Multiplexed Serum Biomarkers to Discriminate Nonviable and Ectopic Pregnancy.

OBJECTIVE: The use of multiplexed biomarkers may improve the diagnosis of normal and abnormal early pregnancies. In this study we assessed 24 markers with multiple machine learning-based methodologies to evaluate combinations of top candidates to develop a multiplexed prediction model for identification of 1) viability and 2) location of an early pregnancy. DESIGN: A nested case-control design evaluating the predictive ability and discrimination of biomarkers in patients at risk of early pregnancy failure in the first trimester to classify viability and location SUBJECTS: 218 individuals with a symptomatic (pain and/or bleeding) early pregnancy: 75 with an ongoing intrauterine gestation, 68 ectopic pregnancies, and 75 miscarriages. INTERVENTIONS: Serum values of 24 biomarkers were assessed in the same patients. Multiple machine learning-based methodologies to evaluate combinations of these top candidates to develop a multiplexed prediction model for identification of 1) a nonviable pregnancy (ongoing intrauterine pregnancy vs miscarriage or ectopic pregnancy) and 2) an ectopic pregnancy (ectopic pregnancy vs ongoing intrauterine pregnancy or miscarriage). MAIN OUTCOME MEASURES: The predicted classification by each model was compared to actual diagnosis and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), conclusive classification, and accuracy were calculated. RESULTS: Models using classification regression tree analysis using three markers (PSG3, CG-Alpha and PAPPA) were able to predict a maximum sensitivity 93.3%, a maximum specificity 98.6%. The model with the highest accuracy was 97.4% (with 70.2% receiving classification). Models using an overlapping group of three markers (sFLT, PSG3 and TFP12) achieved a maximum sensitivity of 98.5%. and a maximum specificity of 95.3%. The model with the highest accuracy was 94.4% (with 65.6% receiving classification). When the models were used simultaneously the conclusive classification increased to 72.7% with an accuracy 95.9%. The predictive ability of the biomarkers random forest produced similar test characteristics when using 11 predictive markers. CONCLUSION: We have demonstrated a pool of biomarkers from divergent biological pathways that can be used to classify individuals with potential early pregnancy loss. The biomarkers CG-Alpha, PAPPA and PSG3 can be used to predict viability and sFLT, TPFI2 and PSG3 can be used to predict pregnancy location.

Cost-effectiveness analysis of expectant vs active management for treatment of persistent pregnancies of unknown location.

BACKGROUND: Persistent pregnancies of unknown location are defined by abnormally trending serum human chorionic gonadotropin with nondiagnostic ultrasound. There is no consensus on optimal management. OBJECTIVE: This study aimed to assess the cost-effectiveness of 3 primary management strategies for persistent pregnancies of unknown location: (1) expectant management, (2) empirical 2-dose methotrexate, and (3) uterine evacuation followed by methotrexate, if indicated. STUDY DESIGN: This was a prospective economic evaluation performed concurrently with the Expectant versus Active Management for Treatment of Persistent Pregnancies of Unknown Location multicenter randomized trial that was conducted from July 2014 to June 2019. Participants were randomized 1:1:1 to expectant management, 2-dose methotrexate, or uterine evacuation. The analysis was from the healthcare sector perspective with a 6-week time horizon after randomization. Costs were expressed in 2018 US dollars. Effectiveness was measured in quality-adjusted life years and the rate of salpingectomy. Incremental cost-effectiveness ratios and cost-effectiveness acceptability curves were generated. Sensitivity analyses were performed to assess the robustness of the analysis. RESULTS: Methotrexate had the lowest mean cost ($875), followed by expectant management ($1085) and uterine evacuation ($1902) (P=.001). Expectant management had the highest mean quality-adjusted life years (0.1043), followed by methotrexate (0.1031) and uterine evacuation (0.0992) (P=.0001). The salpingectomy rate was higher for expectant management than for methotrexate (9.4% vs 1.2%, respectively; P=.02) and for expectant management than for uterine evacuation (9.4% vs 8.1%, respectively; P=.04). Uterine evacuation, with the highest costs and the lowest quality-adjusted life years, was dominated by both expectant management and methotrexate. In the base case analysis, expectant management was not cost-effective compared with methotrexate at a willingness to pay of $150,000 per quality-adjusted life year given an incremental cost-effectiveness ratio of $175,083 per quality-adjusted life year gained (95% confidence interval, -$1,666,825 to $2,676,375). Threshold analysis demonstrated that methotrexate administration would have to cost $214 (an increase of $16 or 8%) to favor expectant management. Moreover, expectant management would be favorable in lower-risk patient populations with rates of laparoscopic surgical management for ectopic pregnancy not exceeding 4% of pregnancies of unknown location. Based on the cost-effectiveness acceptability curves, the probability of expectant management being cost-effective compared with methotrexate at a willingness to pay of $150,000 per quality-adjusted life year gained was 50%. The results were dependent on the cost of surgical intervention and the expected rate of methotrexate failure. CONCLUSION: The management of pregnancies of unknown location with a 2-dose methotrexate protocol may be cost-effective compared with expectant management and uterine evacuation. Although uterine evacuation was dominated, expectant management vs methotrexate results were sensitive to modest changes in treatment costs of both methotrexate and surgical management.

Evaluation of novel biomarkers for early pregnancy outcome prediction†.

OBJECTIVE: To assess performance and discriminatory capacity of commercially available enzyme-linked immunosorbent assays of biomarkers for predicting first trimester pregnancy outcome in a multi-center cohort. DESIGN: In a case-control study at three academic centers of women with pain and bleeding in early pregnancy, enzyme-linked immunosorbent assays of biomarkers were screened for assay performance. Performance was assessed via functional sensitivity, assay reportable range, recovery/linearity, and intra-assay precision (%Coefficient of Variation). Top candidates were analyzed for discriminatory capacity for viability and location among 210 women with tubal ectopic pregnancy, viable intrauterine pregnancy, or miscarriage. Assay discrimination was assessed by visual plots, area under the curve with 95% confidence intervals, and measures of central tendency with two-sample t-tests. RESULTS: Of 25 biomarkers evaluated, 22 demonstrated good or acceptable assay performance. Transgelin-2, oviductal glycoprotein, and integrin-linked kinase were rejected due to poor performance. The best biomarkers for discrimination of pregnancy location were pregnancy-specific beta-1-glycoprotein 9, pregnancy-specific beta-1-glycoprotein 1, insulin-like growth factor binding protein 1, kisspeptin (KISS1), pregnancy-specific beta-1-glycoprotein 3, and beta parvin (PARVB). The best biomarkers for discrimination of pregnancy viability were pregnancy-specific beta-1-glycoprotein 9, pregnancy-specific beta-1-glycoprotein 3, EH domain-containing protein 3, KISS1, WAP four-disulfide core domain protein 2 (HE4), quiescin sulfhydryl oxidase 2, and pregnancy-specific beta-1-glycoprotein 1. CONCLUSION: Performance of commercially available enzyme-linked immunosorbent assays was acceptable for a panel of novel biomarkers to predict early pregnancy outcome. Of these, six and seven candidates demonstrated good discriminatory capacity of pregnancy location and viability, respectively, when validated in a distinct external population. Four markers demonstrated good discrimination for both location and viability.

Identification and verification of plasma protein biomarkers that accurately identify an ectopic pregnancy.

BACKGROUND: Differentiating between a normal intrauterine pregnancy (IUP) and abnormal conditions including early pregnancy loss (EPL) or ectopic pregnancy (EP) is a major clinical challenge in early pregnancy. Currently, serial ß-human chorionic gonadotropin (ß-hCG) and progesterone are the most commonly used plasma biomarkers for evaluating pregnancy prognosis when ultrasound is inconclusive. However, neither biomarker can predict an EP with sufficient and reproducible accuracy. Hence, identification of new plasma biomarkers that can accurately diagnose EP would have great clinical value. METHODS: Plasma was collected from a discovery cohort of 48 consenting women having an IUP, EPL, or EP. Samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by a label-free proteomics analysis to identify significant changes between pregnancy outcomes. A panel of 14 candidate biomarkers were then verified in an independent cohort of 74 women using absolute quantitation by targeted parallel reaction monitoring mass spectrometry (PRM-MS) which provided the capacity to distinguish between closely related protein isoforms. Logistic regression and Lasso feature selection were used to evaluate the performance of individual biomarkers and panels of multiple biomarkers to predict EP. RESULTS: A total of 1391 proteins were identified in an unbiased plasma proteome discovery. A number of significant changes (FDR ≤ 5%) were identified when comparing EP vs. non-EP (IUP + EPL). Next, 14 candidate biomarkers (ADAM12, CGA, CGB, ISM2, NOTUM, PAEP, PAPPA, PSG1, PSG2, PSG3, PSG9, PSG11, PSG6/9, and PSG8/1) were verified as being significantly different between EP and non-EP in an independent cohort (FDR ≤ 5%). Using logistic regression models, a risk score for EP was calculated for each subject, and four multiple biomarker logistic models were identified that performed similarly and had higher AUCs than models with single predictors. CONCLUSIONS: Overall, four multivariable logistic models were identified that had significantly better prediction of having EP than those logistic models with single biomarkers. Model 4 (NOTUM, PAEP, PAPPA, ADAM12) had the highest AUC (0.987) and accuracy (96%). However, because the models are statistically similar, all markers in the four models and other highly correlated markers should be considered in further validation studies.

Application of a Multiplex Platform to Identify Novel Biomarkers for Pregnancy Location and Viability.

Determining early pregnancy location and viability can be cumbersome, often requiring serial evaluations. This study aimed to identify novel biomarker candidates for pregnancy location and viability using a pseudodiscovery high-throughput technique. This was a case-control study among patients presenting for early pregnancy assessment, including ectopic pregnancies, early pregnancy losses, and viable intrauterine pregnancies. For pregnancy location, ectopic pregnancy was considered "case" and non-ectopic considered "control." For pregnancy viability, viable intrauterine pregnancy was considered "case" and early pregnancy loss + ectopic pregnancy were considered "control." Using Proximity Extension Assay technology from Olink Proteomics, serum levels of 1012 proteins were compared separately for pregnancy location and viability. Receiver operator characteristic curves were generated to determine a biomarker's discriminative abilities. Analysis included 13 ectopic pregnancies, 76 early pregnancy losses, and 27 viable intrauterine pregnancies. For pregnancy location, 18 markers had an area under the curve (AUC) ≥0.80, with three being expressed more in ectopic compared to non-ectopic pregnancies: thyrotropin subunit beta, carbonic anhydrase 3, and DEAD (Asp-Glu-Ala-Asp) box polypeptide 58. For pregnancy viability, two markers had an AUC ≥0.80: lutropin subunit beta and serpin B8. While some of the markers had previously been implicated in early pregnancy physiology, others were from pathways not previously explored. Using a high-throughput platform, a large number of proteins were screened as potential biomarkers for pregnancy location and viability, and twenty candidate biomarkers were identified. Further exploration of these proteins may facilitate validation as diagnostic tools for establishing early pregnancy diagnoses.

Evaluation of a New Model for Human Chorionic Gonadotropin Rise in Pregnancies of Unknown Viability.

OBJECTIVE: To evaluate the performance of a new human chorionic gonadotropin (hCG) threshold model to classify pregnancies as viable or nonviable using a longitudinal cohort of individuals with pregnancy of unknown viability. The secondary objective was to compare the new model with three established models. METHODS: This is a single-center, retrospective cohort study of individuals seen at the University of Missouri from January 1, 2015, until March 1, 2020, who had at least two consecutive quantitative hCG serum levels with an initial level greater than 2 milli-international units/mL and 5,000 milli-international units/mL or less, with the first interval between laboratory draws no greater than 7 days. Prevalence of correct classification of viable intrauterine pregnancies, ectopic pregnancies, and early pregnancy losses was evaluated with a new proposed hCG threshold model and compared with three established models describing minimum expected rates of hCG rise for a viable intrauterine pregnancy. RESULTS: Of an initial cohort of 1,295 individuals, 688 patients met inclusion criteria. One hundred sixty-seven individuals (24.3%) had a viable intrauterine pregnancy; 463 (67.3%) had an early pregnancy loss; and 58 (8.4%) had an ectopic pregnancy. A new model based on the total additive percent rise of hCG at 4 and 6 days after initial hCG (70% or greater and 200% or greater rise, respectively) was created. The new model was able to correctly identify 100% of viable intrauterine pregnancies while minimizing incorrect classification of early pregnancy losses and ectopic pregnancies as normal pregnancies. At 4 days after initial hCG, 14 ectopic pregnancies (24.1%) and 44 early pregnancy losses (9.5%) were incorrectly classified as potentially normal pregnancies. At 6 days after initial hCG, only seven ectopic pregnancies (12.1%) and 25 early pregnancy losses (5.6%) were incorrectly classified as potentially normal pregnancies. In established models, up to nine intrauterine pregnancies (5.4%) were misclassified as abnormal pregnancies and up to 26 ectopic pregnancies (44.8%) and 58 early pregnancy losses (12.5%) were incorrectly classified as potentially normal pregnancies. CONCLUSION: The proposed new hCG threshold model optimizes a balance between identifying potentially viable intrauterine pregnancies and minimizing misdiagnosis of ectopic pregnancies and early pregnancy losses. External validation in other cohorts is needed before widespread clinical use.

Leveraging electronic health record data for endometriosis research.

Endometriosis is a chronic, complex disease for which there are vast disparities in diagnosis and treatment between sociodemographic groups. Clinical presentation of endometriosis can vary from asymptomatic disease-often identified during (in)fertility consultations-to dysmenorrhea and debilitating pelvic pain. Because of this complexity, delayed diagnosis (mean time to diagnosis is 1.7-3.6 years) and misdiagnosis is common. Early and accurate diagnosis of endometriosis remains a research priority for patient advocates and healthcare providers. Electronic health records (EHRs) have been widely adopted as a data source in biomedical research. However, they remain a largely untapped source of data for endometriosis research. EHRs capture diverse, real-world patient populations and care trajectories and can be used to learn patterns of underlying risk factors for endometriosis which, in turn, can be used to inform screening guidelines to help clinicians efficiently and effectively recognize and diagnose the disease in all patient populations reducing inequities in care. Here, we provide an overview of the advantages and limitations of using EHR data to study endometriosis. We describe the prevalence of endometriosis observed in diverse populations from multiple healthcare institutions, examples of variables that can be extracted from EHRs to enhance the accuracy of endometriosis prediction, and opportunities to leverage longitudinal EHR data to improve our understanding of long-term health consequences for all patients.

Application of a Multiplex Platform to Identify Novel Biomarkers for Pregnancy Location and Viability.

Determining early pregnancy location and viability can be cumbersome, often requiring serial evaluations. This study aimed to identify novel biomarker candidates for pregnancy location and viability using a pseudodiscovery high through-put technique. This was a case-control study among patients presenting for early pregnancy assessment, including ectopic pregnancies, early pregnancy losses, and viable intrauterine pregnancies. For pregnancy location, ectopic pregnancy was considered "case" and non-ectopic considered "control." For pregnancy viability, viable intrauterine pregnancy was considered "case" and early pregnancy loss + ectopic pregnancy were considered "control." Using Proximity Extension Assay technology from Olink Proteomics, serum levels of 1012 proteins were compared separately for pregnancy location and viability. Receiver operator characteristic curves were generated to determine a biomarker's discriminative abilities. Analysis included 13 ectopic pregnancies, 76 early pregnancy losses, and 27 viable intrauterine pregnancies. For pregnancy location, 18 markers had an area under the curve (AUC) ≥ 0.80, with three being expressed more in ectopic compared to non-ectopic pregnancies: thyrotropin subunit beta, carbonic anhydrase 3, and DEAD (Asp-Glu-Ala-Asp) box polypeptide 58. For pregnancy viability, two markers had an AUC ≥ 0.80: lutropin subunit beta and serpin B8. While some of the markers were previously identified as implicated in early pregnancy physiology, others were from pathways not previously explored. Using a high through-put platform, a large number of proteins were screened as potential biomarkers for pregnancy location and viability, and twenty candidate biomarkers were identified. Further exploration of these proteins may facilitate validation as diagnostic tools for establishing early pregnancy diagnoses.

A core outcome set for trials in miscarriage management and prevention: An international consensus development study.

OBJECTIVE: To develop core outcome sets (COS) for miscarriage management and prevention. DESIGN: Modified Delphi survey combined with a consensus development meeting. SETTING: International. POPULATION: Stakeholder groups included healthcare providers, international experts, researchers, charities and couples with lived experience of miscarriage from 15 countries: 129 stakeholders for miscarriage management and 437 for miscarriage prevention. METHODS: Modified Delphi method and modified nominal group technique. RESULTS: The final COS for miscarriage management comprises six outcomes: efficacy of treatment, heavy vaginal bleeding, pelvic infection, maternal death, treatment or procedure-related complications, and patient satisfaction. The final COS for miscarriage prevention comprises 12 outcomes: pregnancy loss <24 weeks' gestation, live birth, gestation at birth, pre-term birth, congenital abnormalities, fetal growth restriction, maternal (antenatal) complications, compliance with intervention, patient satisfaction, maternal hospitalisation, neonatal or infant hospitalisation, and neonatal or infant death. Other outcomes identified as important were mental health-related outcomes, future fertility and health economic outcomes. CONCLUSIONS: This study has developed two core outcome sets, through robust methodology, that should be implemented across future randomised trials and systematic reviews in miscarriage management and prevention. This work will help to standardise outcome selection, collection and reporting, and improve the quality and safety of future studies in miscarriage.

Heavy Menstrual Bleeding Treatment With a Levonorgestrel 52-mg Intrauterine Device.

OBJECTIVE: To evaluate heavy menstrual bleeding treatment outcomes with levonorgestrel 52-mg intrauterine device (IUD) use in participants without body mass index (BMI) or parity restrictions. METHODS: Investigators included participants aged 18-50 years with no pelvic or systemic pathology causing heavy menstrual bleeding at 29 U.S. centers in a prospective trial. Participants had up to three screening cycles with menstrual product collection for alkaline hematin blood-loss measurements. Investigators enrolled those with two menses with blood loss of 80 mL or more (values averaged for baseline blood loss), placed the IUD, and followed participants for up to six 28-day cycles. Participants collected any menstrual products used during cycles 3 and 6 for blood-loss measurement. We evaluated outcomes in participants with at least one follow-up assessment for the primary outcome of median absolute blood-loss change and, secondarily, treatment success , defined as the proportion with a final measured blood loss less than 80 mL and at least 50% reduction from baseline. We evaluated exploratory outcomes of differences in blood-loss changes by BMI and parity using Wilcoxon rank sum test. RESULTS: Of 105 enrolled participants, 47 (44.8%) had obesity (BMI 30.0 or higher) and 29 (27.6%) were nulliparous. Baseline mean blood loss ranged from 73 to 520 mL (median 143 mL, interquartile range 112-196 mL). Eighty-nine (84.8%) had at least one evaluable follow-up evaluation. Participants had median (interquartile range) absolute blood-loss decreases at cycles 3 (n=86) and 6 (n=81) of 93.3% (86.1-97.7%) and 97.6% (90.4-100%), respectively. At cycle 6, participants without obesity (n=43) and with obesity (n=38) had similar median [interquartile range] decreases (97.6% [91.8-100%] and 97.5% [90.3-100%], respectively; P =.89), with comparable findings for nulliparous (n=25) and parous (n=56) participants (97.0% [91.7-99.1%] and 98.1% [89.9-100%], respectively; P =.43). Treatment success occurred in 81.8% (95% CI 74.2-89.4%) of 99 participants, excluding those with no outcomes due to lost to follow-up or consent withdrawal, and did not vary by BMI or parity. The most common adverse events leading to discontinuation were bleeding or cramping (n=6 [5.7%]) and expulsion (n=5 [4.8%]). CONCLUSION: This levonorgestrel 52-mg IUD reduces blood loss by more than 90% over 6 months compared with baseline for most users with heavy menstrual bleeding. FUNDING SOURCE: Medicines360. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov , NCT03642210.

What Is an Ectopic Pregnancy?

This JAMA Patient Page describes ectopic pregnancy and its risk factors, symptoms, diagnosis, and treatment.

A core outcome set for future research in ectopic pregnancy: an international consensus development study.

OBJECTIVE: To address methodological deficiencies in published randomized controlled trials and systematic reviews, this study has developed a core outcome set to guide future research in ectopic pregnancy (EP). DESIGN: To identify potential outcomes, we performed a comprehensive literature review and interviews with individuals with lived experience in EP. Potential core outcomes were then entered into a 3-round Delphi survey. A total of 154 participants from 6 continents, comprising health care professionals, researchers, and individuals with lived experience in EP, completed all 3 rounds of the Delphi survey. Outcomes were prioritized at 3 consensus development meetings, and recommendations were developed on how to report these outcomes where possible. SETTING: Not applicable. PATIENT(S): Health care professionals, researchers, and individuals with lived experience in EP. INTERVENTION(S): Not applicable. MAIN OUTCOME MEASURE(S): Consensus for inclusion in core outcome set. RESULT(S): Six outcomes reached full consensus, including treatment success, resolution time, the number of additional interventions, adverse events, mortality and severe morbidity, and treatment satisfaction. CONCLUSION(S): The core outcome set with 6 outcomes for EP will help standardize reporting of clinical trials, facilitate implementation of findings into clinical practice, and enhance patient-centered care.

Recurrent implantation failure: reality or a statistical mirage?: Consensus statement from the July 1, 2022 Lugano Workshop on recurrent implantation failure.

IMPORTANCE: To date, recurrent implantation failure (RIF) has no clear definition and no clearly identified impaired function. Hence, the term RIF is currently used somewhat haphazardly, on the basis of clinicians' judgment. OBJECTIVE: International experts in reproductive medicine met on July 1, 2022, in Lugano, Switzerland, to review the different facets of RIF and define the diagnosis and its appropriate management. EVIDENCE REVIEW: A systematic review without meta-analysis of studies published in English from January 2015 to May 2022. FINDINGS: Data indicated that RIF has been largely overevaluated, overdiagnosed, and overtreated without sufficient critical assessment of its true nature. Our analyses show that true RIF is extremely uncommon-occurring in <5% of couples with infertility-and that reassurance and continued conventional therapies are warranted in most cases of assisted reproductive technology (ART) failure. Although the true biologic determinants of RIF may exist in a small subset of people with infertility, they elude the currently available tools for assessment. Without identification of the true underlying etiology(ies), it is reasonable not to assign this diagnosis to a patient until she has failed at least 3 euploid blastocyst transfers (or the equivalent number of unscreened embryo transfers, adjusted to the patient's age and corresponding euploidy rate). In addition, other factors should be ruled out that may contribute to her reduced odds of sustained implantation. In such cases, implantation failure should not be the only issue considered in case of ART failure because this may result from multiple other factors that are not necessarily repetitive or persistent. In reality, RIF impacting the probability of further ART success is a very rare occurrence. CONCLUSION: True RIF is extremely uncommon, occurring in <5% of couples with infertility. Reassurance and continued conventional therapies are warranted in most cases. It would seem reasonable not to assign this diagnosis to a patient until she has failed at least 3 euploid embryo transfers (or the equivalent number of unscreened embryos, adjusted to her age). RELEVANCE: Given the number of internationally recognized experts in the field present at the Lugano meeting 2022, our publication constitutes a consensus statement.

Validation of a multiple marker test for early pregnancy outcome prediction.

PURPOSE: To validate the use of a multiple biomarker test panel for predicting first trimester pregnancy outcome in a multi-center cohort. METHODS: A case-control study of women presenting with pain and bleeding in early pregnancy at 5-10 weeks gestational age was performed at three academic centers. Sera from women with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage (SAB) were analyzed via immunoassay for Activin A (AA), Progesterone (P4), A Disintegrin And Metalloprotease-12 (ADAM12), pregnancy-associated plasma protein A (PAPP-A), glycodelin (Glyc), and human chorionic gonadotropin (hCG). Biomarkers were assessed for reproducibility using medians, ranges, standard deviations, and area under receiver-operating characteristic curve (AUC) and accuracy in early pregnancy outcome classification compared to a previous derivation population. RESULTS: In 192 pregnancies, the biomarkers demonstrated good reproducibility with similar medians, ranges, and AUCs when compared to the derivation population except glycodelin. Pregnancy location was conclusively classified in 53% (n = 94) of the whole study sample with 78% accuracy. Pregnancy viability was conclusively classified in 58% (n = 112) of the new sample with 89% accuracy. Results were similar with subsequent model revisions where glycodelin was excluded and in the subgroups of subjects with a hCG below 2000 mIU/mL and a gestational age less than 6 weeks. CONCLUSION: The use of a panel of biomarkers to maximize test accuracy of a prediction of pregnancy location and prediction of pregnancy viability was reproducible and validated in an external population from which it was derived, but clinical utility is limited based on the test characteristics obtained.