Methodology for Using Real-World Data From Electronic Health Records to Assess Chemotherapy Administration in Women With Breast Cancer.

PURPOSE: Identification of patients' intended chemotherapy regimens is critical to most research questions conducted in the real-world setting of cancer care. Yet, these data are not routinely available in electronic health records (EHRs) at the specificity required to address these questions. We developed a methodology to identify patients' intended regimens from EHR data in the Optimal Breast Cancer Chemotherapy Dosing (OBCD) study. METHODS: In women older than 18 years, diagnosed with primary stage I-IIIA breast cancer at Kaiser Permanente Northern California (2006-2019), we categorized participants into 24 drug combinations described in National Comprehensive Cancer Network guidelines for breast cancer treatment. Participants were categorized into 50 guideline chemotherapy administration schedules within these combinations using an iterative algorithm process, followed by chart abstraction where necessary. We also identified patients intended to receive nonguideline administration schedules within guideline drug combinations and nonguideline drug combinations. This process was adapted at Kaiser Permanente Washington using abstracted data (2004-2015). RESULTS: In the OBCD cohort, 13,231 women received adjuvant or neoadjuvant chemotherapy, of whom 10,213 (77%) had their intended regimen identified via the algorithm, 2,416 (18%) had their intended regimen identified via abstraction, and 602 (4.5%) could not be identified. Across guideline drug combinations, 111 nonguideline dosing schedules were used, alongside 61 nonguideline drug combinations. A number of factors were associated with requiring abstraction for regimen determination, including: decreasing neighborhood household income, earlier diagnosis year, later stage, nodal status, and human epidermal growth factor receptor 2 (HER2)+ status. CONCLUSION: We describe the challenges and approaches to operationalize complex, real-world data to identify intended chemotherapy regimens in large, observational studies. This methodology can improve efficiency of use of large-scale clinical data in real-world populations, helping answer critical questions to improve care delivery and patient outcomes.

Costs to Medicare of Nonrecommended Bone-Modifying Agent Use for Castration-Sensitive Prostate Cancer.

PURPOSE: Bone-modifying agents (BMAs) do not prevent skeletal-related events among patients with castration-sensitive prostate cancer (CSPC), but many patients receive BMAs unnecessarily. The costs to Medicare from overuse have not been assessed. METHODS: We used linked SEER-Medicare data 2011-2015 to measure the frequency and number of doses of zoledronic acid (ZA) and denosumab received during CSPC (between diagnosis and initiation of metastatic, castration resistant prostate cancer therapy). We estimated excess BMA among patients who received BMA therapy for CSPC and did not have an indication for osteoporosis fracture prevention. We used the Medicare fee schedule for drug prices and peer-reviewed sources to estimate adverse event frequencies and costs. RESULTS: Median CSPC duration was 387 days (IQR, 253-573), during which time 42% of patients received ≥one dose of denosumab (mean doses, 7) and 18% received ≥one dose of ZA (mean doses, 7). Thirty-eight percent of those receiving denosumab and 47% of those receiving ZA had a history of osteoporosis, osteopenia, spine or hip fracture, or hypercalcemia. The estimated, annual excess BMA cost to Medicare was $44,105,041 in US dollars (USD), composed of $43,303,078 USD and $45,512 USD in drug costs for denosumab and ZA, respectively, and $682,865 USD and $75,585 USD in adverse event costs, respectively. In one-way sensitivity analysis, the estimate was most sensitive to denosumab dosing frequency (estimate range, $28,469,237 USD-$98,830,351 USD) and duration of CSPC (estimate range, $36,823,311 USD-$99,015,908 USD). CONCLUSION: BMA overuse in CSPC incurs substantial cost to Medicare, largely because of denosumab drug costs. Excess costs may be reduced by greater adherence to guideline-concordant BMA use.

Evaluation of Algorithms Using Automated Health Plan Data to Identify Breast Cancer Recurrences.

BACKGROUND: We updated algorithms to identify breast cancer recurrences from administrative data, extending previously developed methods. METHODS: In this validation study, we evaluated pairs of breast cancer recurrence algorithms (vs. individual algorithms) to identify recurrences. We generated algorithm combinations that categorized discordant algorithm results as no recurrence [High Specificity and PPV (positive predictive value) Combination] or recurrence (High Sensitivity Combination). We compared individual and combined algorithm results to manually abstracted recurrence outcomes from a sample of 600 people with incident stage I-IIIA breast cancer diagnosed between 2004 and 2015. We used Cox regression to evaluate risk factors associated with age- and stage-adjusted recurrence rates using different recurrence definitions, weighted by inverse sampling probabilities. RESULTS: Among 600 people, we identified 117 recurrences using the High Specificity and PPV Combination, 505 using the High Sensitivity Combination, and 118 using manual abstraction. The High Specificity and PPV Combination had good specificity [98%, 95% confidence interval (CI): 97-99] and PPV (72%, 95% CI: 63-80) but modest sensitivity (64%, 95% CI: 44-80). The High Sensitivity Combination had good sensitivity (80%, 95% CI: 49-94) and specificity (83%, 95% CI: 80-86) but low PPV (29%, 95% CI: 25-34). Recurrence rates using combined algorithms were similar in magnitude for most risk factors. CONCLUSIONS: By combining algorithms, we identified breast cancer recurrences with greater PPV than individual algorithms, without additional review of discordant records. IMPACT: Researchers should consider tradeoffs between accuracy and manual chart abstraction resources when using previously developed algorithms. We provided guidance for future studies that use breast cancer recurrence algorithms with or without supplemental manual chart abstraction.

Physician knowledge, practice patterns, and barriers encountered regarding guideline-concordant use of bone modifying agents for prostate cancer.

BACKGROUND: Guidelines recommend bone-modifying agents (BMAs) for patients with castrate-resistant prostate cancer (CRPC) and bone metastasis, but not for castrate-sensitive prostate cancer (CSPC). Physicians beliefs and practices regarding BMA therapy are poorly understood. METHODS: This was a qualitative interview study with embedded Likert-scale elements. Study participants were physicians who treat prostate cancer, located within an academic cancer center or an affiliated community-based network. Participants were asked about their experiences and practice patterns regarding BMA therapy. Participants used Likert-scale items to identify the most common barriers to guideline-concordant BMA use and the most effective potential interventions. Participants were subsequently asked to rank the three most common barriers and the three most effective interventions to reduce underuse (for CRPC) and overuse (for CSPC). RESULTS: Nineteen physicians were invited and 15 participated; one physician did not answer some questions as outside of their practice scope. All were aware of the recommendation for BMAs in CRPC. 14% (2/14) were unaware of the recommendation against BMA use for CSPC; an additional 29% (4/14) believed that BMA use could be appropriate for CSPC depending on the metastatic disease burden. 36% (5/14) were unaware of recommendations for screening and treatment of low bone mineral density. The most common barriers (occurring "often" or "sometimes") were obtaining dental clearance (11/15) and insufficient clinic time (6/15). The interventions identified as most effective to reduce underuse were dental navigation (11/15) and electronic medical record (EMR)-based guidance (9/15). The interventions identified as most effective to reduce overuse were peer-to-peer education (14/15) and EMR-based guidance (13/15). CONCLUSIONS: Awareness of guideline recommendations for screening and treatment of low bone mineral density and against BMA use for CSPC was good, but not complete. Dental navigation, peer-to-peer education, and EMR-based guidance were preferred intervention strategies to improve guideline-concordant use.

Methods for retrospectively improving race/ethnicity data quality: a scoping review.

Improving race and ethnicity (hereafter, race/ethnicity) data quality is imperative to ensure underserved populations are represented in data sets used to identify health disparities and inform health care policy. We performed a scoping review of methods that retrospectively improve race/ethnicity classification in secondary data sets. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searches were conducted in the MEDLINE, Embase, and Web of Science Core Collection databases in July 2022. A total of 2 441 abstracts were dually screened, 453 full-text articles were reviewed, and 120 articles were included. Study characteristics were extracted and described in a narrative analysis. Six main method types for improving race/ethnicity data were identified: expert review (n = 9; 8%), name lists (n = 27, 23%), name algorithms (n = 55, 46%), machine learning (n = 14, 12%), data linkage (n = 9, 8%), and other (n = 6, 5%). The main racial/ethnic groups targeted for classification were Asian (n = 56, 47%) and White (n = 51, 43%). Some form of validation evaluation was included in 86 articles (72%). We discuss the strengths and limitations of different method types and potential harms of identified methods. Innovative methods are needed to better identify racial/ethnic subgroups and further validation studies. Accurately collecting and reporting disaggregated data by race/ethnicity are critical to address the systematic missingness of relevant demographic data that can erroneously guide policymaking and hinder the effectiveness of health care practices and intervention.