Abstract

Background: Gene panels are routinely used to assess predisposition to hereditary cancers by simultaneously testing multiple susceptibility genes and/or variants. More recently, genetic panels have been implemented as part of solid tumor malignancy testing assessing somatic alterations. One example is targeted variant panels for thyroid nodules that are not conclusively malignant or benign upon fine-needle aspiration (FNA). We systematically reviewed published studies from 2009 to 2018 that contained genetic data from preoperative FNA specimens on cytologically indeterminate thyroid nodules (ITNs) that subsequently underwent surgical resection. Pooled prevalence estimates per gene and variant, along with their respective positive predictive values (PPVs) for malignancy, were calculated.Summary: Our systematic search identified 540 studies that were supplemented by 18 studies from bibliographies or personal files. Sixty-one studies met all inclusion criteria and included >4600 ITNs. Overall, 26% of nodules contained at least 1 variant or fusion. However, half of them did not include details on the specific gene, variant, and/or complete fusion pair reported for inclusion toward PPV calculations. The PPVs of genomic alterations reported at least 10 times were limited to BRAFV600E (98%, 95% confidence interval [CI 96–99%]), PAX8/PPARG (55% [CI 34–78%]), HRASQ61R (45% [CI 22–72%]), BRAFK601E (42% [CI 19–68%]), and NRASQ61R (38% [CI 23–55%]). Excluding BRAFV600E, the pooled PPV for all other specified variants and fusions was 47%. Multiple variants within the same nodule were identified in ∼1% of ITN and carried a cumulative PPV of 77%.Conclusions: The chance that a genomic alteration predicts malignancy depends on the individual variant or fusion detected. Only five alterations were reported at least 10 times; BRAFV600E had a PPV of 98%, while the remaining four had individual PPVs ranging from 38% to 55%. The small sample size of most variants and fusion pairs found among ITNs, however, limits confidence in their individual PPV point estimates. Better specific reporting of genomic alterations with cytological category, histological subtype, and cancer staging would facilitate better understanding of cancer prediction, and the independent contribution of the genomic profile to prognosis.

Highlights

  • The prediction of malignancy in thyroid nodules continues to evolve

  • We examined the available published data on individual gene variants and fusions in preoperative cytologically indeterminate thyroid fine-needle aspiration (FNA) samples from cohorts representative of routine clinical practice to determine their predictive values for thyroid malignancy

  • We evaluated the incidence and positive predictive values (PPVs) of genetic variants and fusions on preoperative clinical specimens from >4600 thyroid nodules with indeterminate cytology from 61 publications

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Summary

Introduction

The prediction of malignancy in thyroid nodules continues to evolve. Sonographic characteristics of thyroid nodules alone are not sufficient to predict the risk of malignancy for many nodules [1,2]. One example is targeted variant panels for thyroid nodules that are not conclusively malignant or benign upon fine-needle aspiration (FNA). We systematically reviewed published studies from 2009 to 2018 that contained genetic data from preoperative FNA specimens on cytologically indeterminate thyroid nodules (ITNs) that subsequently underwent surgical resection. Sixty-one studies met all inclusion criteria and included >4600 ITNs. Overall, 26% of nodules contained at least 1 variant or fusion. Half of them did not include details on the specific gene, variant, and/or complete fusion pair reported for inclusion toward PPV calculations. Conclusions: The chance that a genomic alteration predicts malignancy depends on the individual variant or fusion detected. The small sample size of most variants and fusion pairs found among ITNs, limits confidence in their individual PPV point estimates. Better specific reporting of genomic alterations with cytological category, histological subtype, and cancer staging would facilitate better understanding of cancer prediction, and the independent contribution of the genomic profile to prognosis

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