Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta‐analysis

Abstract

Background

Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta‐analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

Methods

We conducted a meta‐analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random‐ or fixed‐effects model. Area under the curve (AUC) and summary receiver‐operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

Results

Our systematic review and meta‐analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713–0.740) and 0.717 (95% CI: 0.703–0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364–0.432) and 2.597 (95% CI: 2.389–2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624–9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post‐test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non‐MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent‐free biophotonic), and nations.

Conclusion

Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

Abstract

Our meta‐analysis showed that saliva might be a promising, efficient, and noninvasive biomarker with the potential to differentiate between patients with and without breast cancer. Subgroup analyses were done to determine sensitivity, specificity, PLR, NLR, and DOR based on the mean age of patients, saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non‐MS measurement methods), sample size, biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent‐free biophotonic), and nations. Unstimulated saliva has a more acceptable diagnostic value compared to stimulated saliva in breast cancer.