Comparison of Colorectal and Endometrial Microsatellite Instability Tumor Analysis and Premm₅ Risk Assessment for Predicting Pathogenic Germline Variants on Multigene Panel Testing

Abstract

PURPOSE

Tumor testing for microsatellite instability and/or mismatch repair-deficiency (MSI/IHC) and clinical prediction models effectively screen for Lynch syndrome (LS)–associated colorectal cancer (CRC) and endometrial cancer (EC), but they have not been assessed for their ability to identify non-LS forms of inherited risk. The aim of this study was to compare MSI/IHC and the PREMM₅ prediction model to identify carriers of LS and non-LS pathogenic variants (PVs) among patients with CRC and EC.

PATIENTS AND METHODS

Data were retrospectively analyzed from two single-institution cohorts: 706 patients with CRC and/or EC referred for genetic evaluation/testing (high-risk cohort) and 1,058 consecutively ascertained patients with CRC (oncology clinic cohort), unselected for familial risk. All participants underwent germline multigene panel testing. PREMM₅ scores were calculated from personal/family cancer history. The primary outcome was the proportion of individuals with germline PVs (LS PVs, high-penetrance PVs, and any PVs) who had abnormal MSI/IHC testing and/or PREMM₅ score ≥ 2.5%.

RESULTS

MSI/IHC and PREMM₅ had comparable sensitivity for identifying LS carriers in high-risk (89.3% v 85.7%; P = .712) and oncology clinic patients (96.6% v 96.6%; P = 1.000), although MSI/IHC had significantly superior specificity for LS (81.3% v 20.1%; P < .001; 92.3% v 24.3%; P < .001). In both cohorts, PREMM₅ had superior sensitivity to MSI/IHC at identifying patients with any high-penetrance PVs and any low-, moderate-, and high-penetrance PVs. Among patients with normal MSI/IHC, PREMM₅ identified 84.2% and 83.3% of high-risk patients with CRC/EC and oncology clinic CRC patients with high-penetrance PVs, respectively.

CONCLUSION

MSI/IHC and PREMM₅ effectively identify patients with CRC and/or EC with LS, although MSI/IHC has better specificity for LS. Because PREMM₅ identifies non-LS, high-penetrance germline PVs, patients with CRC and/or EC with PREMM₅ score ≥ 2.5%, including those with normal MSI/IHC, should be offered multigene panel testing.

INTRODUCTION

Recent studies of multigene germline testing have demonstrated that 9% to 10% of patients with colorectal (CRC) or endometrial cancer (EC) carry germline pathogenic/likely pathogenic variants (PVs) in cancer susceptibility genes.^1,2 Although Lynch syndrome (LS) is the most common underlying etiology, accounting for 3% to 5% of CRCs and 2% to 6% of ECs, there is a wide diversity of non-LS cancer susceptibility genes that account for other cases.^1-6 LS is caused by germline PVs in DNA mismatch repair (MMR) genes (MLH1, MSH2, MSH6, or PMS2) or EPCAM, and LS-associated CRCs and ECs almost invariably demonstrate defective MMR protein expression by immunohistochemistry (IHC) and high-level microsatellite instability (MSI).^2-4 Therefore, to screen for LS, multiple guidelines recommend MSI/IHC tumor testing for all CRCs and ECs, with subsequent germline LS testing in those with abnormal MSI/IHC results.^7-10

CONTEXT

• Key Objective

• How do microsatellite instability (MSI)/immunohistochemistry (IHC) tumor findings and PROBE.EMPOWER.MANIFEST PREMM₅ compare for use in the identification of Lynch syndrome (LS) and non-LS pathogenic variants (PVs) on multigene panel testing?

• Knowledge Generated

• PREMM₅ and MSI/IHC tumor testing had comparable sensitivity for identifying LS. A PREMM₅ score ≥ 2.5% had 83.7%-92.5% sensitivity for identifying high-penetrance PVs including LS and 76.5% to 89.5% sensitivity for identifying any PVs including LS among those with normal tumor findings.

• Relevance

• Any individual with a PREMM₅ score ≥ 2.5% should be offered multigene panel testing, including those with normal MSI/IHC tumor findings.

Although MSI/IHC tumor testing is the primary means by which LS is identified in routine practice, prediction modeling also has proven efficacy in identifying LS carriers. PREMM₅¹¹ is a clinical prediction model that uses an individual’s age, sex, and personal/family history of cancer to provide a numeric estimate of his or her likelihood of carrying a germline PV in any of the five LS genes.¹² Clinical practice guidelines^7,8,10,13 recommend germline LS testing for any individuals with a predicted ≥ 5.0% probability of LS by PREMM₅, although recent data¹² suggest that use of a ≥ 2.5% PREMM₅ score cutoff has superior clinical benefit because of improved sensitivity, and this is endorsed by some recent guidelines.¹⁴ In addition, PREMM₅ is currently the only LS prediction model that identifies risk for all five LS-associated genes, offering the most comprehensive approach for LS prediction. Because the scores generated by PREMM₅ are agnostic to MSI/IHC results, it is difficult to know how best to synergize the two approaches for identifying LS. In particular, the approach to a patient with CRC/EC who may have a personal/family history concerning for inherited predisposition, but with normal MSI/IHC results, is currently unclear. One hypothesis that motivated our study, particularly relevant in the era of multigene panel testing, is that PREMM₅ may be an effective means of identifying both LS and non-LS forms of inherited cancer risk in those with CRC and/or EC,⁶ whereas MSI/IHC is presumably only effective at identifying LS in such individuals. This hypothesis is based on findings showing the phenotypic overlap between LS carriers and those with other inherited syndromes, such as hereditary breast/ovarian cancer syndrome,^2,15 as well as the diversity of non-LS mutations detected in patients who fulfill LS testing criteria.^6,16 The primary aim of this study was to compare the efficacy of MSI/IHC and PREMM₅ testing at identifying both LS and non-LS germline PVs among individuals with CRC and/or EC. We also compared performance of PREMM₅ for identification of LS and non-LS PVs at the ≥ 2.5% and ≥ 5.0% thresholds.

PATIENTS AND METHODS

Two nonoverlapping cohorts of individuals recruited to study registries from a single institution (Dana-Farber Cancer Institute [DFCI], Boston, MA) were analyzed in this study: a consecutively ascertained cohort of individuals with a prior diagnosis of CRC and/or EC who were referred for genetic counseling/testing for suspected inherited cancer risk from January 2013 to December 2017 (high-risk cohort) and a cohort of consecutively ascertained individuals recruited to an institutional sample registry from December 2008 to March 2014 while undergoing routine oncologic care for a diagnosis of CRC (oncology clinic cohort), regardless of age, MSI/IHC results, family history, or other features of hereditary risk, as previously described.²

For the high-risk cohort, clinical and family history data, including type(s) of cancer, age(s) at diagnosis, and relative(s) affected, were collected from patient self-report during a standard clinical encounter with a certified genetic counselor and systematically recorded in a Progeny database after their clinical visit. Tumor testing data (including MSI/IHC results and somatic BRAF analysis) were obtained from medical record review. Germline multigene panel testing recommendations were made by genetic counselors as part of standard clinical care, and testing was performed at various commercial laboratories (Appendix Table A1, online only).

For the oncology clinic cohort, genetic testing was performed for all patients systematically without selection based on personal/family history. Personal/family history data and MSI/IHC tumor testing data were obtained from medical record review and research-based germline testing with a 25-gene panel developed by Myriad Genetics (Salt Lake City, UT) was performed, as previously described.²

For both cohorts, an individual was considered to have abnormal MSI/IHC results if there was documentation that his or her CRC and/or EC had MSI-high status by polymerase chain reaction or absent expression of MLH1, MSH2, MSH6, and/or PMS2 by IHC; one exception was that individuals whose CRC harbored BRAF p.V600E mutation or whose CRC/EC harbored MLH1 promoter methylation were classified as having normal tumor testing, because such somatic findings are considered to rule out LS, and subsequent germline LS testing is not typically indicated.^10,13 Patients were excluded from the study if they did not have a diagnosis of either CRC or EC, available family history data, or available multigene panel germline testing data.

Individuals with PVs and likely PVs were collectively considered to have PVs. For the high-risk cohort, variant classification was based on the clinical germline testing report issued by the commercial laboratory performing testing. Variant classification for the oncology clinic cohort was performed as previously described.² High-penetrance gene PVs included those in LS-associated genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) as well as PVs in APC (excluding the p.I1307K variant), BMPR1A, BRCA1, BRCA2, CDH1, CDKN2A, biallelic MUTYH, NF1, PALB2, PTEN, and TP53 (Appendix Table A2, online only). The outcome of any PV included high-penetrance gene PVs as well as those in low- or moderate-penetrance cancer susceptibility genes ATM, BARD1, BRIP1, CHEK2, monoallelic MUTYH, NBN, RAD51C, RAD51D, and the APC p.I1307K variant (Appendix Table A2). Definitions of high versus low or moderate penetrance were based on published calculations of lifetime risk for cancer conferred by each gene.^7,13,17-23

A PREMM₅ score was generated for each participant. Participants whose PREMM₅ score was higher than either of two previously validated thresholds (2.5% and 5.0%)^12,24 were categorized as PREMM₅ ≥ 2.5% and PREMM₅ ≥ 5.0%, respectively, and analyses were separately conducted to assess the performance of each of these thresholds.

Each screening test (abnormal MSI/IHC, PREMM₅ ≥ 2.5%, and PREMM₅ ≥ 5.0%) was assessed in terms of its ability to detect individuals with germline PVs in three categories:

1. LS genes

2. Germline PVs in any high-penetrance genes (including LS PVs)

3. Low-, moderate-, and high-penetrance germline PVs in any cancer susceptibility genes.

Results from screening strategies were dichotomized as positive or negative. Basic performance metrics (sensitivity, specificity, and positive and negative predictive values) were calculated, and corresponding 95% CIs were derived for each screening test for each of the three outcomes (germline LS PVs, any high-penetrance PVs, and any PVs). A subgroup analysis was performed in individuals from both cohorts with normal MSI/IHC to evaluate the ability of PREMM₅ to detect individuals harboring any germline high-penetrance PV or any germline PV.

For both cohorts, decision curve analysis was used to assess the net benefit (NB) of different PREMM₅ score thresholds for detecting germline LS PVs, any high-penetrance PVs, and any germline PVs by summing the true positives (TPs; individuals with PREMM₅ scores at/above a given threshold with a germline PV) minus a weighted number w of false positives (FPs; individuals with PREMM₅ scores at/above a given threshold without a germline PV) divided by the sample size n: NB = (TP − w × FP)/n, where the weight factor “w” is defined by a score threshold “p” [w=p/(1-p)]^12,25 The NB of using PREMM₅ to guide germline testing was assessed at a range of 0%-10% score threshold probabilities for identifying participants with each of the three outcomes (germline LS PVs, any high-penetrance PVs, and any PVs) and was compared versus two reference strategies: germline testing of all participants and germline testing of no participants.

A two-sided P value of < .05 was considered statistically significant for all comparisons. All analyses were conducted with R (version 3.6.1; R Foundation for Statistical Computing, Vienna, Austria). This study was reviewed and approved by the Dana-Farber/Harvard Cancer Center Institutional Review Board.

RESULTS

High-Risk Cohort

From January 2013 to December 2017, 706 individuals who had CRC and/or EC (CRC only, n = 475; EC only, n = 247; both CRC and EC, n = 16) and were referred for evaluation to the DFCI cancer genetics clinic were included in the high-risk cohort. Of these, 516 (73.1%) had MSI/IHC results, 117 (22.7%) of which were abnormal. The median PREMM₅ score in the cohort was 4.3% (interquartile range [IQR], 2.6%-7.3%); 299 (42.4%) of 706 and 547 (77.5%) of 706 participants had PREMM₅ scores ≥ 5.0% and ≥ 2.5%, respectively; 33 (4.7%) of 706 participants carried LS PVs, 62 (8.8%) of 706 carried any high-penetrance PVs (including LS), 96 (13.6%) of 706 carried any germline PV, and 610 (86.4%) of 706 did not carry a PV (Table 1; Appendix Table A3, online only).

TABLE 1.

Characteristics of the Study Population

Oncology Clinic Cohort

Of the 1,058 patients with CRC in the oncology clinic cohort, MSI/IHC data were available from 572 tumors (54.1%), of which 70 (12.2%) were abnormal. The median PREMM₅ score in the cohort was 3.3% (IQR, 2.1%-5.7%); 323 (30.5%) of 1,058 and 699 (66.1%) of 1,058 participants had PREMM₅ scores ≥ 5.0% and ≥ 2.5%, respectively; 33 (3.1%) of 1,058 carried LS PVs, 55 (5.2%) of 1,058 carried any high-penetrance PVs (including LS PVs), 105 (9.9%) of 1,058 carried any germline PV, and 953 (90.1%) of 1,058 did not carry a PV (Table 1; Appendix Table A4, online only).

Performance of PREMM₅ and MSI/IHC Tumor Testing

In both cohorts, a PREMM₅ score threshold ≥ 2.5% had higher sensitivity for detecting germline LS PV carriers than a ≥ 5.0% threshold (high-risk cohort, 87.9% v 60.6%; P = .001; oncology clinic cohort, 93.9% v 72.7%; P = .004) but significantly lower specificity (high-risk cohort, 23.0% v 58.5%; P < .001; oncology clinic cohort, 34.8% v 70.8%; P < .001; Table 2; Appendix Tables A5 and A6, online only). In both cohorts, a PREMM₅ ≥ 2.5% score threshold had comparable sensitivity to MSI/IHC testing for detecting LS PV carriers (high-risk cohort, 85.7% v 89.3%; P = .712; oncology clinic cohort, 96.6% v 96.6%; P = 1.000) but significantly lower specificity (high-risk cohort, 20.1% v 81.3%; P < .001; oncology clinic cohort, 24.3% v 92.3%; P < .001; Table 3).

TABLE 2.

PREMM₅ Performance Characteristics for Predicting LS in High-Risk and Oncology Clinic Cohorts

TABLE 3.

Comparison of MSI/IHC Versus PREMM₅ ≥ 2.5% Performance in High-Risk and Oncology Clinic Cohorts

In both cohorts, a PREMM₅ ≥ 2.5% score threshold had significantly superior sensitivity to MSI/IHC tumor testing at identifying individuals with any germline high-penetrance PVs (high-risk cohort, 83.7% v 61.2%; P = .010; oncology clinic cohort, 92.5% v 70.0%; P = .003) and any germline PVs (high-risk cohort, 86.3% v 47.9%; P < .001; oncology clinic cohort, 84.6% v 47.7%; P < .001) but inferior specificity.

Among 399 individuals in the high-risk cohort and 502 in the oncology clinic cohort with confirmed normal MSI/IHC results, a PREMM₅ ≥ 2.5% score threshold had 84.2% and 83.3% sensitivity, respectively, for identifying individuals with any high-penetrance germline PV and 89.5% and 76.5% sensitivity, respectively, for identifying those with any germline PV (Table 4). A vast majority of germline PVs in individuals with normal MSI/IHC and PREMM₅ score ≥ 2.5% occurred in non-LS genes (Fig 1).

TABLE 4.

PREMM₅ ≥ 2.5% Performance in Those With Normal MSI/IHC in High-Risk and Oncology Clinic Cohorts

FIG 1.

Numbers of Lynch syndrome (LS)–associated and non-LS–associated pathogenic variants (PVs) in patients segregated by PREMM₅ score and microsatellite instability (MSI)/immunohistochemistry (IHC) status.

By decision curve analysis, PREMM₅ showed favorable NB for detecting those with any germline high-penetrance PVs at a score threshold ≥ 2.5% for the oncology clinic cohort (a consecutive cohort of individuals with CRC) but not in the high-risk cohort where individuals were referred based on clinical suspicion for inherited cancer risk (Fig 2). PREMM₅ showed favorable NB for detecting individuals with germline LS PVs in both cohorts at a score threshold ≥ 2.5% (Appendix Fig A1, online only). For detecting individuals with any germline PVs (including those with low or moderate penetrance), PREMM₅ had inferior NB to a strategy of germline testing for all participants in both cohorts (Appendix Fig A2, online only).

FIG 2.

Net benefit of PREMM₅ for predicting high-penetrance pathogenic variants in the (A) high-risk cohort (n = 706) and (B) oncology clinic cohort (n = 1,058).

DISCUSSION

In this study of two distinct clinical cohorts of individuals with CRC/EC, we found that MSI/IHC tumor testing and PREMM₅ clinical prediction modeling were effective (high sensitivity and high negative predictive value) at identifying those with underlying germline LS PVs consistent with numerous prior studies and in keeping with professional society practice guidelines.^{3,4,7-10,13,26} However, although MSI/IHC screening was highly specific for underlying LS, PREMM₅ assessment using a score threshold ≥ 2.5% showed considerable efficacy at identifying individuals with both LS and non-LS forms of inherited cancer risk. In particular, PREMM₅ assessment with a ≥ 2.5% score threshold had > 80% sensitivity and > 95% negative predictive value for identifying individuals with germline high-penetrance PVs in individuals in whom MSI/IHC testing was normal. Our results also confirm superior sensitivity of a PREMM₅ threshold ≥ 2.5% compared with ≥ 5.0%; many individuals with high-penetrance PVs would have been missed if a threshold ≥ 5.0% had been used.

High-penetrance PVs identified in individuals with normal tumor MSI/IHC results and a PREMM₅ score ≥ 2.5% included those in APC, BRCA1, BRCA2, CDKN2A, biallelic MUTYH, PALB2, TP53, and other genes, thus encompassing a diverse array of cancer susceptibility genes where there are established surveillance and prevention strategies for carriers and their at-risk family members. Although there is variability in clinical practice, guidance regarding the approach to offering genetic testing when tumor results are normal is lacking, and many individuals with normal MSI/IHC testing likely would not have been referred for germline evaluation. Although PREMM₅ was developed and validated as a clinical prediction model specific to LS,¹² our data demonstrate its ability to identify individuals with inherited cancer risk in a broader fashion and support the notion that all individuals with PREMM₅ scores ≥ 2.5%, including those with normal MSI/IHC, be offered genetic evaluation and germline testing with a multigene panel.

The primary means of risk evaluation for LS has long been through MSI/IHC tumor testing of CRCs and ECs, given that LS-associated cancers almost invariably demonstrate MSI-high status/MMR deficiency by such testing. Individuals with abnormal tumor findings in the absence of LS, BRAF PVs, or MLH1 promoter hypermethylation are most likely explained by double somatic MMR PVs.²⁷ Although universal tumor testing has become the standard of care,^3,4,7-10,26 PREMM₅ and other clinical prediction tools have been well-validated alternatives to MSI/IHC tumor testing for LS screening and have particular value in screening individuals for whom tumor testing is unavailable, including those who have not had a prior cancer.^12,24 With the emergence of next-generation genetic sequencing and the widespread commercial use of multigene panels for inherited cancer risk assessment, however, there is an important need to effectively screen individuals for a wide diversity of cancer predispositions, not just LS. Prior work by our group and others has shown that > 9% of individuals with CRC and EC (including 16% to 24% of those diagnosed before age 50 years) harbor germline PVs in cancer susceptibility genes, including both LS and non-LS PVs; however, the optimal means for identifying those with non-LS forms of risk remains unclear.^1,2,5,28 By demonstrating the ability of PREMM₅ risk assessment to detect germline PVs in both LS- and non-LS–associated high-penetrance cancer susceptibility genes with high sensitivity and high negative predictive value in individuals with CRC and EC, our data in this study fill this critical gap in knowledge.

A number of recent studies have demonstrated a higher-than-expected prevalence of germline high-penetrance cancer susceptibility gene PVs in unselected, consecutively ascertained individuals with a variety of cancer diagnoses beyond CRC and EC, including breast,²⁹ epithelial ovarian,^30,31 exocrine pancreatic,^32-34 metastatic prostate,³⁵ urothelial,^36,37 and biliary tract cancers.³⁸ An approach of universal testing is now endorsed by various professional society guidelines for all individuals diagnosed with breast,³⁹ epithelial ovarian,⁴⁰ exocrine pancreatic,^40,41 or metastatic/high-grade prostate cancer.⁴⁰

Our data demonstrate that for individuals with CRC and EC, there may be an intermediate approach between syndrome-specific evaluation and an approach of germline testing for all. Using a PREMM₅ score ≥ 2.5% to select individuals for germline multigene panel testing had a > 92% sensitivity and > 97% negative predictive value in identifying those with any germline high-penetrance PVs among a consecutively ascertained cohort of patients with CRC (oncology clinic cohort), and decision curve analyses demonstrated this to have favorable NB versus universal germline testing. Among patients with CRC and/or EC referred for genetic evaluation (high-risk cohort), the sensitivity and negative predictive value of PREMM₅ score triaging with a score threshold of ≥ 2.5% were likewise high, particularly among those with normal MSI/IHC results. The NB favored a test-all approach for identifying high-penetrance variants in this cohort.

A key strength of this study is the use of both high-risk individuals referred for germline evaluation in parallel with a distinct nonoverlapping cohort of individuals consecutively ascertained in the setting of a CRC diagnosis, all of whom underwent multigene germline testing and had extensive clinical and family history data available for review.

We recognize that there are important limitations, however, to this study, including that only a subset of participants had available MSI/IHC data, that we did not have a parallel cohort of average-risk patients with EC to complement the oncology clinic cohort of patients with CRC, the single-center design of the study, and that comparing PREMM₅ performance with tumor findings by MSI/IHC by nature makes it impossible to study the unaffected population. We also recognize that PREMM₅ was developed and validated based on its ability to detect individuals with pathogenic germline LS PVs. Although the study data demonstrate the ability of PREMM₅ to have value for multisyndromic clinical prediction using a score cutoff of ≥ 2.5% to guide testing, we would emphasize that there remains a profound need for a clinical prediction model developed and validated specifically with the intent of multisyndromic risk assessment. Lastly, our data demonstrate that the ability of PREMM₅ to detect low- or moderate-penetrance gene PVs is more limited than its ability to identify those with high-penetrance gene PVs (both LS and non-LS).

In conclusion, these data in > 1,700 individuals with CRC and/or EC with prior germline testing confirm the notion that both MSI/IHC and PREMM₅ clinical prediction modeling with a score ≥ 2.5% are highly effective at identifying patients with CRC and/or EC with underlying LS. Notably, especially now that the field of cancer genetics has embraced the routine use of multisyndromic germline risk assessment, we found that a PREMM₅ score ≥ 2.5% should trigger multigene panel testing in individuals with CRC and/or EC, including in those in whom MSI/IHC is normal. These data highlight the fact that inherited susceptibility for CRC and EC extends well beyond LS, such that MSI/IHC is a necessary component of universal LS risk assessment but is insufficient for providing comprehensive genetic risk assessment in such individuals in whom other non-LS forms of inherited susceptibility may be at play. Until a test-all approach becomes recommended for CRC or such critically needed clinical prediction models can be developed and validated for multisyndromic risk assessment inclusive of high-, moderate-, and low-penetrance forms of inherited cancer susceptibility, we would endorse the use of multigene germline testing in all individuals with a PREMM₅ score ≥ 2.5%.

Appendix

FIG A1.

Net benefit of PREMM₅ for predicting Lynch syndrome. Pathogenic variants in the (A) high-risk cohort (n = 706) and (B) oncology clinic cohort (n = 1,058).

FIG A2.

Net benefit of PREMM₅ for predicting any pathogenic variant in the (A) high-risk cohort (n = 706) and (B) oncology clinic cohort (n = 1,058).

TABLE A1.

Types of Multigene Panels Performed in High-Risk Cohort

TABLE A2.

Genes by Outcome and Their Clinical Relevance

TABLE A3.

Prevalence of PVs in High-Risk Cohort

TABLE A4.

Prevalence of PVs in Oncology Clinic Cohort

TABLE A5.

Comparison of MSI/IHC Versus PREMM₅ ≥ 5.0% Performance in High-Risk and Oncology Clinic Cohorts

TABLE A6.

PVs Detected at PREMM₅ ≥ 2.5% Threshold That Would Have Gone Undetected at PREMM₅ ≥ 5.0% Threshold

AUTHOR CONTRIBUTIONS

Conception and design: Alessandro Mannucci, Matthew B. Yurgelun, Sapna Syngal

Financial support: Sapna Syngal

Administrative support: Chinedu Ukaegbu, Sapna Syngal

Collection and assembly of data: Alessandro Mannucci, C. Sloane Furniss, Chinedu Ukaegbu, Miki Horiguchi, Matthew B. Yurgelun

Data analysis and interpretation: All authors

Manuscript writing: All authors

Final approval of manuscript: All authors

Accountable for all aspects of the work: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

Comparison of Colorectal and Endometrial Microsatellite Instability Tumor Analysis and Premm₅ Risk Assessment for Predicting Pathogenic Germline Variants on Multigene Panel Testing

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center.

Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).

Hajime Uno

Consulting or Advisory Role: Roche

Matthew B. Yurgelun

Consulting or Advisory Role: Janssen

Other Relationship: UpToDate

Sapna Syngal

Consulting or Advisory Role: Myriad Genetics, DC Health

Patents, Royalties, Other Intellectual Property: Dana-Farber Cancer Institute has a registered service mark for the PREMM₅ model and holds copyrights for the PREMM questionnaires (Inst); Myriad Genetics (through Dana-Farber Cancer Institute) paid an inventor share of the IP (license issue fee)

Travel, Accommodations, Expenses: Myriad Genetics

No other potential conflicts of interest were reported.