Feasibility Of Precision Oncology Virtual Tumor Boards To Optimize Direct Point-Of-Care Management And Clinical Trial Enrollment Of Advanced Cancer Patients

Feasibility Of Precision Oncology Virtual Tumor Boards To Optimize Direct Point-Of-Care Management And Clinical Trial Enrollment Of Advanced Cancer Patients

Feasibility Of Precision Oncology Virtual Tumor Boards To Optimize Direct Point-Of-Care Management And Clinical Trial Enrollment Of Advanced Cancer Patients

A Loaiza-Bonilla, S Kurnaz, K Johnston, C Culcuoglu, B Arango

November 6, 2017

Objectives

Precision oncology encompasses the implementation of high level of evidence disease-specific and biomarker-driven diagnostic and treatment recommendations for optimized cancer care. This can be noted as feasibility of precision oncology. Telemedicine and value-based care may optimize clinical trial enrollment and overall cost-benefit. We evaluated the feasibility and clinical utility of a precision oncology virtual tumor boards (VTB) program, and its clinical impact on community-dwelling patients with advanced solid tumors to facilitate point-of-care management and clinical trial enrollment, as well as the financial impact and potential outcomes of the intervention.

Methods

We report the results on the initial 10 VTB-evaluated patients of an ongoing prospective qualitative case study screened between October 2016 and March 2017. Eligibility required written informed consent. Cases were evaluated by a patient-activated multidisciplinary VTB. A Markov model by incorporating clinical, utility and cost data was developed to evaluate economic outcome of VTB regarding survival and cost-of-care. Using a proprietary knowledge-base, parametric survival analyses of patient-level progression-free (PFS) and overall survival (OS) data from reported clinical trials in known sources were performed. Average Sales Prices public data sources were used to estimate unit treatment costs and duration of subsequent active therapies. Oncology-modeled patient pathways, expert opinion and Delphi panel methods were used for assumptions.

Results

The VTB identified clinical trials for 80% of these heavily treated patients, and 50% of patients decided to pursue a clinical trial. VTB resulted in data that impacted clinical decisions in 100% of cases. VTB achieved 88% cost reduction compared to standard therapies due to clinical trial enrollment (517,000USD vs 61,000USD). Treatment options as prioritized by VTB also provided an estimated reported PFS advantage (6.3 months) compared to standard therapy (3.6 months).

Conclusions

These results demonstrate the feasibility and benefits of incorporating precision oncology VTB into clinical practice, including its value as clinical trial recruitment engine and as a cost-effective, value-based measure for innovative care delivery models.

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  • Svalbard and Jan Mayen+47
  • Sweden (Sverige)+46
  • Switzerland (Schweiz)+41
  • Syria (‫سوريا‬‎)+963
  • Taiwan (台灣)+886
  • Tajikistan+992
  • Tanzania+255
  • Thailand (ไทย)+66
  • Timor-Leste+670
  • Togo+228
  • Tokelau+690
  • Tonga+676
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  • Tunisia (‫تونس‬‎)+216
  • Turkey (Türkiye)+90
  • Turkmenistan+993
  • Turks and Caicos Islands+1
  • Tuvalu+688
  • U.S. Virgin Islands+1
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  • Venezuela+58
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