Advocating for equitable management of hereditary cancer syndromes

Enhanced family history-based algorithms increase the identification of individuals meeting criteria for genetic testing of hereditary cancer syndromes but would not reduce disparities on their own

OBJECTIVE

This study aimed to 1) investigate algorithm enhancements for identifying patients eligible for genetic testing of hereditary cancer syndromes using family history data from electronic health records (EHRs); and 2) assess their impact on relative differences across sex, race, ethnicity, and language preference.

MATERIALS AND METHODS

The study used EHR data from a tertiary academic medical center. A baseline rule-base algorithm, relying on structured family history data (structured data; SD), was enhanced using a natural language processing (NLP) component and a relaxed criteria algorithm (partial match [PM]). The identification rates and differences were analyzed considering sex, race, ethnicity, and language preference.

RESULTS

Among 120,007 patients aged 25-60, detection rate differences were found across all groups using the SD (all P < 0.001). Both enhancements increased identification rates; NLP led to a 1.9 % increase and the relaxed criteria algorithm (PM) led to an 18.5 % increase (both P < 0.001). Combining SD with NLP and PM yielded a 20.4 % increase (P < 0.001). Similar increases were observed within subgroups. Relative differences persisted across most categories for the enhanced algorithms, with disproportionately higher identification of patients who are White, Female, non-Hispanic, and whose preferred language is English.

CONCLUSION

Algorithm enhancements increased identification rates for patients eligible for genetic testing of hereditary cancer syndromes, regardless of sex, race, ethnicity, and language preference. However, differences in identification rates persisted, emphasizing the need for additional strategies to reduce disparities such as addressing underlying biases in EHR family health information and selectively applying algorithm enhancements for disadvantaged populations. Systematic assessment of differences in algorithm performance across population subgroups should be incorporated into algorithm development processes.

What can we learn from more than 1,000 Brazilian patients at risk of hereditary cancer?

Background

Identifying individuals at a higher risk of developing cancer is a major concern for healthcare providers. Cancer predisposition syndromes are the underlying cause of cancer aggregation and young-onset tumors in many families. Germline genetic testing is underused due to lack of access, but Brazilian germline data associated with cancer predisposition syndromes are needed.

Methods

Medical records of patients referred for genetic counseling at the Oncogenetics Department at the Hospital Sírio-Libanês (Brasília, DF, Brazil) from July 2017 to January 2021 were reviewed. The clinical features and germline findings were described. Detection rates of germline pathogenic/likely pathogenic variant (P/LPV) carriers were compared between international and Brazilian guidelines for genetic testing.

Results

A total of 1,091 individuals from 985 families were included in this study. Most patients (93.5%) had a family history of cancer, including 64% with a family member under 50 with cancer. Sixty-six percent of patients (720/1091) had a personal history of cancer. Young-onset cancers (&lt;50 years old) represented 62% of the patients affected by cancer and 17% had multiple primary cancers. The cohort included patients with 30 different cancer types. Breast cancer was the most prevalent type of cancer (52.6%). Germline testing included multigene panel (89.3%) and family variant testing (8.9%). Approximately 27% (236/879) of the tested patients harbored germline P/LPVs in cancer susceptibility genes. BRCA2, BRCA1, and TP53 were the most frequently reported genes, corresponding to 18.6%, 14.4%, and 13.5% of the positive results, respectively. Genetic testing criteria from international guidelines were more effective in identifying carriers than the Brazilian National Agency of Supplementary Health (ANS) criteria (92% vs. 72%, p&lt;0.001). Forty-six percent of the cancer-unaffected patients who harbored a germline P/LPV (45/98) would not be eligible for genetic testing according to ANS because they did not have a family variant previously identified in a cancer-affected relative.

Conclusion

The high detection rate of P/LPVs in the present study is possibly related to the genetic testing approach with multigene panels and cohort’s characteristics, represented mainly by individuals with a personal or family history of young-onset cancer. Testing asymptomatic individuals with suspicious family history may also have contributed to a higher detection rate. A significant number of carriers would not have been identified using ANS criteria for genetic testing.