Payment for cancer biomarker testing

Proposal for Value-Based, Tiered Reimbursement for Tumor Biomarker Tests to Promote Innovation and Evidence Generation

Cancer precision medicine depends on high-quality tumor biomarker tests (TBTs) for treatment selection. TBT reimbursement within the United States in the current regulatory environment is not tied to premarket evidence of clinical utility, resulting in a vicious cycle wherein low-level evidence of utility leads to poor reimbursement, thereby impeding investment in developing new, clinically valuable TBTs supported by high-level evidence. Rational, value-based TBT pricing presents many practical challenges. Precise one-to-one mapping of reimbursement to cost savings or cost effectiveness is precluded by an absence of formal cost-effectiveness analyses for many emerging TBTs, and for more established TBTs, it has become clear that such analyses may yield wildly variable, subjective estimates. To address these challenges, we propose a system of tiered reimbursement that rewards development of high-quality TBTs within specific use contexts, supported by strong evidence of analytic validity and clinical utility. We propose three use contexts of TBTs, each defined by its influence on treatment decisions relative to the current standard of care-Opt-Out, Opt-In, and the use of appropriate, alternative, effective therapies (Opt-Alt). By ensuring minimum levels of reimbursement, this system provides a return on investment to encourage and support the research and development needed to generate high levels of evidence for claims of clinical utility for TBTs by using a robust, objective, and value-based system. We believe our proposed evaluation system will serve as a practical starting point to raise the bar for TBT quality and utility, which has the potential to redirect health care dollars from futile or ineffective treatment to investment in the development of high-quality TBTs needed for safe and effective precision cancer care.

Precision Medicine and Non-Colorectal Cancer Liver Metastases: Fiction or Reality?

BACKGROUND

Non-colorectal liver metastases (nCRLM) constitute a variety of heterogeneous diseases and a considerable therapeutic challenge. Management is based on the primary tumor and the clinical course. In the era of precision medicine (PM) we know that cancer is heterogeneous within the tumor and across different sites.

METHODS

We give an overview of the path to PM through 'omics' beyond genomics. We refer to the experience gained to date from models such as colorectal cancer and we discuss the opportunity offered by PM for the management of nCRLM.

RESULTS

In order to best characterize and track tumor biological behaviors as well as to understand mechanisms of response to therapy and survival we suggest the application of novel clinical trial designs, a dynamic approach with serial monitoring involving evaluation of primary and metastatic sites. Quality and standardization of tissue acquisition and biobanking is a precondition for the reliability of this approach.

CONCLUSION

The application of PM is increasingly becoming a reality. Elucidating the mysteries of tumors in complex settings can only be achieved with the approach PM offers. nCRLM may serve as a model for the application of PM principles and techniques in understanding individual diseases and also cancer as an entity and therapeutic challenge.

PD-L1 and Lung Cancer: The Era of Precision-ish Medicine?

The success of immune checkpoint inhibitor therapy in lung cancer, both in squamous and nonsquamous non-small cell carcinoma, has led to US Food and Drug Administration approval for 2 medications that have as part of their prescribing information an associated immunohistochemistry-based companion or complementary diagnostic test for programmed death ligand-1 (PD-L1). The intense interest in drug development in this area has resulted in additional agents with associated diagnostics looming on the horizon in 2016. In the era of precision medicine, the paradigm of paired molecular target and molecular test, which serves as a model of oncogenic mutation-driven cancer therapy, is challenged by the proliferation of immunohistochemistry-based tests with different antibodies, instruments, and scoring. The difficulty inherent to targeted therapy aimed at a moving target is discussed, as well as the emerging challenges to pathologists and oncologists who seek to optimize care in this complex therapeutic arena.

A Standardized DNA Variant Scoring System for Pathogenicity Assessments in Mendelian Disorders

We developed a rules‐based scoring system to classify DNA variants into five categories including pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, and benign. Over 16,500 pathogenicity assessments on 11,894 variants from 338 genes were analyzed for pathogenicity based on prediction tools, population frequency, co‐occurrence, segregation, and functional studies collected from internal and external sources. Scores were calculated by trained scientists using a quantitative framework that assigned differential weighting to these five types of data. We performed descriptive and comparative statistics on the dataset and tested interobserver concordance among the trained scientists. Private variants defined as variants found within single families (n = 5,182), were either VUS (80.5%; n = 4,169) or likely pathogenic (19.5%; n = 1,013). The remaining variants (n = 6,712) were VUS (38.4%; n = 2,577) or likely benign/benign (34.7%; n = 2,327) or likely pathogenic/pathogenic (26.9%, n = 1,808). Exact agreement between the trained scientists on the final variant score was 98.5% [95% confidence interval (CI) (98.0, 98.9)] with an interobserver consistency of 97% [95% CI (91.5, 99.4)]. Variant scores were stable and showed increasing odds of being in agreement with new data when re‐evaluated periodically. This carefully curated, standardized variant pathogenicity scoring system provides reliable pathogenicity scores for DNA variants encountered in a clinical laboratory setting.