Cancer Genomics Testing: diagnostic yield and reimbursement

Cancer Genomics Testing: diagnostic yield and reimbursement Anthony N. Sireci, MD, MS Assistant Professor of Pathology and Cell Biology Columbia University Medical Center Assistant Director and Physician Manager Laboratory of Personalized Genomic Medicine

Outline Review of cancer genomics test menu and requirements for complex workflow Analysis of utilization of genomics testing over time at CUMC Overview of diagnostic yield for comprehensive cancer panel Reimbursement experience Future directions

Executive Summary The introduction and deployment of NGS-based genomics testing in oncology requires building a complex, inter-departmentally aligned ecosystem that is distinct from more routine laboratory testing Oncologists and patients alike are driving the increased utilization of genomic oncology testing at rates which exceed the growth of more standard molecular oncology diagnostics Our experience at CUMC shows that large cancer panels and whole exome testing identify targetable/actionable/impactful mutations at a high rate and at least suggest clinical effectiveness of this testing Reimbursement from third party payers does not meet costs for the majority of genomics testing and is trending downward on a month by month basis. Poor reimbursement is mainly driven, in cancer panels, by Medicare and a select private payer Our team is working on a variety of mechanisms to increase oncologist involvement in appropriate test utilization as well as working with oncologists to establish convincing costeffectiveness models

Outline Review of Cancer genomics test menu and requirements for complex workflow Analysis of utilization of genomics testing over time at CUMC Overview of diagnostic yield for comprehensive cancer panel Reimbursement experience Future directions

We have developed and validated a tiered approach to NGS oncology testing at CUMC and have provided this testing since July, 2014 48 genes commonly associated with cancer Histologyspecific panels TruSeq Cancer Panel Columbia Combined Cancer Panel (CCCP) 467 cancer-related genes selected by CUMC oncologists 393 exon-only genes and 74 select whole genes (FM: 236 exons; 19 rearrangements) Micro-dissection to enrich for tumor content; lower requirements than FM Cancer Whole Exome with Transcriptome (cwes) Tumor exome, germline exome, and transcriptome Provides information on: cancer predispositions somatic mutations copy number changes translocations expression data

Clinical traige Of variants Data DNA Cancer genomics testing requires establishing a workflow which goes beyond the traditional focus of the molecular pathology laboratory Assesses tumor cellularity Micro/macrodissection Microdissection Macrodissection DNA extraction Molecular accessioning H&E Molecular Pathologist NGS Feedback Internal consensus Clinical Report Bioinformatics LIS Report EHR

Clinical traige Of variants Data DNA Even within the more traditional workflows, there are unique challenges when deploying cancer genomics testing Assesses tumor cellularity Micro/macrodissection Microdissection Macrodissection DNA extraction Molecular accessioning H&E Molecular Pathologist NGS Feedback Internal consensus Clinical Report Bioinformatics LIS Report EHR

CPT codes Submit CPT Codes for preauth diagnosis Patient/test information Clinical traige Of variants Data tissue DNA However, cancer genomics testing requires establishing a workflow to integrate oncologists, anatomic pathologists, the EMR, the molecular lab and third party payers Rad/onc Patient with possible cancer Surgery Assesses tumor cellularity Micro/macrodissection Microdissection Macrodissection DNA extraction Pathology Assess adequacy Choose block H&E and blanks Molecular accessioning H&E Molecular Pathologist NGS Oncologist Cancer Panel order Preauth granted Billing Preauth Feedback Internal consensus Clinical Report Bioinformatics Preauth decision LIS 3 rd party payer Report Billing system EHR Molecular Pathology Report

CPT codes Submit CPT Codes for preauth diagnosis Patient/test information Clinical traige Of variants Data tissue DNA Cancer genomics testing requires establishing a workflow to integrate oncologists, anatomic pathologists, EMR, the molecular lab and third party payers refocus! Rad/onc Patient with possible cancer Surgery Assesses tumor cellularity Micro/macrodissection Microdissection Macrodissection DNA extraction Pathology Assess adequacy Choose block H&E and blanks Molecular accessioning H&E Molecular Pathologist NGS Oncologist Cancer Panel order Preauth granted Billing Preauth Feedback Internal consensus Clinical Report Bioinformatics Preauth decision LIS 3 rd party payer Report Billing system EHR Molecular Pathology Report

CPT codes Submit CPT Codes for preauth diagnosis Patient/test information Clinical traige Of variants Data tissue DNA Cancer genomics testing requires establishing a workflow to integrate oncologists, anatomic pathologists, the molecular lab and third party payers accounting for reflex Rad/onc Patient with possible cancer Surgery Assesses tumor cellularity Micro/macrodissection Microdissection Macrodissection DNA extraction Pathology Assess adequacy Choose block H&E and blanks Molecular accessioning H&E Molecular Pathologist NGS Oncologist Cancer Panel order Preauth granted Billing Preauth Feedback Internal consensus Clinical Report Bioinformatics Preauth decision LIS 3 rd party payer Report Billing system EHR Molecular Pathology Report

CPT codes diagnosis Clinical traige Of variants Data tissue DNA Cancer genomics testing requires establishing a workflow to integrate oncologists, anatomic pathologists, the molecular lab and third party payers accounting for reflex Rad/onc Patient with possible cancer Surgery Assesses tumor cellularity Micro/macrodissection Microdissection Macrodissection DNA extraction Pathology Assess adequacy Choose block H&E and blanks Molecular accessioning H&E Molecular Pathologist NGS Feedback Bioinformatics Oncologist Internal consensus Clinical Report LIS 3 rd party payer Report Billing system EHR Molecular Pathology Report

Specimen count There has been a 8% (range: 4-13%) month over month increase in the utilization of histology-specific targeted cancer panels at CUMC 40 Utilization of histology-specific cancer panels (Jan 2015-Jul 2016) 35 30 LUNG PANEL COLORECTAL PANEL MELANOMA PANEL TSEQ PANEL 25 20 15 10 5 0

Specimen count There has been a 10.4% and 2% month over month increase in the utilization of comprehensive panels and cwes, respectively at CUMC 60 Utilization of large cancer panels and whole exome/transcriptome (Jan 2015- July 2016) 50 40 30 CCCP cwes 20 10 0

Specimen count This trend in increased utilization has not been seen in a more standard molecular assay testing TCR clonality 80 Utilization: TCR assay (Jan 2015-July 2016 ) 70 60 50 40 30 20 10 0

Ordering practices differ by test ordered with Lung and Colorectal panels being ordered mostly on inpatients 70% Cases ordered on inpatients % of total 60% 50% 40% 30% 20% 10% 0% CCCP LUNG PANEL COLORECTAL PANEL MELANOMA PANEL TRUSEQ

Outline Review of cancer genomics test menu and requirement for complex workflow Analysis of utilization of genomics testing over time at CUMC Overview of diagnostic yield for comprehensive cancer panel Reimbursement experience Future directions

We are able to successfully sequence the majority of specimen submitted to the laboratory including biopsies and FNA samples Sireci et. al. Data in submission for publication

Sireci et. al. Data in submission for publication

Our large cancer panel has a diagnostic hit rate of ~50% and is particularly effective for certain cancers Sireci et. al. Data in submission for publication

Our large cancer panel has a diagnostic hit rate of ~50% of cases and is particularly effective for certain cancers Sireci et. al. Data in submission for publication

Outline Cancer genomics test menu and requirement for complex workflow Analysis of utilization of genomics testing over time at CUMC Overview of diagnostic yield for comprehensive cancer panel Reimbursement experience Future directions

% of costs reimbursed While the lung panel is reimbursed at a breakeven value, the remainder of our cancer genomics assays are performed at a loss/sample 120% Average reimbursement of cancer genomics testing % of estimated cost (Jan 2015-July 2016) 100% 80% 60% 40% 20% 0% cwes CCCP Lung Panel Colorectal Panel Melanoma Panel TruSeq

We observe similar trends in reimbursement over time for histology-specific subpanels for lung and colorectal cancers, each decreasing 4% and 5% respectively monthly Reimbursement Reimbursement over time for the most commonly ordered subpanels Lung Colorectal

Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15 Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 Tests ordered per month Reimbursement Analysis of reimbursement over time for 81455 shows a month over month decrease in payments while utilization by oncologists is increasing Utilization for 81455 over time Average reimbursement for 81455 over time

Reimbursement for cwes has seen a modest month over month increase of 2% since January 2015 and might be the consequence of a unique payer mix in Pediatrics Total reimbursed per case Reimbursement over time for cwes

% of costs reimbursed A deeper dive into reimbursement for our comprehensive cancer panel coded under 81455 during 2015 reveals causes of low reimbursement including payer mix, ICD10 codes used and payer classification of genomics testing as non-clinical 120% Average reimbursement of cancer genomics testing % of estimated cost 100% 80% 60% 40% 20% 0% cwes CCCP Lung Panel Colorectal Panel Melanoma Panel TruSeq

A deeper dive into reimbursement for large panel testing (>51 genes) in 2015 shows low reimbursement relative to EGFR CPT code driven mainly by 0% payment by Medicare Distribution of payers for CCCP cases (n=153) Reimbursement by payer for 81455 18% Commercial Government Managed Gov't 40% 35% 30% 30% 52% Average reimbursement as a percent off charges for 81455 25% 20% 15% 10% Mean=19.4% Commercial Government Managed Gov't 5% 0% Commercial Government Managed Gov't Distribution of payers for EGFR cases (n=231) Reimbursement by payer for 81235 50% 21% 42% 37% Commercial Government Managed Gov't Average reimbursement as a percent off charges for 81235 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Mean=36.8% Commercial Government Managed Gov't Commercial Government Managed Gov't Sireci et. al. Data in submission for publication

Insurers appear to be more likely to pay for comprehensive sequencing for certain tumor types over others, but this analysis is complicated by differences in payer mix Average reimbursement by histology Payer mix by organ system involved Average reimbursement as a percent of charges for 81055 35% 30% 25% 20% 15% 10% 5% 0% Mean=20.4% Liver GU Bone and soft tissue CUP Breast Gyn GI Colon Pancreas Lung Other Melanoma CNS Heme commercial Government Managed Gov't Other 0 5 10 15 20 25 Sireci et. al. Data in submission for publication

Despite an 82% approval of preauthorization for 81455, we maintain a high denial rate for this code relative to more standard codes Payment and denial rates CCCP (81455) 100% n=153 80% 45% Denied 60% Reimbursed Summary of major of denial reasons CCCP (81455) 100% 80% 60% 5% 13% Noncovered service No authorization Clinical notes required 40% 20% 55% 40% 20% 82% 0% Cases with available reimbursement data 0% Denied cases Payment and denial rates EGFR (81235) 100% 80% 60% 40% 20% 0% n=231 86% 14% Cases with available reimbursement data Denied Reimbursed Summary of major of denial reasons EGFR (81235) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 16% 34% 50% Denied cases Noncovered service Clincial notes required Other Sireci et. al. Data in submission for publication

Future Directions Studies evaluating the cost and cost-effectiveness of cancer whole exomes in pediatrics and cancer panel testing compared to standard diagnostics in progress Working with third party payers to establish more favorable reimbursement policies for this testing in progress Developing clinical utilization strategies and protocols to focus this costly testing on the correct patient population in progress Establishing a streamlined workflow for involvement of CGC members to add to LCD responses from AMP/CAP plea Publication of collective reimbursement experience by CGC members recent idea (like, last night)

Acknowledgments Administrators Melissa Carter Kris Smith Joann Li Medical Directors Mahesh Mansukhani Brynn Levy Susan Hsiao Vimla Aggarwal Andrew Turk Tatyana Gindin Clinicians Andrew Kung Rich Carvajal Julia Glade Bender Jennifer Oberg Technical Staff Vaishali Hodel Odelia Nahum