Long-Term Patterns of Oral Anticancer Agent Adoption, Duration, and Switching in Patients With CML

BACKGROUND

Oral tyrosine kinase inhibitors (TKIs) have been the standard of care for chronic myeloid leukemia (CML) since 2001. However, few studies have evaluated changes in the treatment landscape of CML over time. This study assessed the long-term treatment patterns of oral anticancer therapies among patients with CML.

METHODS

This retrospective cohort study included patients newly diagnosed with CML between January 1, 2000, and December 31, 2016, from 10 integrated healthcare systems. The proportion of patients treated with 5 FDA-approved oral TKI agents-bosutinib, dasatinib, imatinib, nilotinib, and ponatinib-in the 12 months after diagnosis were measured, overall and by year, between 2000 and 2017. We assessed the use of each oral agent through the fourth-line setting. Multivariable logistic regression estimated the odds of receiving any oral agent, adjusting for sociodemographic and clinical characteristics.

RESULTS

Among 853 patients with CML, 81% received an oral agent between 2000 and 2017. Use of non-oral therapies decreased from 100% in 2000 to 5% in 2005, coinciding with imatinib uptake from 65% in 2001 to 98% in 2005. Approximately 28% of patients switched to a second-line agent, 9% switched to a third-line agent, and 2% switched to a fourth-line agent. Adjusted analysis showed that age at diagnosis, year of diagnosis, and comorbidity burden were statistically significantly associated with odds of receiving an oral agent.

CONCLUSIONS

A dramatic shift was seen in CML treatments away from traditional, nonoral chemotherapy toward use of novel oral TKIs between 2000 and 2017. As the costs of oral anticancer agents reach new highs, studies assessing the long-term health and financial outcomes among patients with CML are warranted.

Clinical Molecular Marker Testing Data Capture to Promote Precision Medicine Research Within the Cancer Research Network

PURPOSE

To evaluate health care systems for the availability of population-level data on the frequency of use and results of clinical molecular marker tests to inform precision cancer care.

METHODS

We assessed cancer-related molecular marker test data availability across 12 US health care systems in the Cancer Research Network. Overall, these systems provide care to a diverse population of more than 12 million people in the United States. We performed qualitative analyses of test data availability for five blood-based protein, nine germline, and 14 tissue-based tumor marker tests in each health care system's electronic health record and tumor registry using key informants, test code lists, and manual review of data types and output. We then performed quantitative analyses to estimate the proportion of patients with cancer with test utilization data and results for specific molecular marker tests.

RESULTS

Health systems were able to systematically capture population-level data on all five blood protein markers, six of 14 tissue-based tumor markers, and none of the nine germline markers. Successful, systematic data capture was achievable for tests with electronic data feeds for test results (blood protein markers) or through prior manual abstraction by tumor registrars (select tumor-based markers). For test results stored in scanned image files (particularly germline and tumor marker tests), information on which test was performed and test results was not readily accessible in an electronic format.

CONCLUSION

Even in health care systems with sophisticated electronic health records, there were few codified data elements available for evaluating precision cancer medicine test use and results at the population level. Health care organizations should establish standards for electronic reporting of precision medicine tests to expedite cancer research and facilitate the implementation of precision medicine approaches.

Geospatial Monitoring of Body Mass Index: Use of Electronic Health Record Data Across Health Care Systems

OBJECTIVES

The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations.

MATERIALS AND METHODS

We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region.

RESULTS

We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region.

PRACTICE IMPLICATIONS

The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.

Predicting 5-Year Risk of RRT in Stage 3 or 4 CKD: Development and External Validation

BACKGROUND AND OBJECTIVES

Only a minority of patients with CKD progress to renal failure. Despite the potential benefits of risk stratification in the CKD population, risk prediction models are not routinely used. Our objective was to develop and externally validate a clinically useful and pragmatic prediction model for the 5-year risk of progression to RRT in stage 3 or 4 CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We used a retrospective cohort design. The development cohort consisted of 22,460 Kaiser Permanente Northwest members with stage 3 or 4 CKD (baseline 2002-2008). The validation cohort consisted of 16,553 Kaiser Permanente Colorado members with stage 3-4 CKD (baseline 2006-2008). The final model included eight predictors: age, sex, eGFR, hemoglobin, proteinuria/albuminuria, systolic BP, antihypertensive medication use, and diabetes and its complications.

RESULTS

In the Northwest and Colorado cohorts, there were 737 and 360 events, and observed 5-year Kaplan-Meier risks of 4.72% (95% confidence interval [95% CI], 4.38 to 5.06) and 2.57% (95% CI, 2.30 to 2.83), respectively. Our prediction model performed extremely well in the development cohort, with a c-statistic of 0.96, an R2 of 79.7%, and good calibration. We had similarly good performance in the external validation cohort, with a c-statistic of 0.95, R2 of 81.2%, and good calibration. In the external validation cohort, the observed risk was slightly lower than the predicted risk in the highest-risk quintile. Using the top quintile of predicted risk as a cutpoint gave a sensitivity of 92.2%.

CONCLUSIONS

We developed a pragmatic prediction model and risk score for predicting the 5-year RRT risk in stage 3 and 4 CKD. This model uses variables that are typically available in routine primary care settings, and can be used to help guide important decisions such as timing of referral to nephrology and fistula placement.