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Mass spectrometry and serum pattern profiling for analyzing the individual risk for endometriosis: promising insights?
Oleh:
Wolfler, Monika M.
;
Schwamborn, Kristina
Jenis:
Article from Journal - ilmiah internasional
Dalam koleksi:
Fertility and Sterility (keterangan: ada di ClinicalKey) vol. 91 no. 06 (Jun. 2009)
,
page 2331-2337 .
Topik:
Endometriosis
;
diagnosis
;
serum
;
protein pattern profiling
;
proteomics
;
SELDI-TOF
;
mass spectrometry
Ketersediaan
Perpustakaan FK
Nomor Panggil:
F02.K.2009.02
Non-tandon:
1 (dapat dipinjam: 0)
Tandon:
tidak ada
Lihat Detail Induk
Isi artikel
Objective To evaluate whether distinct patterns of serum proteins in symptomatic women are of value to predict endometriosis before laparoscopy. Design Prospective exploratory cohort study. Setting Tertiary 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.
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