Do female age and body weight modify the effect of individualized <scp>FSH</scp> dosing in <scp>IVF</scp>/<scp>ICSI</scp> treatment? A secondary analysis of the <scp>OPTIMIST</scp> trial

Chen²,

Zeng³

et al. 2022

Front. Endocrinol.

Polycystic ovarian syndrome (PCOS) is the major cause of anovulatory infertility. Since women with PCOS are often accompanied by increased body weight and hyper response to controlled ovarian stimulation, individualized gonadotropin (Gn) dose is required to achieve a therapeutic effect while minimizing the risk of ovarian hyperstimulation simultaneously. We aimed to investigate the essential role of body weight in optimizing initial Gn dosage for PCOS patients during in vitro fertilization (IVF). We retrospectively included 409 infertile PCOS patients who used gonadotropin-releasing hormone (GnRH)-antagonist fixed protocol and underwent their first cycle of IVF in West China Second University Hospital from January 2019 to June 2021. Baseline characteristics controlled ovarian stimulation parameters, and reproductive outcomes were compared between patients with different body weights and different ovarian responses. Multivariable linear regression analyses were adopted to investigate the relationship between body weight and initial Gn dosage. Receiver operating characteristic (ROC) curves were drawn to find the optimal cut-off value of body weight in predicting the starting Gn dosage so as to prevent high ovarian response (HOR). We found that luteinizing hormone (LH) level and Anti-Mullerian hormone (AMH) level were lowest in the group with body weight over 70 kg and was highest in the group with body weight less than 50 kg. Increased body weight was significantly correlated to the rise of initial Gn dosage (Beta = 0.399, t = 8.921, p < 0.001). Normal ovarian response (NOR) patients had significantly less fresh cycle cancel rate and ovarian hyperstimulation syndrome (OHSS) rate which outweighed the fewer embryos compared with HOR patients. Using ROC curves, 53.25 kg (sensitivity, 84.2%; specificity, 53.8%) and 70.5 kg (sensitivity, 58.8%; specificity, 93.0%) were identified as the optimal cut-off values to predict the initial Gn dosage of no more than 150 IU and 225 IU, respectively. In conclusion, adjusting the initial Gn dosage based on body weight is crucial to preventing ovarian hyperstimulation while not influencing reproductive outcomes for PCOS patients during IVF.

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The Essential Role of Body Weight in Adjusting Gn Dosage to Prevent High Ovarian Response for Women With PCOS During IVF: A Retrospective Study

Chen²,

Zeng³

et al. 2022

Front. Endocrinol.

“…Therefore, body weight is more predominant in determining FSH distribution than BMI [30]. A previous study found that reducing the FSH dose in predicted hyper responders with body weight > 55kg signi cantly decreased the OHSS occurrence but also decreased the probability of live birth [29]. On the contrary, a randomized controlled trial (RCT) found that reduction of Gn dosage signi cantly lowered the OHSS incidence, together with no in uence on live birth rates [16].…”

Section: Discussionmentioning

confidence: 99%

“…The excess weight affects the ovarian response to Gn [28]. Exogenous serum FSH level is inversely associated with body weight [29]. The volume of extracellular uid is a key factor in drug distribution.…”

Section: Discussionmentioning

confidence: 99%

Evaluating Body Weight In Predicting Initial Gn Dosage During IVF For Women With PCOS: A Retrospective Study

Chen

et al. 2022

Preprint

Background: Polycystic ovarian syndrome (PCOS) is the major cause of anovulatory infertility. Since women with PCOS are often accompanied by increased body weight and infertility, Individualized gonadotropin (Gn) dose is required to achieve therapeutic effect while minimizing the risk of ovarian hyperstimulation simultaneously. We aimed to investigate the essential role of body weight in optimizing initial Gn dosage for PCOS patients during in vitro fertilization (IVF).Methods: We retrospectively included 227 infertile PCOS patients who used gonadotropin-releasing hormone (GnRH)-antagonist fixed protocol underwent their first cycle of IVF in West China Second University Hospital from January 2019 to December 2020. Baseline characteristics controlled ovarian stimulation parameters, and reproductive outcomes were compared between patients with different body weights and different ovarian responses. Multivariable logistic regression analyses were adopted to investigate the relationship between body weight and initial Gn dosage. Receiver operating characteristic (ROC) curves were drawn to find the optimal cut-off value of body weight in predicting the starting Gn dosage so as to prevent high ovarian response (HOR).Results: Circulating testosterone (T) level was increased and Anti-Mullerian hormone (AMH) level was decreased in higher weight groups compared to lower weight groups. Increased body weight was significantly correlated to the rise of initial Gn dosage (OR = 1.113, 95% CI = 1.021-1.227, p = 0.016). Normal ovarian response (NOR) patients had significantly less fresh cycle cancel rate and ovarian hyperstimulation syndrome (OHSS) rate which outweighed the slightly fewer embryos compared with HOR patients. Using ROC curves, 55.5 kg and 70.5 kg were identified as the optimal cut-off values to predict the initial Gn dosage no more than 150 IU (sensitivity, 72.5%; specificity, 63.4%) and 225 IU (sensitivity, 75.0%; specificity, 95.2%), respectively.Conclusion: Body weight was an independent factor for initial Gn dosage. Adjusting initial Gn dosage based on body weight is crucial to achieving better reproductive outcomes for PCOS patients during IVF.

“…Poor ovarian response leads to a high risk of treatment cycles being canceled or a lack of high-quality embryos for transfer. Studies have demonstrated that the impact features, e.g., a women’s clinical information (age, body mass index (BMI), infertility cause, and infertility duration), basal endocrine level (Anti-Müllerian hormone (AMH), basal follicle stimulating hormone (bFSH)), and ultrasound-related index (antral follicle count (AFC)), are closely related to the extent of ovarian response to COS [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. The features, such as age, AMH, bFSH, and AFC, etc., are currently recognized as high-impact features related to ovarian reserve function [ 10 , 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Modeling of Ovarian Response and the Quantitative Evaluation of Comprehensive Impact Features

et al. 2022

Appropriate ovarian responses to the controlled ovarian stimulation strategy is the premise for a good outcome of the in vitro fertilization cycle. With the booming of artificial intelligence, machine learning is becoming a popular and promising approach for tailoring a controlled ovarian stimulation strategy. Nowadays, most machine learning-based tailoring strategies aim to generally classify the controlled ovarian stimulation outcome, lacking the capacity to precisely predict the outcome and evaluate the impact features. Based on a clinical cohort composed of 1365 women and two machine learning methods of artificial neural network and supporting vector regression, a regression prediction model of the number of oocytes retrieved is trained, validated, and selected. Given the proposed model, an index called the normalized mean impact value is defined and calculated to reflect the importance of each impact feature. The proposed models can estimate the number of oocytes retrieved with high precision, with the regression coefficient being 0.882% and 89.84% of the instances having the prediction number ≤ 5. Among the impact features, the antral follicle count has the highest importance, followed by the E2 level on the human chorionic gonadotropin day, the age, and the Anti-Müllerian hormone, with their normalized mean impact value > 0.3. Based on the proposed model, the prognostic results for ovarian response can be predicted, which enables scientific clinical decision support for the customized controlled ovarian stimulation strategies for women, and eventually helps yield better in vitro fertilization outcomes.