The Role of Proteomic Testing in Improving Prognosis And Care Planning Quality Measures for Lung Cancer.

Page RD1, Argento AC2, Nash DB3, Skoufalos A3, Schaefer ES4.

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Abstract

PURPOSE:

The Oncology Care Model (OCM) is a payment model from the Centers for Medicare and Medicaid Services designed to reduce costs and improve quality in cancer care. Key components of quality for the OCM originate from the 13-component cancer care plan. We surveyed the literature to understand the value of prognosis in OCM-directed planning for non-small-cell lung cancer (NSCLC) care and to investigate how the results of a prognostic, proteomic biomarker test, the VeriStrat test, can help OCM-participating providers meet the specific quality measures.

DESIGN:

A targeted literature review was supplemented by real-world author experience.

METHODOLOGY:

Available MEDLINE-indexed literature on the topic of lung cancer prognosis and cancer care planning (1997-2017) were reviewed. Authors also included relevant commentary based on their own real-world experience with VeriStrat testing and prognostic conversations.

RESULTS:

There was near-universal consensus in guidelines and literature about the critical importance of early, candid, and ongoing physician-patient discussions about prognosis, which informs most components of the OCM care plan. The VeriStrat test has been shown to provide accurate predictions of outcomes in all lines of therapy and in various treatments for patients with NSCLC, including chemotherapies and EGFR-TKI therapies.

CONCLUSION:

Accurate prognostic estimates, such as those provided by the VeriStrat test, are useful for predicting and documenting expected response to treatment, avoiding ineffective and costly overtreatment and for facilitating meaningful conversations with NSCLC patients about the timing of best supportive care and hospice care when appropriate, thereby improving cancer care planning and quality scores.

KEYWORDS:

Oncology Care Model; care planning; end of life; lung cancer; physician patient communication; prognosis; proteomics; quality measures; treatment preferences