The ovarian response prediction index (ORPI) as a clinical internal quality control to prevent ovarian hyperstimualtion syndrome

Oliveira, J.B.A.; Franco, J.G.

doi:10.5935/1518-0557.20160021

Cited by 7 publications

(4 citation statements)

References 4 publications

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“…[ 9 ] The cut-off value reported by that study approximated our results. Oliveira and Franco [ 28 ] reported the ORPI offered excellent ovarian response prediction (AUC = 0.91), and good predictions for the possibility of collecting >4 metaphase II oocytes (AUC = 0.84) and excessive ovarian response (AUC = 0.89) in infertile women, and ORPI value (≥1.7) was the benchmark that indicated high risk for OHSS. Selcuk et al [ 29 ] found that the level of association between the ovarian response tests and poor ovarian response data was (in descending order): ovarian sensitivity index (OSI), ORPI, AFC, AMH, and age (AUC = 0.976, 0.905, 0.899, 0.864, 0.617, respectively), and OSI and ORPI could be superior to other ovarian responsiveness markers for poor and high ovarian responses on cycles with agonist or antagonist protocols.…”

Section: Discussionmentioning

confidence: 99%

The comparison of evaluative effectiveness between antral follicle count/age ratio and ovarian response prediction index for the ovarian reserve and response functions in infertile women

Zhou

Zhao

et al. 2020

Medicine

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Aim of the present study was to explore the evaluative effectiveness of age, ovarian volume (OV), antral follicle count (AFC), serum follicle-stimulating hormone (FSH), anti-Müllerian hormone (AMH), AFC/Age ratio, AMH/Age ratio, FSH/luteinizing hormone (LH) ratio, and ovarian response prediction index (ORPI) to determine which could more advantageously assess ovarian reserve and response. This research enrolled 319 consecutive infertile women who had undergone in vitro fertilization-ET/intracytoplasmic sperm injection (IVF-ET/ICSI) treatments. Abovementioned variables were measured and calculated. Receiver operating characteristic (ROC) curve analysis was used to analyze the predictive accuracy of variables and to calculate cut-off values and corresponding sensitivity and specificity. Our study revealed that the significant variables for evaluating a decline in ovarian reserve include age, OV, FSH, AFC/Age ratio, AMH/Age ratio, and ORPI. Moreover, the area under the curve (AUC) of AFC/Age ratio was higher than other 5 variables (AUC = 1.000), and the cut-off value of AFC/Age ratio was 0.111 (sensitivity 100.00%, specificity 100.00%). The significant variables forecasting excessive ovarian response were age, AFC, AMH, FSH, AFC/Age ratio, AMH/Age ratio, FSH/LH ratio, and ORPI, and the significant variables forecasting poor ovarian response were AMH, LH, OV, AFC/Age ratio, AMH/Age ratio, and FSH/LH ratio. When ORPI was used to predict excessive response, the cut-off value of ORPI was 0.880 (sensitivity 84.72%, specificity 67.32%) and ORPI presented better effectiveness. When used to predict poor response, the evaluative effectiveness of 6 variables was almost similar, although the AUC of AFC/Age ratio presented the largest value. Regarding the infertile women, AFC/Age ratio performed better than did the other variables in evaluating ovarian reserve, and it offered excellent effectiveness in predicting poor ovarian response, however, ORPI presented better effectiveness in predicting excessive ovarian response.

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Section: Discussionmentioning

confidence: 99%

The comparison of evaluative effectiveness between antral follicle count/age ratio and ovarian response prediction index for the ovarian reserve and response functions in infertile women

Zhou

Zhao

et al. 2020

Medicine

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“…The ovarian response prediction index (ORPI), calculated as the product of AMH level (ng/ml) and AFC divided by age of the woman (years), was first reported by Oliveira et al (53). The original study showed that ORPI had good prediction on oocyte yield, and the same group subsequently also showed that using ORPI for individualization of the ovarian stimulation regimen resulted in elimination of OHSS in their center (54). A retrospective analysis on 285 women stimulated with a standardized initiation dose using corifollitropin alpha in the GnRH antagonist protocol confirmed that ORPI was significantly correlated with the oocyte yield (55).…”

Section: Discordance Between Amh and Afc In Prediction Of Ovarian Resmentioning

confidence: 99%

Clinical Application of AMH Measurement in Assisted Reproduction

Nelson

2020

Front. Endocrinol.

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Anti-Müllerian hormone reflects the continuum of the functional ovarian reserve, and as such can predict ovarian response to gonadotropin stimulation and be used to individualize treatment pathways to improve efficacy and safety. However, consistent with other biomarkers and age-based prediction models it has limited ability to predict live birth and should not be used to refuse treatment, but rather to inform counselling and shared decision making. The use of absolute clinical thresholds to stratify patient phenotypes, assess discordance and individualize treatment protocols in non-validated algorithms combined with the lack of standardization of assays may result in inappropriate classification and sub-optimal clinical decision making. We propose that holistic baseline phenotyping, incorporating antral follicle count and other patient characteristics is critical. Treatment decisions driven by validated algorithms that use ovarian reserve biomarkers as continuous measures, reducing the risk of misclassification, are likely to improve overall outcomes for our patients.

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“…The cut-off value reported by that study approximated our results. Oliveira et al [28] reported the ORPI offered excellent ovarian response prediction (AUC = 0.91), and good predictions for the possibility of collecting > 4 MII oocytes (AUC = 0.84) and excessive ovarian response (AUC = 0.89) in infertile women, and ORPI value (≥1.7) was the benchmark that indicated high risk for OHSS. Selcuk et al [29] found that the level of association between the ovarian response tests and poor ovarian response data was (in descending order): ovarian sensitivity index (OSI), ORPI, AFC, AMH, and age (AUC = 0.976, 0.905, 0.899, 0.864, 0.617, respectively), and OSI and ORPI could be superior to other ovarian responsiveness markers for poor and high ovarian responses on cycles with agonist or antagonist protocols.…”

Section: Discussionmentioning

confidence: 98%

The evaluative effectiveness of a combined index exceeded that of a single variable for the ovarian reserve and response of infertile women

Zhou

Zhao

et al. 2019

Preprint

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Aim of the present study was to explore the evaluative effectiveness of age, ovarian volume, antral follicle count (AFC), serum follicle-stimulating hormone (FSH), anti-Müllerian hormone (AMH), FSH/LH ratio and ovarian response prediction index (ORPI) to determine which could most advantageously assess ovarian reserve and response.Methods This research enrolled 319 consecutive infertile women who had undergone IVF-ET/ICSI treatments. Abovementioned variables were measured and calculated. Receiver Operating Characteristic Curve analysis was used to analyze the predictive accuracy of variables and to calculate cut-off values and corresponding sensitivity and specificity.Results Our study revealed that the significant variables for evaluating a decline in ovarian reserve include age, total volume of bilateral ovary, FSH, and ORPI. Moreover, the area under the curve (AUC) of ORPI was higher than other three variables (AUC = 0.903), and the cut-off value of ORPI was 0.245 (sensitivity 90.1%, specificity 73.9%). The significant variables forecasting excessive ovarian response were age, AFC, AMH, ORPI, FSH and FSH/LH ratio, and the significant variables forecasting low ovarian response were AMH and FSH/LH ratio. ORPI and FSH/LH ratio presented better effectiveness in evaluating ovarian response. When they were used to predict excessive response, the cut-off values of ORPI and FSH/LH ratio was 0.886 (sensitivity 84.7%, specificity 67.3%) and 1.753 (sensitivity 56.2%, specificity 67.6%), respectively. When used to predict low response, the cut-off value of FSH/LH ratio was 2.983 (sensitivity 75.0%, specificity 83.8%).Conclusions ORPI performed better than did the other variables in evaluating ovarian reserve and predicting excessive ovarian response, and the FSH/LH ratio performed better than did the other variables in predicting low ovarian response. Consequently, we agreed that the evaluative effectiveness of a combined index exceeded that of a single variable for evaluating the ovarian reserve and response of infertile women.

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The ovarian response prediction index (ORPI) as a clinical internal quality control to prevent ovarian hyperstimualtion syndrome

Cited by 7 publications

References 4 publications

The comparison of evaluative effectiveness between antral follicle count/age ratio and ovarian response prediction index for the ovarian reserve and response functions in infertile women

The comparison of evaluative effectiveness between antral follicle count/age ratio and ovarian response prediction index for the ovarian reserve and response functions in infertile women

Clinical Application of AMH Measurement in Assisted Reproduction

The evaluative effectiveness of a combined index exceeded that of a single variable for the ovarian reserve and response of infertile women

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