| Literature DB >> 28547097 |
Eric Surrey1, Cathryn M Carter2, Ahmed M Soliman3, Shahnaz Khan4, Dana B DiBenedetti4, Michael C Snabes3.
Abstract
PURPOSE: The objective of this review was to evaluate existing patient-completed screening questionnaires and/or symptom-based predictive models with respect to their potential for use as screening tools for endometriosis in adult women. Validated instruments were of particular interest.Entities:
Keywords: Endometriosis; Patient-reported; Screener; Self-administered; Symptoms
Mesh:
Year: 2017 PMID: 28547097 PMCID: PMC5509779 DOI: 10.1007/s00404-017-4406-9
Source DB: PubMed Journal: Arch Gynecol Obstet ISSN: 0932-0067 Impact factor: 2.344
Final PubMed search strategy, conducted April 5, 2016 (limits: humans; no comments or editorials)
| Search number | Search terms | Number of results |
|---|---|---|
| Disease terms | ||
| 1 | “Endometriosis”[Majr] OR endometriosis[Title] OR endometrioses[Title] OR endometrioma[Title] OR endometriomas[Title] OR endometrial lesion*[Title] Limits: English | 13,101 |
| Screening instruments | ||
| 2 | #1 AND (“Early Diagnosis”[Mesh] OR “Symptom Assessment”[Mesh] OR “Surveys and Questionnaires”[Majr] OR “Physical Examination”[Majr] OR “Medical History Taking”[Mesh] OR “Logistic Models”[Majr] OR “ROC Curve”[Majr] OR “Models, Theoretical”[Majr] OR “medical history”[Title] OR predict*[Title] OR interview*[Title] OR screen*[Title] OR questionnaire[Title] OR surve*[Title] OR model*[Title] OR measur*[Title] OR validat*[Title] OR (pain[Title] AND symptom*[Title]) OR patient report*[Title] OR “self check”[Title] OR diagnostic[Title] OR sensitivity[Title] OR “area under curve”[Text Word] OR “symptoms constellation”[Text Word] OR “predictive ability”[Title] OR empirical[Title] OR “non surgical”[Title] OR “differential diagnosis”[Title]) Limits: English | 881 |
| Exclusions | ||
| #3 | “Animals”[Mesh] NOT “Humans”[Mesh] Limits: English | 3,745,995 |
| #4 | “Comment”[Publication Type] OR “Editorial”[Publication Type] Limits: English | 862,127 |
| #5 | “Endometriosis/drug therapy”[Mesh] | 1888 |
| #6 | #2 NOT (#3 OR #4 OR #5) | 611 |
PICOS inclusion and exclusion criteria
| Criteria | Included | Excluded |
|---|---|---|
| Population | Studies in women with symptoms consistent with endometriosis | Studies involving only surgical, imaging, or biomarker diagnosis of endometriosis |
| Interventions and comparators | No specific drug interventions or comparators were the focus of this review | Studies examining drug interventions in women with a diagnosis of endometriosis |
| Outcomes | Symptom-based patient-completed endometriosis screening instruments (questionnaires and/or predictive models) | Instruments other than symptom-based, patient-completed endometriosis screening questionnaires (e.g., EPBD, ESD, B&B) and/or predictive models |
| Study design | Studies of any design that evaluated patient-reported screening of endometriosis | Commentaries and editorials |
B&B Biberoglu and Behrman, EPBD Endometriosis Pain and Bleeding Diary, ESD Endometriosis Symptom Diary, PICOS population, intervention, comparison, outcomes, study design
Fig. 1Literature search results. ACOG, American Congress of Obstetricians and Gynecologists; ASRM, American Society for Reproductive Medicine; JEPPD/J Endo, Journal of Endometriosis and Pelvic Pain Disorders; SRI, Society for Reproductive Investigation; WCE, World Congress of Endometriosis
Characteristics of identified studies and measures
| References | Population and country | Type of tool | Brief description | Clinical utility | Assessment of performance and validation |
|---|---|---|---|---|---|
| Endometriosis studies | |||||
| Forman et al. [ |
| Patient-completed questionnaire | Differentiation of subfertile women with a healthy pelvis vs. endometriosis via patients’ responses to a 7-point physical symptom and medical history questionnaire | Questionnaire did not distinguish patients with minimal endometriosis from patients with a normal pelvis | Performance and validation not reported |
| Fasciani et al. [ |
| Endometriosis Index based on patient pain evaluation, physician consultation, and diagnostic evidence | Predictors of endometriosis in women with chronic pelvic pain, infertility, or clinically suspected endometriosis based on 38 variables and parameters | Potentially useful as a noninvasive screening tool to detect endometriosis and differentiate between disease severities, but not feasible as a patient-completed measure | Score > 28 test was predictive of deep-infiltrating endometriosis with 72.4% sensitivity and 90.1% specificity |
| Yeung et al. [ |
| Predictive mathematical model for early stage endometriosis | Physical and demographic characteristics, medical and family history, symptoms, and quality of life were collected via a preoperative questionnaire | Allows for an individual probability of early stage disease to be calculated for each patient, but not feasible as a patient-completed measure | Excellent discriminatory ability (AUC = 0.822, |
| Eskenazi et al. [ |
| Patient interviews and noninvasive diagnostic procedures | Prediction and validation of surgical diagnosis using symptoms in a sample who participated in structured 1-h interviews regarding infertility, dysmenorrhea, dyspareunia, and noncyclic pelvic pain; patients had pelvic examination and transvaginal ultrasound prior to surgery | Positive ultrasound was 100% successful in diagnosing ovarian endometriosis but failed to diagnose nonovarian endometriosis | The presence of any symptom correctly classified 66% of diagnoses |
| Calhaz-Jorge et al. [ |
| Predictive mathematical model | Predictors of endometriosis in subfertile women scheduled for laparoscopy using logistic regression to evaluate whether medical history could predict the presence of endometriosis | Presence of endometriosis (all stages and severe) could be predicted from the medical history, particularly primary subfertility, dysmenorrhea, chronic pelvic pain, ever used oral contraception, and obesity (inverse relationship) | Multivariate prediction model had an area under the ROC curve of 0.71 for all endometriosis and 0.74 for grade III/IV endometriosis |
| Ballard et al. [ |
| Patient-completed questionnaire | Investigation of whether different dimensions of chronic pelvic pain are useful in the diagnosis of endometriosis | Throbbing pain and dyschezia could be useful for differentiating between women with endometriosis and women without endometriosis | Performance not reported |
| Hackethal et al. [ |
| Patient-completed questionnaire | Prospective, preoperative, structured 34-item questionnaire regarding history of endometriosis, surgical history, allergies and other illnesses, family history, fertility/pregnancy, hormone treatment, menstrual history, and visual analog scales for common painful symptoms of endometriosis | The questionnaire did not attempt to differentiate between women with and without endometriosis and may be too long to be feasible as a patient-completed screener | Performance not reported |
| Nnoaham et al. [ |
| Predictive symptom-based model | Multiple logistic regressions to predict the likelihood of finding endometriosis on laparoscopy in women with pelvic pain and/or infertility | Validated symptom-based models were relatively poor for predicting any-stage endometriosis, but accuracy was slightly increased if there was ultrasound evidence of ovarian cysts or nodules; stage III/IV endometriosis was predicted with a good accuracy | Area under ROC curve = 0.683 |
| Endometriosis Self-test [ | United States | Patient-completed questionnaire | Self-scoring (yes/no) of 10 factors associated with endometriosis that could lead women to suspect endometriosis and contact their gynecologist/doctor; 3 or more “yes” answers could indicate the presence of endometriosis | Includes some core concepts, but a woman could screen “positive” for possible endometriosis by checking 3 of the nonsymptom items | Performance and validation not reported |
| Park et al. [ | United States | Patient-completed web-based application for women undergoing surgery or medical therapy for endometriosis | Web-based educational and symptom survey tool | Enables patients to self-evaluate and efficiently document endometriosis symptoms and to report alarming symptoms | Performance and validation not reported |
| Site-specific endometriosis studies | |||||
| Griffiths et al. [ |
| Retrospective, observational analysis of patient-reported symptoms | Prevalence-based likelihood ratios to calculate the relative strength of each potential symptom of rectovaginal endometriosis (i.e., dysmenorrhea, dyspareunia, infertility, dyschezia, rectal pain, cyclical and noncyclical rectal bleeding, tenesmus, and diarrhea) | Potentially a useful measure to diagnose site-specific endometriosis, but utility for detecting endometriosis in the general population may be limited | Apareunia and nausea or abdominal bloating were particularly strong markers for rectovaginal disease with a predictive prevalence of 87 and 89%, respectively |
| Fedele et al. [ |
| Partial modification of the American Urologic Association Symptom Index (AUASI) | Presurgical diagnosis of bladder endometriosis using a 7-item questionnaire, with 3 disease-specific items designed to assess irritative symptoms, especially during the perimenstrual period | Potentially a useful measure to diagnose site-specific endometriosis, but utility for detecting endometriosis in the general population may be limited | Excellent diagnostic accuracy for bladder endometriosis in a population with a high suspicion of bladder involvement |
| DIE studies | |||||
| Chapron et al. [ |
| Diagnostic model based on a list of symptoms collected via a standardized self-administered questionnaire | Predicting posterior DIE in women with symptoms including dysmenorrhea, dyspareunia, nonmenstrual pain, and urinary or gastrointestinal symptoms during menses | Painful defecation during menses was the strongest predictor of posterior DIE | Area under the ROC curve was 0.77, sensitivity was 74.5%, specificity was 68.7%, positive likelihood ratio was 2.4, and negative likelihood ratio was 0.4 |
| Lafay Pillet et al. [ |
| DIE score calculated from a multiple regression model, derived from preoperative symptom questionnaire | Diagnostic score calculated to predict the risk of DIE based on 57 variables | A diagnostic score calculated from four clinical symptoms of DIE in patients who underwent surgery for an endometriosis cyst had good diagnostic performance | AUC for 4-symptom model: 0.84 (95% CI 0.79–0.90) |
| Perelló et al. [ |
| Retrospective analysis of women with histologically confirmed ovarian endometrioma who underwent surgery | Model to predict DIE in patients with ovarian endometrioma | Model showed good discrimination in predicting development of DIE in patients with ovarian endometriomas | Area under the ROC curve was 0.91 (95% CI 0.86–0.95), optimal cutoff of the predicted probability was 0.54, sensitivity was 80%, specificity was 84%, and 81% were correctly classified |
| Bezerra Barcellos et al. [ |
| Assessment of clinical signs and anatomic sites using Lasmar map [ | Assessment of anatomical areas affected by endometriosis using sites of disease recorded by medical history, physical examination, imaging tests without laparoscopy, age, parity, skin color, and symptoms (dysmenorrhea, hypermenorrhea, pelvic pain not related to menstrual cycle, dyspareunia, dyschezia, or urinary symptoms) | Diagnostic approach includes imaging evaluation rather than symptoms only | The preoperative clinical evaluation/Lasmar map had high sensitivity, specificity, and accuracy for identifying the main sites of endometriosis without diagnostic laparoscopy |
AUC area under the curve, CI confidence interval, DIE deep-infiltrating endometriosis, OB/GYN obstetrician/gynecologist, PCP primary care physician, ROC receiver-operating characteristic
aWorld Endometriosis Research Foundation–Women’s Health Symptom Survey, a 25-item, self-administered questionnaire completed prior to surgery (>200 variables)