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Comparison of Precision Oncology Annotation Services in the National Precision Oncology Program
BACKGROUND
The National Precision Oncology Program (NPOP) provides comprehensive genomic profiling (CGP) through external vendors to patients within the Veterans Affairs Healthcare System who meet testing guidelines. We sought to assess the concordance of cancer therapy recommendations between Foundation Medicine (FM), one of the NPOP vendors, and OncoKB, an FDA-recognized public precision oncology knowledge database, which annotates human genetic variants associated with therapies guidance at varying levels of evidence.
METHODS
We selected FM CGP test reports with at least one therapy recommendation regardless of FDA approval or level of evidence were selected to compare FM and OncoKB therapy annotations of different mutation types, including short variants (SVs), rearrangements, and copy number alterations (CNAs) between 02/01/2019-03/13/2023. Therapy recommendations of annotations for unique combinations of gene, variant, and cancer type from FM and OncoKB were compared. Comparisons were scored as an Exact Match (EM) if FM and OncoKB therapy annotation was the same or a Partial Match (PM) if the FM therapy annotation was a subset of OncoKB’s or vice versa.
RESULTS
For annotations involving FDA-approved therapies, a total of 10,435 cases were compared for SVs, 546 for rearrangements, and 732 for CNAs. Among SVs annotations, 7,029 (67.4%) were EM and 787 (7.5%) were PM. Of rearrangement annotations, 328 (60.1%) were EM and 95 (17.4%) were PM. Of CNA annotations, 469 (64.1%) were EM and 28 (3.8%) were PM. For off-label therapies, agreement between annotation sources was much lower in all above scenarios. Examples included 3022 (29%) cases were identified as EM plus PM for SVs, 324 (59.3%) for rearrangements, and 42 (5.7%) for CNAs.
CONCLUSIONS
Therapy recommendations were inconsistent between FM and OncoKB annotation services, with a substantial disagreement among both FDA-approved and off-label therapy annotations. The limitation of time difference of annotations performed between FM and OncoKB therapy annotations accounted for some disagreement. Establishing accuracy and improving concordance between different annotation services is needed to better match treatments to patients and improve provider trust and reliability of annotation service.
BACKGROUND
The National Precision Oncology Program (NPOP) provides comprehensive genomic profiling (CGP) through external vendors to patients within the Veterans Affairs Healthcare System who meet testing guidelines. We sought to assess the concordance of cancer therapy recommendations between Foundation Medicine (FM), one of the NPOP vendors, and OncoKB, an FDA-recognized public precision oncology knowledge database, which annotates human genetic variants associated with therapies guidance at varying levels of evidence.
METHODS
We selected FM CGP test reports with at least one therapy recommendation regardless of FDA approval or level of evidence were selected to compare FM and OncoKB therapy annotations of different mutation types, including short variants (SVs), rearrangements, and copy number alterations (CNAs) between 02/01/2019-03/13/2023. Therapy recommendations of annotations for unique combinations of gene, variant, and cancer type from FM and OncoKB were compared. Comparisons were scored as an Exact Match (EM) if FM and OncoKB therapy annotation was the same or a Partial Match (PM) if the FM therapy annotation was a subset of OncoKB’s or vice versa.
RESULTS
For annotations involving FDA-approved therapies, a total of 10,435 cases were compared for SVs, 546 for rearrangements, and 732 for CNAs. Among SVs annotations, 7,029 (67.4%) were EM and 787 (7.5%) were PM. Of rearrangement annotations, 328 (60.1%) were EM and 95 (17.4%) were PM. Of CNA annotations, 469 (64.1%) were EM and 28 (3.8%) were PM. For off-label therapies, agreement between annotation sources was much lower in all above scenarios. Examples included 3022 (29%) cases were identified as EM plus PM for SVs, 324 (59.3%) for rearrangements, and 42 (5.7%) for CNAs.
CONCLUSIONS
Therapy recommendations were inconsistent between FM and OncoKB annotation services, with a substantial disagreement among both FDA-approved and off-label therapy annotations. The limitation of time difference of annotations performed between FM and OncoKB therapy annotations accounted for some disagreement. Establishing accuracy and improving concordance between different annotation services is needed to better match treatments to patients and improve provider trust and reliability of annotation service.
BACKGROUND
The National Precision Oncology Program (NPOP) provides comprehensive genomic profiling (CGP) through external vendors to patients within the Veterans Affairs Healthcare System who meet testing guidelines. We sought to assess the concordance of cancer therapy recommendations between Foundation Medicine (FM), one of the NPOP vendors, and OncoKB, an FDA-recognized public precision oncology knowledge database, which annotates human genetic variants associated with therapies guidance at varying levels of evidence.
METHODS
We selected FM CGP test reports with at least one therapy recommendation regardless of FDA approval or level of evidence were selected to compare FM and OncoKB therapy annotations of different mutation types, including short variants (SVs), rearrangements, and copy number alterations (CNAs) between 02/01/2019-03/13/2023. Therapy recommendations of annotations for unique combinations of gene, variant, and cancer type from FM and OncoKB were compared. Comparisons were scored as an Exact Match (EM) if FM and OncoKB therapy annotation was the same or a Partial Match (PM) if the FM therapy annotation was a subset of OncoKB’s or vice versa.
RESULTS
For annotations involving FDA-approved therapies, a total of 10,435 cases were compared for SVs, 546 for rearrangements, and 732 for CNAs. Among SVs annotations, 7,029 (67.4%) were EM and 787 (7.5%) were PM. Of rearrangement annotations, 328 (60.1%) were EM and 95 (17.4%) were PM. Of CNA annotations, 469 (64.1%) were EM and 28 (3.8%) were PM. For off-label therapies, agreement between annotation sources was much lower in all above scenarios. Examples included 3022 (29%) cases were identified as EM plus PM for SVs, 324 (59.3%) for rearrangements, and 42 (5.7%) for CNAs.
CONCLUSIONS
Therapy recommendations were inconsistent between FM and OncoKB annotation services, with a substantial disagreement among both FDA-approved and off-label therapy annotations. The limitation of time difference of annotations performed between FM and OncoKB therapy annotations accounted for some disagreement. Establishing accuracy and improving concordance between different annotation services is needed to better match treatments to patients and improve provider trust and reliability of annotation service.