Mass spectrometry and serum pattern profiling for analyzing the individual risk for endometriosis: promising insights?

article OA: closed CC0 ⤵ 31 in-corpus citations
View on OpenAlex View on PubMed View at publisher
AI-generated summary by gemini-2.5-flash-lite, 2026-06-08

This study explored mass spectrometry and serum pattern profiling to analyze individual risk for endometriosis, offering potentially promising insights into the condition.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

Abstract

ObjectiveTo evaluate whether distinct patterns of serum proteins in symptomatic women are of value to predict endometriosis before laparoscopy.DesignProspective exploratory cohort study.SettingTertiary care center.Patient(s)A total of 91 consecutive symptomatic patients suffering from dysmenorrhea, dyspareunia, chronic pelvic pain, or unexplained infertility.Intervention(s)Collection of serum samples and a standardized protocol for patients' history before laparoscopic diagnosis.Main outcome measure(s)Protein expression was analyzed by mass spectrometric analysis according to surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) standards. The analysis of data was performed using a genetic algorithm (ClinProTools 2.0 software) and a rule-based decision-tree algorithm (XLminer software).Result(s)A total of 90 out of 91 samples were eligible for analysis. At laparoscopy, 51 of 90 patients (56.7%) exhibited endometriosis and 39 of 90 (43.3%) were disease free. Analyzing the serum samples, the software revealed a unique selection of mass peaks between 2,000 and 20,000 Da, which allowed for discrimination between patients suffering from endometriosis and control subjects. Overall recognition capacity was 70.8%, exhibiting a sensitivity of 81.3% (95% confidence interval [CI] 66.5-92.5) and a specificity of 60.3% (95% CI 46.1-74.2]) using the genetic algorithm, and a sensitivity of 78.4% and a specificity of 59.0% using the rule-based decision-tree algorithm.Conclusion(s)These findings provide direct evidence that screening for serum protein patterns using SELDI-TOF MS before laparoscopy might be of discriminative value in the prediction of disease and partly confirms recently published data. However, in this prospective setting, we found both low sensitivity and low specificity, which disqualifies the screening for serum protein patterns by SELDI-TOF MS as a "quick fix" diagnostic test.

My notes (saved in your browser only)

Condition tags

endometriosis

MeSH descriptors

Blood Proteins Endometriosis Endometriosis Mass Spectrometry Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Adult Blood Proteins Endometriosis Endometriosis Female Humans Intestines Intestines Laparoscopy Mass Spectrometry Middle Aged Ovary Ovary Patient Selection Peritoneal Cavity

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (33)

Cited by (31)

Source provenance

europepmc
last seen: 2026-08-24T06:08:07.662257+00:00
openalex
last seen: 2026-06-10T17:14:06.276822+00:00
pubmed
last seen: 2026-05-13T22:14:30.652814+00:00
License: CC0 · commercial use OK