Oncologist and organizational factors associated with variation in breast cancer multigene testing

Performance of a novel spectroscopy-based tool for adjuvant therapy decision-making in hormone receptor-positive breast cancer: a validation study

PURPOSE

Digistain Index (DI), measured using an inexpensive mid-infrared spectrometer, reflects the level of aneuploidy in unstained tissue sections and correlates with tumor grade. We investigated whether incorporating DI with other clinicopathological variables could predict outcomes in patients with early breast cancer.

METHODS

DI was calculated in 801 patients with hormone receptor-positive, HER2-negative primary breast cancer and ≤ 3 positive lymph nodes. All patients were treated with systemic endocrine therapy and no chemotherapy. Multivariable proportional hazards modeling was used to incorporate DI with clinicopathological variables to generate the Digistain Prognostic Score (DPS). DPS was assessed for prediction of 5- and 10-year outcomes (recurrence, recurrence-free survival [RFS] and overall survival [OS]) using receiver operating characteristics and Cox proportional hazards regression models. Kaplan-Meier analysis evaluated the ability of DPS to stratify risk.

RESULTS

DPS was consistently highly accurate and had negative predictive values for all three outcomes, ranging from 0.96 to 0.99 at 5 years and 0.84 to 0.95 at 10 years. DPS demonstrated statistically significant prognostic ability with significant hazard ratios (95% CI) for low- versus high-risk classification for RFS, recurrence and OS (1.80 [CI 1.31-2.48], 1.83 [1.32-2.52] and 1.77 [1.28-2.43], respectively; all P < 0.001).

CONCLUSION

DPS showed high accuracy and predictive performance, was able to stratify patients into low or high-risk, and considering its cost and rapidity, has the potential to offer clinical utility.

Importance of Patient Health Insurance Coverage and Out-of-Pocket Costs for Genomic Testing in Oncologists' Treatment Decisions

PURPOSE

Use of genomic testing, especially multimarker panels, is increasing in the United States. Not all tests and related treatments are covered by health insurance, which can result in substantial patient out-of-pocket (OOP) costs. Little is known about oncologists' treatment decisions with respect to patient insurance coverage and OOP costs for genomic testing.

METHODS

We identified 1,049 oncologists who used multimarker tumor panels from the 2017 National Survey of Precision Medicine in Cancer Treatment. Separate multivariable ordinal logistic regressions examined associations of oncologist-, practice-, and area-level characteristics and oncologists' ratings of importance (very, somewhat, or a little/not important) of insurance coverage and OOP costs for genomic testing in treatment decisions, adjusting for oncologist years of experience, sex, race and ethnicity, specialty, use of next-generation sequencing (NGS) tests, region, tumor boards, patient insurance mix, and area-level socioeconomic characteristics.

RESULTS

Among oncologists, 47.3%, 32.7%, and 20.0% reported that patient insurance coverage for genomic testing was very, somewhat, or a little/not important, respectively, in treatment decisions. In addition, 56.9%, 28.0%, and 15.2% reported that OOP costs for testing were very, somewhat, or a little/not important, respectively. In adjusted analyses, oncologists who used NGS tests were more likely to report patient insurance and OOP costs as important (odds ratio [OR], 2.00 [95% CI, 1.16 to 3.45] and OR, 2.12 [95% CI, 1.22 to 3.68], respectively) in treatment decisions compared with oncologists who did not use these tests, as were oncologists who treated solid tumors, rather than only hematological cancers. More years of experience and higher percentages of Medicaid or self-paid/uninsured patients in the practice were associated with reporting insurance coverage (OR, 1.43 [95% CI, 1.09 to 1.89]) and OOP costs (OR, 1.51 [95% CI, 1.13 to 2.01]) as important. Oncologists in practices with molecular tumor boards for genomic tests were less likely to report coverage (OR, 0.63 [95% CI, 0.47 to 0.85]) and OOP costs (OR, 0.72 [95% CI, 0.53 to 0.97]) as important than their counterparts in practices without these tumor boards.

CONCLUSION

Most oncologists rate patient health insurance and OOP costs for genomic tests as important considerations in subsequent treatment recommendations. Modifiable factors associated with these ratings can inform interventions to support patient-physician decision making about care.

Tracing the potential of networks to improve community cancer care: an in-depth single case study

Background

Despite overall declines in cancer mortality in the USA over the past three decades, many patients in community settings fail to receive evidence-based cancer care. Networks that link academic medical centers (AMCs) and community providers may reduce disparities by creating access to specialized expertise and care, but research on network effectiveness is mixed. The objective of this study was to identify factors related to whether and how an exemplar AMC network served to provide advice and referral access in community settings.

Methods

An embedded in–depth single case study design was employed to study a network in the Midwest USA that connects a leading cancer specialty AMC with community practices. The embedded case units were a subset of 20 patients with young-onset colorectal cancer or risk-related conditions and the providers involved in their care. The electronic health record (EHR) was reviewed from January 1, 1990, to February 28, 2018. Social network analysis identified care, advice, and referral relationships. Within-case process tracing provided detailed accounts of whether and how the network provided access to expert, evidence-based care or advice in order to identify factors related to network effectiveness.

Results

The network created access to evidence-based advice or care in some but not all case units, and there was variability in whether and how community providers engaged the network, including the path for referrals to the AMC and the way in which advice about an evidence-based approach to care was communicated from AMC specialists to community providers. Factors related to instances when the network functioned as intended included opportunities for both rich and lean communication between community providers and specialists, coordinated referrals, and efficient and adequately utilized documentation systems.

Conclusions

Network existence alone is insufficient to open up access to evidence-based expertise or care for patients in community settings. In-depth understanding of how this network operated provides insight into factors that support or inhibit the potential of networks to minimize disparities in access to evidence-based community cancer care, including both personal and organizational factors.

Feasibility of Measuring Preferences for Chemotherapy Among Early-Stage Breast Cancer Survivors Using a Direct Rank Ordering Multicriteria Decision Analysis Versus a Time Trade-Off

OBJECTIVES

Chemotherapy is increasingly a preference-based choice among women diagnosed with early-stage breast cancer. Multicriteria decision analysis (MCDA) is a promising but underutilized method to facilitate shared decision making. We explored the feasibility of conducting an MCDA using direct rank ordering versus a time trade-off (TTO) to assess chemotherapy choice in a large population-based sample.

METHODS

We surveyed 904 early-stage breast cancer survivors who were within 5 years of diagnosis and reported to the Western Washington State Cancer System and Kaiser Permanente Northern California registries. Direct rank ordering of 11 criteria and TTO surveys were conducted from September 2015 to July 2016; clinical data were obtained from registries or medical records. Multivariable regressions estimated post hoc associations between the MCDA, TTO, and self-reported chemotherapy receipt, considering covariates.

RESULTS

Survivors ranged in age from 25 to 74 years and 73.9% had stage I tumors. The response rate for the rank ordering was 81.0%; TTO score was 94.2%. A one-standard deviation increase in the difference between the chemotherapy and no chemotherapy MCDA scores was associated with a 75.1% (95% confidence interval 43.9-109.7%; p < 0.001) increase in the adjusted odds of having received chemotherapy; no association was found between the TTO score and chemotherapy receipt.

CONCLUSIONS

A rank-order-based MCDA was feasible and was associated with chemotherapy choice. Future research should consider developing and testing this MCDA for use in clinical encounters. Additional research is required to develop a TTO-based model and test its properties against a pragmatic MCDA to inform future shared decision-making tools.

The leadership behaviors needed to implement clinical genomics at scale: a qualitative study

PURPOSE

To investigate leadership in clinical genomics and identify likely implications of different leadership approaches for future implementation of clinical genomics.

METHODS

We undertook 37 interviews in a cross-sectional qualitative study examining implementation of clinical genomics in Australia. Participants were either nongenetic medical specialists working with genomic initiatives (e.g., immunologists, nephrologists) or working at a service/organizational level (e.g., department heads, chief medical officers). We identified participants as genomic migrants (long-established practitioners) and genomic natives (those medical specialists coming into independent practice with genomic technology in situ). Data were analyzed deductively with reference to leadership approach.

RESULTS

Leadership approaches were often blended or reported to iteratively support development of another. There was concern at both the absence or the excess of entrepreneurial leadership (i.e., risk-taking).

CONCLUSION

Entrepreneurial leadership is needed to promote innovativeness, risk-taking, and proactivity, essential in these early stages of clinical genomics. Shared decision-making is required from a wide range of clinicians, calling for both clinical and distributed leadership. Sharing leadership, and the potential loss of positional status from formal senior positions, may prove challenging to genomics "migrants," who are essential for nurturing genomic "natives." Clinicians will need support from their organizations and professional bodies to manage the transition.

Factors Associated With Oncologist Discussions of the Costs of Genomic Testing and Related Treatments

BACKGROUND

Use of genomic testing is increasing in the United States. Testing can be expensive, and not all tests and related treatments are covered by health insurance. Little is known about how often oncologists discuss costs of testing and treatment or about the factors associated with those discussions.

METHODS

We identified 1220 oncologists who reported discussing genomic testing with their cancer patients from the 2017 National Survey of Precision Medicine in Cancer Treatment. Multivariable polytomous logistic regression analyses were used to assess associations between oncologist and practice characteristics and the frequency of cost discussions. All statistical tests were two-sided.

RESULTS

Among oncologists who discussed genomic testing with patients, 50.0% reported often discussing the likely costs of testing and related treatments, 26.3% reported sometimes discussing costs, and 23.7% reported never or rarely discussing costs. In adjusted analyses, oncologists with training in genomic testing or working in practices with electronic medical record alerts for genomic tests were more likely to have cost discussions sometimes (odds ratio [OR] = 2.09, 95% confidence interval [CI] = 1.19 to 3.69) or often (OR = 2.22, 95% CI = 1.30 to 3.79), respectively, compared to rarely or never. Other factors statistically significantly associated with more frequent cost discussions included treating solid tumors (rather than only hematological cancers), using next-generation sequencing gene panel tests, having higher patient volume, and working in practices with higher percentages of patients insured by Medicaid, or self-paid or uninsured.

CONCLUSIONS

Interventions targeting modifiable oncologist and practice factors, such as training in genomic testing and use of electronic medical record alerts, may help improve cost discussions about genomic testing and related treatments.

Health Economics Tools and Precision Medicine: Opportunities and Challenges

Precision medicine - individualizing care for patients and addressing variations in treatment response - is likely to be important in improving the nation's health in a cost-effective manner. Despite this promise, widespread use of precision medicine, specifically genomic markers, in clinical care has been limited in practice to date. Lack of evidence, clear evidence thresholds, and reimbursement have been cited as major barriers. Health economics frameworks and tools can elucidate the effects of legal, regulatory, and reimbursement policies on the use of precision medicine while guiding research investments to enhance the appropriate use of precision medicine. Despite the capacity of economics to enhance the clinical and human impact of precision medicine, application of health economics to precision medicine has been limited - in part because precision medicine is a relatively new field - but also because precision medicine is complex, both in terms of its applications and implications throughout medicine and the healthcare system. The goals of this review are several-fold: (1) provide an overview of precision medicine and key policy challenges for the field; (2) explain the potential utility of economics methods in addressing these challenges; (3) describe recent research activities; and (4) summarize opportunities for cross-disciplinary research.

Expected Monetary Impact of Oncotype DX Score-Concordant Systemic Breast Cancer Therapy Based on the TAILORx Trial

BACKGROUND

TAILORx demonstrated that women with node-negative, hormone receptor-positive, HER2-negative breast cancers and Oncotype DX recurrence scores (RS) of 0-25 had similar 9-year outcomes with endocrine vs chemo-endocrine therapy; evidence for women aged 50 years and younger and RS 16-25 was less clear. We estimated how expected changes in practice following the trial might affect US costs in the initial 12 months of care (initial costs).

METHODS

Data from Surveillance, Epidemiology, and End Results (SEER), SEER-Medicare, and SEER-Genomic Health Inc datasets were used to estimate Oncotype DX testing and chemotherapy rates and mean initial costs pre- and post-TAILORx (in 2018 dollars), assuming all women received Oncotype DX testing and score-suggested therapy posttrial. Sensitivity analyses tested the impact on costs of assumptions about compliance with testing and score-suggested treatment and estimation methods.

RESULTS

Pretrial mean initial costs were $2.816 billion. Posttrial, Oncotype DX testing costs were projected to increase from $115 to $231 million and chemotherapy use to decrease from 25% to 17%, resulting in initial care costs of $2.766 billion, or a net savings of $49 million (1.8% decrease). A small net savings was seen under most assumptions. The one exception was if all women aged 50 years and younger with tumors with RS 16-25 elected to receive chemotherapy, initial care costs could increase by $105 million (4% increase).

CONCLUSIONS

Personalizing breast cancer treatment based on tumor genetic profiles could result in small cost decreases in the initial 12 months of care. Studies are needed to evaluate the long-term costs and nonmonetary benefits of personalized cancer care.

Uptake of the 21-Gene Assay Among Women With Node-Positive, Hormone Receptor−Positive Breast Cancer

Background: This study assessed uptake of the Oncotype DX 21-gene assay over time and characterized which sociodemographic and clinical factors are associated with test uptake among women with lymph node−positive (LN+), hormone receptor−positive, HER2-negative breast cancer. Methods: Invasive breast cancer cases diagnosed in 2010 through 2013 were included from a SEER database linked to 21-gene assay results performed at Genomic Health’s Clinical Laboratory. Factors associated with 21-gene assay uptake were identified using a multivariable logistic regression model. Results: Uptake of the 21-gene assay increased over time and differed by race, socioeconomic status (SES), and age. In the multivariable model, when clinical and SES variables were controlled for, racial differences in test uptake were no longer observed. Private insurance status was associated with higher odds of 21-gene assay uptake (Medicaid vs private insurance: adjusted odds ratio, 0.86; P=.02), and high area-level SES was associated with an increased odds of uptake (quintile 5 vs 1: adjusted odds ratio, 1.6; P<.001). Demographic factors such as age and marital status influenced test uptake, and use varied greatly by geographic region. Uptake of the 21-gene assay increased over time and preceded the assay’s inclusion in the NCCN Guidelines for LN+ breast cancer. Differences in uptake by race, SES, and age have persisted over time. However, when clinical and SES variables were controlled for, racial differences in assay uptake were no longer observed. Socioeconomic variables, such as health insurance type and area-level SES, were associated with assay uptake. Conclusions: Future research should continue to document practice patterns related to the 21-gene assay. Given variation in testing associated with area-level SES, insurance coverage, and geographic region, interventions to understand and reduce differential uptake are needed to ensure equitable access to this genomic test.

The impact of gene expression profile testing on confidence in chemotherapy decisions and prognostic expectations

PURPOSE

Little is known about whether gene expression profile (GEP) testing and specific recurrence scores (e.g., medium risk) improve women's confidence in their chemotherapy decision or perceived recurrence risk. We evaluate the relationship between these outcomes and GEP testing.

METHODS

We surveyed women eligible for GEP testing (stage I or II, Gr1-2, ER+, HER2-) identified through the Surveillance, Epidemiology, and End Results (SEER) Registry of Washington or Kaiser Permanente Northern California from 2012 to 2016, approximately 0-4 years from diagnosis (N = 904, RR = 45.4%). Confidence in chemotherapy was measured as confident (Very, completely) versus Not Confident (Somewhat, A little, Not At All); perceived risk recurrence was recorded numerically (0-100%). Women reported their GEP test receipt (Yes, No, Unknown) and risk recurrence score (High, Intermediate, Low, Unknown). In our analytic sample (N = 833), we propensity score weighted the three test receipt cohorts and used propensity weighted multivariable regressions to examine associations between the outcomes and the three test receipt cohorts, with receipt stratified by score.

RESULTS

29.5% reported an unknown GEP test receipt; 86% being confident. Compared to no test receipt, an intermediate score (aOR 0.34; 95% CI 0.20-0.58), unknown score (aOR 0.09; 95% CI 0.05-0.18), and unknown test receipt (aOR 0.37; 95% CI 0.24-0.57) were less likely to report confidence. Most women greatly overestimated their recurrence risk regardless of their test receipt or score.

CONCLUSIONS

GEP testing was not associated with greater confidence in chemotherapy decisions. Better communication about GEP testing and the implications for recurrence risk may improve women's decisional confidence.