ArticleBMC women's health2023
Nomogram to predict FSH starting dose in poor ovarian response women in progestin primed ovarian stimulation protocol.
Article in BMC women's health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Development and externally validated prediction model of individualization of FSH starting dose in the depot GnRH agonist protocol for the early follicular phase.Frontiers in endocrinology · 2025Article
- A retrospective study: establishment and validation of the prediction model for the gonadotropin starting dose in IVF/ICSI-ET among normal ovarian response women.Frontiers in endocrinology · 2025Article
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Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction of individual ovarian response to exogenous gonadotropin is a cornerstone for success and safety in all controlled ovarian stimulation (COS) protocols. Providing the best FSH starting dose according to each woman's own characteristics is the key to the success of individualized treatment. The objective of this investigation was to evaluate the potential application of a novel nomogram based on antral follicle counting (AFC), anti-Müllerian hormone (AMH) and body mass index (BMI) as a tool to optimize the follicle-stimulating hormone (FSH) starting dose in women with poor ovarian response in in-vitro fertilization (IVF)/intra-cytoplasmic sperm injection (ICSI) cycles in progestin-primed ovarian stimulation (PPOS). We performed a retrospective analysis involving 130 poor ovarian responders undergoing IVF/ICSI cycles in a PPOS protocol from June 2017 to February 2019 in our reproductive center. The individual FSH starting dose was selected according to patients' clinical history and characteristics. The influence of variables including age, BMI, AMH and AFC on the FSH starting dose was assessed through multiple regression analysis. We used the variables reaching the statistical significance for calculation for the final predictive model. In the univariate analysis, BMI, AMH and AFC were significant (P < 0.05) predictors of FSH starting dose, age was canceled. In the multivariate analysis, BMI, AMH and AFC remained significant (P < 0.05). According to the nomogram, 118 patients (90.77% of 130) would have received a higher FSH starting dose and 12 patients (9.23% of 130) a lower FSH starting dose than practice dose. The application of the nomogram based on three variables easily determined in clinical practice: BMI, AMH and AFC would lead to a more tailored FSH starting dose in women with poor ovarian response.
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