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Circulating microRNAs and lipidomic/metabolomic biomarkers show 0.92 SROC AUC for early breast cancer detectionBlood markers show promise for early breast cancer detection

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Key Takeaway
Note that while microRNA and lipidomic biomarkers show high diagnostic accuracy (AUC 0.92), they remain investigational tools.

This systematic review and meta-analysis evaluated the diagnostic accuracy of circulating microRNAs and lipidomic/metabolomic biomarkers as potential indicators for early breast cancer detection. The study included a total population of 6,935 participants, consisting of individuals with confirmed breast cancer cases and corresponding controls. The primary objective was to determine the efficacy of these molecular markers in identifying malignancy at an early stage using serum or plasma samples.

The investigation focused on two main categories of biomarkers: circulating microRNAs and a combination of lipidomic and metabolomic profiles. These were compared against control groups to establish diagnostic metrics. While specific dosing or protocols for biomarker collection are not detailed, the analysis synthesized data from various studies to provide a pooled estimate of diagnostic performance.

The primary results indicated high diagnostic accuracy for these biomarkers. The sensitivity was reported at 0.87 (95% CI [0.83, 0.90]). Specificity was reported at 0.84 (95% CI [0.79, 0.88]). These figures contribute to a diagnostic odds ratio (DOR) of 46.10 (95% CI [27.80, 76.70]). Furthermore, the positive likelihood ratio (PLR) was calculated at 5.17 (95% CI [3.99, 6.68]), while the negative likelihood ratio (NLR) was 0.16 (95% CI [0.13, 0.21]). The SROC area under the curve (AUC) reached 0.92 (95% CI [0.87, 0.94]), suggesting strong discriminative ability.

Safety and tolerability data were not reported for these biomarkers, as they are used for diagnostic purposes rather than therapeutic intervention. However, the clinical utility of these markers is currently limited by several methodological factors. The analysis noted substantial heterogeneity in the results, with I2 values of 88.29% for sensitivity and 90.20% for specificity. Additionally, there were indications of potential small-study effects (p = 0.043). A significant limitation is that most included studies utilized retrospective case-control designs rather than prospective screening cohorts.

When compared to standard clinical practice, these results suggest that while the biomarkers show high statistical accuracy in identifying cancer, they are not yet ready for primary screening. The findings do not replace established imaging modalities like mammography. The high heterogeneity and reliance on retrospective data mean that immediate clinical translation is limited. These markers should be viewed as investigational tools that may eventually serve as complementary diagnostic aids.

Several questions remain regarding the practical application of these biomarkers in a clinical setting. Specifically, it is unclear how well these results translate to diverse populations in prospective trials. The impact of different sample collection methods on the consistency of lipidomic and metabolomic profiles also requires further investigation. Until more prospective data are available, their role remains supportive rather than primary.

How this fits prior evidence

How this fits prior evidence: This finding addresses a gap in non-invasive diagnostic tools for breast cancer. While previous evidence has focused on treatment responses in HER2+ and stage IV cases, as well as management of symptoms like nausea or side effects from surgery, this study focuses specifically on the early detection phase using molecular biomarkers.

A large review of 35 studies involving nearly 7,000 women looked at whether certain substances in the blood could help detect breast cancer early. The substances studied were tiny molecules called microRNAs and other fats and chemicals (lipidomic/metabolomic biomarkers) that can be measured in a blood sample. The goal was to see how well these blood tests could tell apart women who had breast cancer from those who did not.

The results showed that these blood markers performed very well overall. On average, the tests correctly identified 87 out of every 100 women who had breast cancer (sensitivity). They also correctly ruled out breast cancer in 84 out of every 100 women who did not have the disease (specificity). The overall diagnostic accuracy, measured by the area under the curve (AUC), was 0.92, which is considered excellent.

However, the review also found important limitations. There was a lot of variation among the studies, meaning the results were not consistent. For example, the sensitivity varied widely from one study to another. This inconsistency is measured by something called I-squared, which was very high (88% for sensitivity and 90% for specificity). This suggests that the accuracy of these blood tests might depend on many factors, such as the type of breast cancer, the specific markers measured, or the population studied.

Another concern is that most of the studies were done in a way that can overestimate the accuracy of a test. They used a design called retrospective case-control, where researchers look back at stored blood samples from women already known to have cancer or not. This can make a test look better than it would in a real-world screening setting, where the goal is to find cancer in women who have no symptoms.

Because of these limitations, the researchers caution that these blood tests are not ready to replace mammograms for breast cancer screening. They are best seen as investigational tools that might one day be used alongside mammography, especially for women who cannot easily get mammograms or who need additional testing. More research is needed, especially studies that follow women over time (prospective studies) to see how well these tests work in real-world screening programs.

In summary, blood-based biomarkers show promise for detecting breast cancer early, but they are not yet reliable enough for widespread use. The high accuracy seen in studies is encouraging, but the inconsistency and study design issues mean that more work is needed before these tests can be recommended for routine screening.

What this means for you:
Blood tests for breast cancer show high accuracy in studies, but variability and study design issues mean they are not yet ready for routine screening.

Study Details

Study typeMeta analysis
Sample sizen = 6,935
EvidenceLevel 1
PublishedJan 2026
View Original Abstract ↓
BACKGROUND: Breast cancer outcomes improve substantially with earlier detection, yet mammography performance can be limited in dense breasts and may lead to false-positive investigations. Circulating microRNAs (miRNAs) and lipidomic/metabolomic signatures have emerged as promising minimally invasive biomarkers that could complement imaging for early-stage detection. The aim of this systematic review and meta-analysis is to evaluate the diagnostic accuracy of circulating microRNAs and lipidomic/metabolomic biomarkers for early breast cancer detection and to explore between-study heterogeneity. MATERIALS AND METHODS: A PRISMA 2020-compliant systematic review and meta-analysis were conducted. MEDLINE (PubMed), Web of Science, Scopus, Springer, ScienceDirect, and the Cochrane Library were searched for eligible diagnostic studies assessing circulating microRNAs and lipidomic/metabolomic biomarkers measured in serum or plasma. No language restrictions were applied. Non-English reports were screened and, when potentially eligible, translated for full-text assessment and data extraction. Studies using whole blood were excluded. Study quality was assessed using QUADAS-2. Random-effects models (DerSimonian-Laird) pooled sensitivity, specificity, likelihood ratios, diagnostic odds ratio (DOR), and summary ROC (SROC) area under the curve (AUC). Heterogeneity was evaluated using Q and I2 statistics, and small-study effects were assessed using Deeks' test. RESULTS: Thirty-two studies (2015-2025) comprising 6,935 participants (3,697 breast cancer cases; 3,238 controls) were included. Pooled sensitivity was 0.87 (95% CI [0.83, 0.90]) and pooled specificity was 0.84 (95% CI [0.79, 0.88]), with pooled DOR 46.10 (95% CI [27.80, 76.70]), PLR 5.17 (95% CI [3.99, 6.68]), NLR 0.16 (95% CI [0.13, 0.21]), and SROC AUC 0.92 (95% CI [0.87, 0.94]). Heterogeneity was substantial (I2 = 88.29% for sensitivity; I2 = 90.20% for specificity). In subgroup analyses, serum-based studies showed higher pooled specificity than plasma-based studies. A formal threshold effect assessment did not reveal a statistically significant correlation between sensitivity and false-positive rate (Spearman ρ = -0.334, p = 0.062). Deeks' test suggested potential small-study effects (p = 0.043). CONCLUSIONS: Circulating microRNA and lipidomic/metabolomic biomarkers demonstrate strong overall diagnostic performance for breast cancer detection; however, substantial heterogeneity and potential small-study effects limit their immediate clinical translation. Given that most included studies used retrospective case-control designs rather than prospective screening cohorts, these biomarkers are best regarded as investigational, complementary tools rather than replacements for mammography at this stage. Future large, prospective, standardized studies with harmonized pre-analytics and prespecified thresholds are needed to support the implementation of screening or triage pathways.
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