT (HR, 0.76; 95% CI, 0.7-0.8). In the subset of patients with localized-stage HCC who received curative therapy, FC was associated with worse OS (median survival, 67 vs 43 months; HR, 1.2; 95% CI, 1.0-1.4) and increased TTT (HR, 0.74; 95% CI, 0.7-0.8).

CONCLUSIONS

FC patients were less likely to undergo curative therapy when they were diagnosed at an early stage. After covariate adjustment, newly diagnosed patients with HCC receiving FC had worse OS and increased TTT.

Distribution of global health measures from routinely collected PROMIS surveys in patients with breast cancer or prostate cancer

BACKGROUND

The collection of patient-reported outcomes (PROs) is an emerging priority internationally, guiding clinical care, quality improvement projects and research studies. After the deployment of Patient-Reported Outcomes Measurement Information System (PROMIS) surveys in routine outpatient workflows at an academic cancer center, electronic health record data were used to evaluate survey completion rates and self-reported global health measures across 2 tumor types: breast and prostate cancer.

METHODS

This study retrospectively analyzed 11,657 PROMIS surveys from patients with breast cancer and 4411 surveys from patients with prostate cancer, and it calculated survey completion rates and global physical health (GPH) and global mental health (GMH) scores between 2013 and 2018.

RESULTS

A total of 36.6% of eligible patients with breast cancer and 23.7% of patients with prostate cancer completed at least 1 survey, with completion rates lower among black patients for both tumor types (P < .05). The mean T scores (calibrated to a general population mean of 50) for GPH were 48.4 ± 9 for breast cancer and 50.6 ± 9 for prostate cancer, and the GMH scores were 52.7 ± 8 and 52.1 ± 9, respectively. GPH and GMH were frequently lower among ethnic minorities, patients without private health insurance, and those with advanced disease.

CONCLUSIONS

This analysis provides important baseline data on patient-reported global health in breast and prostate cancer. Demonstrating that PROs can be integrated into clinical workflows, this study shows that supportive efforts may be needed to improve PRO collection and global health endpoints in vulnerable populations.

Electronic Health Record-Based Registries: Clinical Research Using Registries in Colon and Rectal Surgery

Electronic health records (EHRs) or electronic medical records (EMRs) contain a vast amount of clinical data that can be useful for multiple purposes including research. Disease registries are collections of data in predefined formats for population management, research, and other purposes. There are differences between EHRs and registries in the data structure, data standards, and protocols. Proprietary EHR systems use different coding systems and data standards, which are usually kept secret. For EHR data to flow seamlessly into registries, there is the need for interoperability between EHR systems and between EHRs and registries. The levels of interoperability required include functional, structural, and semantic interoperability. EHR data can be manually mapped to registry data, but that is a tedious, resource-intensive endeavor. The development of data standards that can be used as building blocks for both EHRs and registries will help overcome the problem of interoperability.

Hospital transfer after a breast cancer diagnosis: A population-based study in the Netherlands of the extent, predictive characteristics and its impact on time to treatment

PURPOSE

Patients may transfer of hospital for clinical reasons but this may delay time to treatment. The purpose of this study is to provide insight in the extent of hospital transfer in breast cancer care; which type of patients transfer and what is the impact on time to treatment.

METHODS

We included 41,413 breast cancer patients registered in the Netherlands Cancer Registry between 2014 and 2016. We investigated transfer of hospital between diagnosis and first treatment being surgery or neoadjuvant chemotherapy (NAC). Co-variate adjusted characteristics predictive for hospital transfer were determined. To adjust for possible treatment by indication bias we used propensity score matching (PSM). Time to treatment in patients with and without hospital transfer was compared.

RESULTS

Among 41,413 patients, 8.5% of all patients transferred to another hospital between diagnosis and first treatment; 4.9% before primary surgery and 24.8% before NAC. Especially young (aged <40 years) patients and those who underwent a mastectomy with immediate breast reconstruction (IBR) were more likely to transfer. The association of mastectomy with IBR with hospital transfer remained when using PSM. Hospital transfer after diagnosis significantly prolonged time to treatment; breast-conserving surgery by 5 days, mastectomy by 7 days, mastectomy with IBR by 9 days and NAC by 1 day.

CONCLUSIONS

While almost 5% of Dutch patients treated with primary surgery transfer hospital after diagnosis and up to 25% for patients treated with NAC, our findings suggest that especially those treated with primary surgery are at risk for additional treatment delay by hospital transfer.

Macrophages Promote Circulating Tumor Cell-Mediated Local Recurrence following Radiotherapy in Immunosuppressed Patients

Although radiotherapy (RT) decreases the incidence of locoregional recurrence in breast cancer, patients with triple-negative breast cancer (TNBC) have increased risk of local recurrence following breast-conserving therapy. The relationship between RT and local recurrence is unknown. Here, we tested the hypothesis that recurrence in some instances is due to the attraction of circulating tumor cells to irradiated tissues. To evaluate the effect of absolute lymphocyte count on local recurrence after RT in patients with TNBC, we analyzed radiation effects on tumor and immune cell recruitment to tissues in an orthotopic breast cancer model. Recurrent patients exhibited a prolonged low absolute lymphocyte count when compared with nonrecurrent patients following RT. Recruitment of tumor cells to irradiated normal tissues was enhanced in the absence of CD8+ T cells. Macrophages (CD11b+F480+) preceded tumor cell infiltration and were recruited to tissues following RT. Tumor cell recruitment was mitigated by inhibiting macrophage infiltration using maraviroc, an FDA-approved CCR5 receptor antagonist. Our work poses the intriguing possibility that excessive macrophage infiltration in the absence of lymphocytes promotes local recurrence after RT. This combination thus defines a high-risk group of patients with TNBC.Significance: This study establishes the importance of macrophages in driving tumor cell recruitment to sites of local radiation therapy and suggests that this mechanism contributes to local recurrence in women with TNBC that are also immunosuppressed.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/15/4241/F1.large.jpg Cancer Res; 78(15); 4241-52. ©2018 AACR.

Higher Absolute Lymphocyte Counts Predict Lower Mortality from Early-Stage Triple-Negative Breast Cancer

Purpose: Tumor-infiltrating lymphocytes (TIL) in pretreatment biopsies are associated with improved survival in triple-negative breast cancer (TNBC). We investigated whether higher peripheral lymphocyte counts are associated with lower breast cancer-specific mortality (BCM) and overall mortality (OM) in TNBC.Experimental Design: Data on treatments and diagnostic tests from electronic medical records of two health care systems were linked with demographic, clinical, pathologic, and mortality data from the California Cancer Registry. Multivariable regression models adjusted for age, race/ethnicity, socioeconomic status, cancer stage, grade, neoadjuvant/adjuvant chemotherapy use, radiotherapy use, and germline BRCA1/2 mutations were used to evaluate associations between absolute lymphocyte count (ALC), BCM, and OM. For a subgroup with TIL data available, we explored the relationship between TILs and peripheral lymphocyte counts.Results: A total of 1,463 stage I-III TNBC patients were diagnosed from 2000 to 2014; 1,113 (76%) received neoadjuvant/adjuvant chemotherapy within 1 year of diagnosis. Of 759 patients with available ALC data, 481 (63.4%) were ever lymphopenic (minimum ALC <1.0 K/μL). On multivariable analysis, higher minimum ALC, but not absolute neutrophil count, predicted lower OM [HR = 0.23; 95% confidence interval (CI), 0.16-0.35] and BCM (HR = 0.19; CI, 0.11-0.34). Five-year probability of BCM was 15% for patients who were ever lymphopenic versus 4% for those who were not. An exploratory analysis (n = 70) showed a significant association between TILs and higher peripheral lymphocyte counts during neoadjuvant chemotherapy.Conclusions: Higher peripheral lymphocyte counts predicted lower mortality from early-stage, potentially curable TNBC, suggesting that immune function may enhance the effectiveness of early TNBC treatment. Clin Cancer Res; 24(12); 2851-8. ©2018 AACR.

Architecture and Implementation of a Clinical Research Data Warehouse for Prostate Cancer

Background

Electronic health record (EHR) based research in oncology can be limited by missing data and a lack of structured data elements. Clinical research data warehouses for specific cancer types can enable the creation of more robust research cohorts.

Methods

We linked data from the Stanford University EHR with the Stanford Cancer Institute Research Database (SCIRDB) and the California Cancer Registry (CCR) to create a research data warehouse for prostate cancer. The database was supplemented with information from clinical trials, natural language processing of clinical notes and surveys on patient-reported outcomes.

Results

11,898 unique prostate cancer patients were identified in the Stanford EHR, of which 3,936 were matched to the Stanford cancer registry and 6153 in the CCR. 7158 patients with EHR data and at least one of SCIRDB and CCR data were initially included in the warehouse.

Conclusions

A disease-specific clinical research data warehouse combining multiple data sources can facilitate secondary data use and enhance observational research in oncology.

Synergistic drug combinations from electronic health records and gene expression

Objective

Using electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.

Method

We applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis.

Results

From EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence.

Conclusions

This is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing.

Comorbidity index in central cancer registries: the value of hospital discharge data

Background

The presence of comorbid medical conditions can significantly affect a cancer patient’s treatment options, quality of life, and survival. However, these important data are often lacking from population-based cancer registries. Leveraging routine linkage to hospital discharge data, a comorbidity score was calculated for patients in the California Cancer Registry (CCR) database.

Methods

California cancer cases diagnosed between 1991 and 2013 were linked to statewide hospital discharge data. A Deyo and Romano adapted Charlson Comorbidity Index was calculated for each case, and the association of comorbidity score with overall survival was assessed with Kaplan–Meier curves and Cox proportional hazards models. Using a subset of Medicare-enrolled CCR cases, the index was validated against a comorbidity score derived using Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data.

Results

A comorbidity score was calculated for 71% of CCR cases. The majority (60.2%) had no relevant comorbidities. Increasing comorbidity score was associated with poorer overall survival. In a multivariable model, high comorbidity conferred twice the risk of death compared to no comorbidity (hazard ratio 2.33, 95% CI: 2.32–2.34). In the subset of patients with a SEER-Medicare-derived score, the sensitivity of the hospital discharge-based index for detecting any comorbidity was 76.5. The association between overall mortality and comorbidity score was stronger for the hospital discharge-based score than for the SEER-Medicare-derived index, and the predictive ability of the hospital discharge-based score, as measured by Harrell’s C index, was also slightly better for the hospital discharge-based score (C index 0.62 versus 0.59, P<0.001).

Conclusions

Despite some limitations, using hospital discharge data to construct a comorbidity index for cancer registries is a feasible and valid method to enhance registry data, which can provide important clinically relevant information for population-based cancer outcomes research.

Prevalence and characteristics of cancer patients receiving care from single vs. multiple institutions

INTRODUCTION

Patients may receive cancer care from multiple institutions. However, at the population level, such patterns of cancer care are poorly described, complicating clinical research. To determine the population-based prevalence and characteristics of patients seen by multiple institutions, we used operations data from a state-mandated cancer registry.

METHODS AND MATERIALS

59,672 invasive cancers diagnosed in 1/1/2010-12/31/2011 in the Greater Bay Area of northern California were categorized as having been reported to the cancer registry within 365days of diagnosis by: 1) ≥1 institution within an integrated health system (IHS); 2) IHS institution(s) and ≥1 non-IHS institution (e.g., private hospital); 3) 1 non-IHS institution; or 4) ≥2 non-IHS institutions. Multivariable logistic regression was used to characterize patients reported by multiple vs. single institutions.

RESULTS

Overall in this region, 17% of cancers were reported by multiple institutions. Of the 33% reported by an IHS, 8% were also reported by a non-IHS. Of non-IHS patients, 21% were reported by multiple institutions, with 28% for breast and 27% for pancreatic cancer, but 19%% for lung and 18% for prostate cancer. Generally, patients more likely to be seen by multiple institutions were younger or had more severe disease at diagnosis.

CONCLUSIONS

Population-based data show that one in six newly diagnosed cancer patients received care from multiple institutions, and differed from patients seen only at a single institution. Cancer care data from single institutions may be incomplete and possibly biased.

Breast Reconstruction Following Cancer Treatment

BACKGROUND

About 8000 breast reconstructions after mastectomy are per - formed in Germany each year. It has become more difficult to advise patients because of the wide variety of heterologous and autologous techniques that are now available and because of changes in the recommendations about radiotherapy.

METHODS

This article is based on a review of pertinent articles (2005-2014) that were retrieved by a selective search employing the search terms "mastectomy" and "breast reconstruction."

RESULTS

The goal of reconstruction is to achieve an oncologically safe and aestically satisfactory result for the patient over the long term. Heterologous, i.e., implant-based, breast reconstruction (IBR) and autologous breast reconstruction (ABR) are complementary techniques. Immediate reconstruction preserves the skin of the breast and its natural form and prevents the psychological trauma associated with mastectomy. If post-mastectomy radiotherapy (PMRT) is not indicated, implant-based reconstruction with or without a net/acellular dermal matrix (ADM) is a common option. Complications such as seroma formation, infection, and explantation are significantly more common when an ADM is used (15.3% vs. 5.4% ). If PMRT is performed, then the complication rate of implant-based breast reconstruction is 1 to 48% ; in particular, Baker grade III/IV capsular fibrosis occurs in 7 to 22% of patients, and the prosthesis must be explanted in 9 to 41% . Primary or, preferably, secondary autologous reconstruction is an alternative. The results of ABR are more stable over the long term, but the operation is markedly more complex. Autologous breast reconstruction after PMRT does not increase the risk of serious complications (20.5% vs. 17.9% without radiotherapy).

CONCLUSION

No randomized controlled trials have yet been conducted to compare the reconstructive techniques with each other. If radiotherapy will not be performed, immediate reconstruction with an implant is recommended. On the other hand, if post-mastectomy radiotherapy is indicated, then secondary autologous breast reconstruction is the procedure of choice. Future studies should address patients' quality of life and the long-term aesthetic results after breast reconstruction.

Use of Gene Expression Profiling and Chemotherapy in Early-Stage Breast Cancer: A Study of Linked Electronic Medical Records, Cancer Registry Data, and Genomic Data Across Two Health Care Systems

PURPOSE

The 21-gene recurrence score (RS) identifies patients with breast cancer who derive little benefit from chemotherapy; it may reduce unwarranted variability in the use of chemotherapy. We tested whether the use of RS seems to guide chemotherapy receipt across different cancer care settings.

METHODS

We developed a retrospective cohort of patients with breast cancer by using electronic medical record data from Stanford University (hereafter University) and Palo Alto Medical Foundation (hereafter Community) linked with demographic and staging data from the California Cancer Registry and RS results from the testing laboratory (Genomic Health Inc., Redwood City, CA). Multivariable analysis was performed to identify predictors of RS and chemotherapy use.

RESULTS

In all, 10,125 patients with breast cancer were diagnosed in the University or Community systems from 2005 to 2011; 2,418 (23.9%) met RS guidelines criteria, of whom 15.6% received RS. RS was less often used for patients with involved lymph nodes, higher tumor grade, and age < 40 or ≥ 65 years. Among RS recipients, chemotherapy receipt was associated with a higher score (intermediate v low: odds ratio, 3.66; 95% CI, 1.94 to 6.91). A total of 293 patients (10.6%) received care in both health care systems (hereafter dual use); although receipt of RS was associated with dual use (v University: odds ratio, 1.73; 95% CI, 1.18 to 2.55), there was no difference in use of chemotherapy after RS by health care setting.

CONCLUSION

Although there was greater use of RS for patients who sought care in more than one health care setting, use of chemotherapy followed RS guidance in University and Community health care systems. These results suggest that precision medicine may help optimize cancer treatment across health care settings.

Development of a large urban longitudinal HIV clinical cohort using a web-based platform to merge electronically and manually abstracted data from disparate medical record systems: technical challenges and innovative solutions

OBJECTIVE

Electronic medical records (EMRs) are being increasingly utilized to conduct clinical and epidemiologic research in numerous fields. To monitor and improve care of HIV-infected patients in Washington, DC, one of the most severely affected urban areas in the United States, we developed a city-wide database across 13 clinical sites using electronic data abstraction and manual data entry from EMRs.

MATERIALS AND METHODS

To develop this unique longitudinal cohort, a web-based electronic data capture system (Discovere®) was used. An Agile software development methodology was implemented across multiple EMR platforms. Clinical informatics staff worked with information technology specialists from each site to abstract data electronically from each respective site's EMR through an extract, transform, and load process.

RESULTS

Since enrollment began in 2011, more than 7000 patients have been enrolled, with longitudinal clinical data available on all patients. Data sets are produced for scientific analyses on a quarterly basis, and benchmarking reports are generated semi-annually enabling each site to compare their participants' clinical status, treatments, and outcomes to the aggregated summaries from all other sites.

DISCUSSION

Numerous technical challenges were identified and innovative solutions developed to ensure the successful implementation of the DC Cohort. Central to the success of this project was the broad collaboration established between government, academia, clinics, community, information technology staff, and the patients themselves.

CONCLUSIONS

Our experiences may have practical implications for researchers who seek to merge data from diverse clinical databases, and are applicable to the study of health-related issues beyond HIV.

An Associative Memory Model for Integration of Fragmented Research Data and Identification of Treatment Correlations in Breast Cancer Care

A major challenge in advancing scientific discoveries using data-driven clinical research is the fragmentation of relevant data among multiple information systems. This fragmentation requires significant data-engineering work before correlations can be found among data attributes in multiple systems. In this paper, we focus on integrating information on breast cancer care, and present a novel computational approach to identify correlations between administered drugs captured in an electronic medical records and biological factors obtained from a tumor registry through rapid data aggregation and analysis. We use an associative memory (AM) model to encode all existing associations among the data attributes from both systems in a high-dimensional vector space. The AM model stores highly associated data items in neighboring memory locations to enable efficient querying operations. The results of applying AM to a set of integrated data on tumor markers and drug administrations discovered anomalies between clinical recommendations and derived associations.

Chromosomal copy number alterations for associations of ductal carcinoma in situ with invasive breast cancer

INTRODUCTION

Screening mammography has contributed to a significant increase in the diagnosis of ductal carcinoma in situ (DCIS), raising concerns about overdiagnosis and overtreatment. Building on prior observations from lineage evolution analysis, we examined whether measuring genomic features of DCIS would predict association with invasive breast carcinoma (IBC). The long-term goal is to enhance standard clinicopathologic measures of low- versus high-risk DCIS and to enable risk-appropriate treatment.

METHODS

We studied three common chromosomal copy number alterations (CNA) in IBC and designed fluorescence in situ hybridization-based assay to measure copy number at these loci in DCIS samples. Clinicopathologic data were extracted from the electronic medical records of Stanford Cancer Institute and linked to demographic data from the population-based California Cancer Registry; results were integrated with data from tissue microarrays of specimens containing DCIS that did not develop IBC versus DCIS with concurrent IBC. Multivariable logistic regression analysis was performed to describe associations of CNAs with these two groups of DCIS.

RESULTS

We examined 271 patients with DCIS (120 that did not develop IBC and 151 with concurrent IBC) for the presence of 1q, 8q24 and 11q13 copy number gains. Compared to DCIS-only patients, patients with concurrent IBC had higher frequencies of CNAs in their DCIS samples. On multivariable analysis with conventional clinicopathologic features, the copy number gains were significantly associated with concurrent IBC. The state of two of the three copy number gains in DCIS was associated with a risk of IBC that was 9.07 times that of no copy number gains, and the presence of gains at all three genomic loci in DCIS was associated with a more than 17-fold risk (P = 0.0013).

CONCLUSIONS

CNAs have the potential to improve the identification of high-risk DCIS, defined by presence of concurrent IBC. Expanding and validating this approach in both additional cross-sectional and longitudinal cohorts may enable improved risk stratification and risk-appropriate treatment in DCIS.

Use of Adjuvant Cisplatin-Based Versus Carboplatin-Based Chemotherapy in Non-Small-Cell Lung Cancer: Findings From the Florida Initiative for Quality Cancer Care

PURPOSE

For patients with resected non-small-cell lung cancer, national guidelines recommend cisplatin-based doublet chemotherapy as the preferred treatment. However, many patients receive a carboplatin-based regimen instead. We aimed to identify factors associated with use of a cisplatin-based regimen and explore its association with other quality-of-care measures.

METHODS

This analysis was part of the Florida Initiative for Quality Cancer Care, an audit and feedback project among 11 medical oncology practices. Feedback-sharing sessions based on findings of year 2006 took place in 2008. Eligible patients were random samples of those with resected stage I to III non-small-cell lung cancer treated in 2006 and 2009.

RESULTS

In both years combined, 81 patients received adjuvant platinum-based doublets: 33 patients (41%) received cisplatin, and 48 patients (59%) received carboplatin. Use of a cisplatin-based doublet significantly increased in 2009 compared with 2006, from 24% to 56% (P = .006). Multivariable analysis determined that academic practices used cisplatin more frequently than nonacademic practices (odds ratios, 3.26; 95% CI, 1.19 to 8.91; P = .02). Moreover, patients treated in 2009 were more likely to receive cisplatin than those treated in 2006 (odds ratio, 4.89; 95% CI, 1.75 to 13.67; P = .002). No significant association between use of cisplatin and other quality-of-care measures was found.

CONCLUSION

In this study, academic practice status and treatment year predicted use of adjuvant cisplatin-based chemotherapy. The increase in use of cisplatin in 2009, as compared with 2006, suggests that audit and feedback may be effective ways to promote such use.

Linking electronic health records to better understand breast cancer patient pathways within and between two health systems

INTRODUCTION

In a fragmented health care system, research can be challenging when one seeks to follow cancer patients as they seek care which can continue for months or years and may reflect many physician and patient decisions. Claims data track patients, but lack clinical detail. Linking routine electronic health record (EHR) data with clinical registry data allows one to gain a more complete picture of the patient journey through a cancer care episode. However, valid analytical approaches to examining care trajectories must be longitudinal and account for the dynamic nature of what is "seen" in the EHR.

METHODS

The Oncoshare database combines clinical detail from the California Cancer Registry and EHR data from two large health care organizations in the same catchment area-a multisite community practice and an academic medical center-for all women treated in either organization for breast cancer from 2000 to 2012. We classified EHR encounters data according to typical periods of the cancer care episode (screening, diagnosis, treatment) and posttreatment surveillance, as well as by facility used to better characterize patterns of care for patients seen at both organizations.

FINDINGS

We identified a "treated" cohort consisting of women receiving interventions for their initial cancer diagnosis, and classified their encounters over time across multiple dimensions (type of care, provider of care, and timing of care with respect to their cancer diagnosis). Forty-three percent of the patients were treated at the academic center only, 42 percent at the community center only, and 16 percent of the patients obtained care at both health care organizations. Compared to women seen at only one organization, the last group had similar-length initial care episodes, but more frequently had multiple episodes and longer observation periods.

DISCUSSION

Linking EHR data from neighboring systems can enhance our information on care trajectories, but careful consideration of the complexity of the treatment process and data generating mechanisms is necessary to make valid inferences.

CONCLUSION/NEXT STEPS

If analyzed as a timeline, and with careful characterization of diagnostic tests, surgical interventions, and type and frequency of physician encounters, the pathways taken by women through their breast cancer episode may lead to better understanding of patient decisions.

Decision Regret following Treatment for Localized Breast Cancer: Is Regret Stable Over Time?

BACKGROUND

While studies suggest most women have little regret regarding their breast cancer treatment decisions immediately following treatment, no studies to date have evaluated how regret may change over time.

OBJECTIVE

To measure the stability of posttreatment decision regret over time among women with breast cancer.

METHODS

Women diagnosed with breast cancer between August 2005 and May 2007 reported to the Detroit, Michigan, or Los Angeles County Surveillance, Epidemiology, and End Results (SEER) registry and completed surveys at 9 months following diagnosis (time 1) and again approximately 4 years later (time 2). A decision regret scale consisting of 5 items was summed to create 2 decision regret scores at both time 1 and time 2 (range, 0-20). Multivariable linear regression was used to examine change in regret from 9 months to 4 years. Independent variables included surgery type, receipt of reconstruction, and recurrence status at follow-up. The model controlled for demographic and clinical factors.

RESULTS

The analytic sample included 1536 women. Mean regret in the overall sample was 4.9 at time 1 and 5.4 at time 2 (P < 0.001). In the multivariable linear model, we found no difference in change in decision regret over time by surgery type. Reporting a new diagnosis of breast cancer at time 2 was associated with a 2.6-point increase in regret over time compared with women without an additional diagnosis (P = 0.003). Receipt of reconstruction was not associated with change in decision regret over time.

CONCLUSIONS

Decision regret following treatment was low and relatively stable over time for most women. Those facing an additional diagnosis of breast cancer following treatment may be at risk for elevated regret-related distress.

Reporting trends and prognostic significance of lymphovascular invasion in muscle-invasive urothelial carcinoma: a population-based study

OBJECTIVES

To investigate reporting patterns and outcomes associated with lymphovascular invasion in a general population setting.

METHODS

We identified all cystectomy patients with muscle-invasive urothelial cancer in Ontario, Canada, 1994-2008. Surgical pathology reports were analyzed for pathological variables including lymphovascular invasion. Lymphovascular invasion reporting patterns were described over time. A Cox proportional hazards model was used to evaluate the association of lymphovascular invasion with survival.

RESULTS

Of the 2802 cases identified, lymphovascular invasion status was reported in 75%. Lymphovascular invasion reporting significantly improved over the study period and was correlated with poor prognostic pathological features (T stage and N stage). Comprehensive cancer center status was not consistently associated with lymphovascular invasion reporting. Patients with lymphovascular invasion had substantially lower survival than patients who were lymphovascular invasion-negative or whose lymphovascular invasion status was unstated (P < 0.001). Lymphovascular invasion was independently associated with survival in patients regardless of lymph node metastasis. After adjusting for age, stage, comorbidity, margin status and adjuvant chemotherapy, lymphovascular invasion remained strongly associated with reduced survival (hazard ratio 1.98, 95% confidence interval 1.71-2.29).

CONCLUSIONS

Although routine reporting of lymphovascular invasion has improved over the years, pathologists appear to be biased towards evaluating lymphovascular invasion in patients with high-stage disease. Despite this bias, lymphovascular invasion remains an important prognostic factor among patients treated by cystectomy. Pathologists in general practice should report lymphovascular invasion status more consistently and urologists should hold their pathology colleagues to a higher standard.

Use of and mortality after bilateral mastectomy compared with other surgical treatments for breast cancer in California, 1998-2011

IMPORTANCE

Bilateral mastectomy is increasingly used to treat unilateral breast cancer. Because it may have medical and psychosocial complications, a better understanding of its use and outcomes is essential to optimizing cancer care.

OBJECTIVE

To compare use of and mortality after bilateral mastectomy, breast-conserving therapy with radiation, and unilateral mastectomy.

DESIGN, SETTING, AND PARTICIPANTS

Observational cohort study within the population-based California Cancer Registry; participants were women diagnosed with stages 0-III unilateral breast cancer in California from 1998 through 2011, with median follow-up of 89.1 months.

MAIN OUTCOMES AND MEASURES

Factors associated with surgery use (from polytomous logistic regression); overall and breast cancer-specific mortality (from propensity score weighting and Cox proportional hazards analysis).

RESULTS

Among 189,734 patients, the rate of bilateral mastectomy increased from 2.0% (95% CI, 1.7%-2.2%) in 1998 to 12.3% (95% CI, 11.8%-12.9%) in 2011, an annual increase of 14.3% (95% CI, 13.1%-15.5%); among women younger than 40 years, the rate increased from 3.6% (95% CI, 2.3%-5.0%) in 1998 to 33% (95% CI, 29.8%-36.5%) in 2011. Bilateral mastectomy was more often used by non-Hispanic white women, those with private insurance, and those who received care at a National Cancer Institute (NCI)-designated cancer center (8.6% [95% CI, 8.1%-9.2%] among NCI cancer center patients vs 6.0% [95% CI, 5.9%-6.1%] among non-NCI cancer center patients; odds ratio [OR], 1.13 [95% CI, 1.04-1.22]); in contrast, unilateral mastectomy was more often used by racial/ethnic minorities (Filipina, 52.8% [95% CI, 51.6%-54.0%]; OR, 2.00 [95% CI, 1.90-2.11] and Hispanic, 45.6% [95% CI, 45.0%-46.2%]; OR, 1.16 [95% CI, 1.13-1.20] vs non-Hispanic white, 35.2% [95% CI, 34.9%-35.5%]) and those with public/Medicaid insurance (48.4% [95% CI, 47.8%-48.9%]; OR, 1.08 [95% CI, 1.05-1.11] vs private insurance, 36.6% [95% CI, 36.3%-36.8%]). Compared with breast-conserving surgery with radiation (10-year mortality, 16.8% [95% CI, 16.6%-17.1%]), unilateral mastectomy was associated with higher all-cause mortality (hazard ratio [HR], 1.35 [95% CI, 1.32-1.39]; 10-year mortality, 20.1% [95% CI, 19.9%-20.4%]). There was no significant mortality difference compared with bilateral mastectomy (HR, 1.02 [95% CI, 0.94-1.11]; 10-year mortality, 18.8% [95% CI, 18.6%-19.0%]). Propensity analysis showed similar results.

CONCLUSIONS AND RELEVANCE

Use of bilateral mastectomy increased significantly throughout California from 1998 through 2011 and was not associated with lower mortality than that achieved with breast-conserving surgery plus radiation. Unilateral mastectomy was associated with higher mortality than were the other 2 surgical options.

Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment

PURPOSE

Multiple-gene sequencing is entering practice, but its clinical value is unknown. We evaluated the performance of a customized germline-DNA sequencing panel for cancer-risk assessment in a representative clinical sample.

METHODS

Patients referred for clinical BRCA1/2 testing from 2002 to 2012 were invited to donate a research blood sample. Samples were frozen at -80° C, and DNA was extracted from them after 1 to 10 years. The entire coding region, exon-intron boundaries, and all known pathogenic variants in other regions were sequenced for 42 genes that had cancer risk associations. Potentially actionable results were disclosed to participants.

RESULTS

In total, 198 women participated in the study: 174 had breast cancer and 57 carried germline BRCA1/2 mutations. BRCA1/2 analysis was fully concordant with prior testing. Sixteen pathogenic variants were identified in ATM, BLM, CDH1, CDKN2A, MUTYH, MLH1, NBN, PRSS1, and SLX4 among 141 women without BRCA1/2 mutations. Fourteen participants carried 15 pathogenic variants, warranting a possible change in care; they were invited for targeted screening recommendations, enabling early detection and removal of a tubular adenoma by colonoscopy. Participants carried an average of 2.1 variants of uncertain significance among 42 genes.

CONCLUSION

Among women testing negative for BRCA1/2 mutations, multiple-gene sequencing identified 16 potentially pathogenic mutations in other genes (11.4%; 95% CI, 7.0% to 17.7%), of which 15 (10.6%; 95% CI, 6.5% to 16.9%) prompted consideration of a change in care, enabling early detection of a precancerous colon polyp. Additional studies are required to quantify the penetrance of identified mutations and determine clinical utility. However, these results suggest that multiple-gene sequencing may benefit appropriately selected patients.

Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Biomarkers

Introduction. ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1-3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2- surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2- and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.