Growth Hormone Enhances Ovarian Response but not Live Births in DOR Patients Undergoing PPOS with Freeze-all Strategy: A Retrospective Cohort Study Contrasted with Kuntai Capsule
XiaojuWan1
MinYu1
XingwuWu1
ZhihuiHuang1
JunTan1✉Emailtanjun561127@163.com
HongyingXu2✉Emailjxxuhongying@163.com
1Reproductive Medicine CenterJiangxi Maternal and Child Health HospitalNanchangChina
2Department of nursingJiangxi Maternal and Child Health HospitalNanchangChina
Xiaoju Wan1, Min Yu1, Xingwu Wu1, Zhihui Huang1, Jun Tan1*, Hongying Xu2*
1Reproductive Medicine Center, Jiangxi Maternal and Child Health Hospital, Nanchang, China
2Department of nursing, Jiangxi Maternal and Child Health Hospital, Nanchang, China
*Corresponding Author: Jun Tan, Email address: tanjun561127@163.com; Hongying Xu, Email address: jxxuhongying@163.com.
Abstract
Objective
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The Progestin-Primed Ovarian Stimulation (PPOS) protocol with a freeze-all strategy is increasingly used for patients with diminished ovarian reserve (DOR). While growth hormone (GH) and Kuntai capsule are proposed adjuvants to enhance outcomes in DOR, their efficacy within this specific treatment context is not well-established. This study aimed to determine whether pretreatment with these adjuvants improves IVF/ICSI outcomes, particularly live birth rates.Methods
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We conducted a large retrospective cohort study at a single tertiary center (2015–2025), including 2,969 DOR patients undergoing PPOS cycles. Participants were stratified into a control group (n = 1,665), a Kuntai capsule pretreatment group (n = 524), and a GH pretreatment group (n = 778). Propensity score matching (1:1:1) was applied to balance baseline characteristics, yielding 439 patients per group for final analysis. The primary outcome was the number of oocytes retrieved. Secondary outcomes encompassed embryo quality parameters, biochemical pregnancy, clinical pregnancy, and live birth rates. Generalized estimating equations (GEE) were employed to control for confounders.Results
GH supplementation significantly enhanced ovarian response, demonstrated by higher peak E₂ levels (607 vs. 518 pg/mL, p < 0.001), increased oocyte yield (3.0 vs. 2.0, p < 0.001), and a greater number of available embryos (2.0 vs. 1.0, p = 0.002) compared to the control. This translated to a higher biochemical pregnancy rate (67.4% vs. 57.3%, p = 0.006). However, clinical pregnancy (45.7% vs. 44.5%) and live birth rates (27.8% vs. 28.2%) remained comparable to controls (p > 0.05). GEE models confirmed GH was not a significant predictor of live birth (adjusted OR 0.85, 95% CI 0.54–1.33). In contrast, Kuntai capsule pretreatment showed no significant improvement over the control in any ovarian response parameters, embryo quality metrics, or clinical outcomes, including live birth (27.0% vs. 28.2%, p > 0.05). Multivariate analysis identified advanced maternal age (> 37 years) as the strongest negative predictor of success (live birth adjusted OR 0.36, p < 0.001).
Conclusion
In DOR patients managed with a PPOS and freeze-all strategy, GH pretreatment improves quantitative stimulation metrics and early pregnancy biomarkers but does not increase the likelihood of clinical pregnancy or live birth. Kuntai capsule pretreatment demonstrated no beneficial effects across all evaluated endpoints. These findings do not support the routine use of these adjuvants in this specific treatment paradigm.
Keywords:
diminished ovarian reserve
growth hormone
Kuntai capsule
PPOS
freeze-all
IVF/ICSI
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Introduction
Diminished ovarian reserve (DOR) signifies a critical reproductive health issue characterized by a quantitative and qualitative decline in the ovarian follicle pool, leading to reduced fecundity(1). The diagnosis typically relies on a combination of biomarkers, including elevated basal follicle-stimulating hormone (FSH), decreased anti-Müllerian hormone (AMH) levels, and a low antral follicle count (AFC)(2). Affecting a substantial proportion of women seeking fertility treatment, DOR imposes significant psychological and economic burdens, while its association with adverse assisted reproductive technology (ART) outcomes remains a central challenge in reproductive medicine(3)(4).
For DOR patients undergoing in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI), the Progestin-Primed Ovarian Stimulation (PPOS) protocol has gained prominence as an effective controlled ovarian stimulation (COS) strategy(5). PPOS reliably suppresses premature luteinizing hormone (LH) surges and offers practical advantages, including oral administration, reduced monitoring frequency, and lower overall costs, making it a valuable option for this patient population(6, 7).
A
Given the suboptimal outcomes often observed in DOR, adjuvant therapies are frequently explored to enhance success. Kuntai capsule, a traditional Chinese medicine approved for conditions related to ovarian function decline, is theorized to nourish the kidney and enrich yin based on its formulation principles(8–11). While some small-scale studies suggest potential benefits on ovarian response and embryo quality in DOR patients undergoing IVF/ICSI, these investigations are limited by sample size, involvement of fresh embryo transfers, and a lack of focus on the specific PPOS context with a freeze-all strategy (12, 13).Growth hormone (GH), integral to cellular metabolism and development, has also been investigated for its potential role in female reproduction(14)(15). Meta-analyses indicate that GH co-treatment might improve oocyte yield in DOR patients, but the evidence is marked by significant heterogeneity in protocols and patient populations. Notably, a compelling hypothesis suggests that GH's primary benefit may be mediated through endometrial receptivity—a mechanism that would be entirely circumvented in a freeze-all cycle, leaving its utility in this specific scenario uncertain(16).
Therefore, a critical evidence gap exists regarding the efficacy of both Kuntai capsule and GH as adjuvants specifically within the modern PPOS and freeze-all paradigm for DOR. This large-scale, propensity score-matched cohort study was designed to definitively assess whether pretreatment with these adjuvants translates into improved laboratory indices and, most importantly, superior live birth rates in this well-defined clinical context.
Materials and methods
Study Design and Population
This large, retrospective cohort study was conducted at a single reproductive medicine center, enrolling DOR patients who underwent their IVF/ICSI cycle using a PPOS protocol between January 2015 and February 2025.
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This retrospective study was conducted in accordance with the fundamental principles of the Declaration of Helsinki and was approved by the Reproductive Medicine Ethics Committee of Jiangxi Maternal and Child Health Hospital (Approval No. SZYY-202504). A
The need for informed consent from participants was waived by the aforementioned ethics committee due to the retrospective nature of the study.DOR was defined by the presence of at least one of the following criteria: AMH < 1.1 ng/ml, AFC < 7, or basal FSH ≥ 10 IU/L. Key exclusion criteria were chromosomal abnormalities, uterine malformations or organic diseases, severe hydrosalpinx, recurrent miscarriage history, donor gamete cycles, loss to follow-up, and cycles cancelled for poor follicular development. Initially, 2,969 couples were categorized into three groups based on pretreatment: a control group (n = 1,665), a Kuntai group (n = 524), and a GH group (n = 780), and the research process was illustrated in Fig. 1.
COS regimen and pretreatment of Kuntai capsules and GH
All patients underwent the PPOS protocol. Gonadotropin (Gn) stimulation was initiated on menstrual cycle day 2 or 3 using urinary follicle stimulating hormone (FSH, Lishenbao, Shanghai Lizhu; 150–300 IU/day). Simultaneously, oral medroxyprogesterone acetate (medroxyprogesterone acetate; Zhejiang Xianju; 8–10 mg/day) was administered to prevent LH surges.
Kuntai Group: Patients additionally received oral Kuntai Capsule (Guiyang Xintian, 0.5 g/capsule; 4 capsules, three times daily) from cycle day 3 until oocyte retrieval.
GH Group: Patients received daily subcutaneous recombinant human growth hormone (Changchun Jinsai; 3 IU/day) concurrently with Gn stimulation until the trigger day.
Egg retrieval, embryo culture and fresh embryo transfer
Triggering was performed with a combination of subcutaneous injection of 0.2 mg of triptorelin acetate (Dabijia, Germany) and intramuscular injection of human chorionic gonadotropin (hCG, Shanghai Lizhu) 2000U when follicular criteria were met (one follicle with a diameter ≥ 18 mm or three follicles with a diameter ≥ 17 mm). Oocytes were retrieved 34–36 hours later via transvaginal ultrasound puncture and fertilized via IVF/ICSI. Embryos were cultured in in G1/G2 (Vitrlife, Sweden) media, with cleavage-stage embryos graded on day 3 and blastocysts on day 5/6. All viable embryos were vitrified (RapidVit vitrification method; Vitrolife) for subsequent frozen-thawed embryo transfer (FET).
Endometrial preparation and frozen-thawed embryo transfer
For frozen-thawed embryo transfer, the endometrium was prepared using one of four protocols, chosen based on the patient's individual clinical profile:
Natural Cycle: For normal ovulation women. Monitoring began around cycle day 12. Intramuscular progesterone (40–60 mg/day, Zhejiang Xianju) was initiated following the detection of the LH surge.
Artificial Cycle: For women with irregular ovulation. Oral estradiol valerate (Bujiale, Bayer, Germany; 4–8 mg/day) was started on cycle day 2–3. After 12–14 days, if no dominant follicle was observed, endometrial transformation was induced with vaginal progesterone (80 mg/day, Zhejiang Xianju).
Down-regulated Artificial Cycle: For patients with a history of intrauterine adhesion or cesarean section. A long-acting GnRH agonist (leuprorelin acetate, 3.75 mg, Beiyi, Shanghai Lizhu) was administered on cycle day 2–3. After 28 days of down-regulation, the endometrial preparation followed the artificial cycle protocol.
Ovulation Induction Cycle: For patients with natural cycle follicular dysplasia or to shorten preparation time. Letrozole (Furui, Jiangsu Hengrui; 5 mg/day) was administered orally for 5 days starting on cycle day 2–3. From day 10–12, urinary FSH (HMG, Le Baode; Zhuhai Lizhu; 150 IU/day) was added if needed. When the endometrial thickness reached ≥ 8 mm and urinary LH was ≤ 20 mIU/ml, hCG (4000 IU) was administered. Progesterone supplementation was started after ultrasound-confirmed ovulation.
Either one or two cleavage-stage embryos were transferred on the 4th day of progesterone exposure, or one or two blastocysts were transferred on the 6th day.
Luteal support and Outcome Definitions
A
Luteal support commenced on the day of embryo transfer, consisting of oral dydrogesterone (Duphaston, Abbott, Netherlands; 20 mg/day) combined with vaginal progesterone sustained-release gel (Crinone, Merck Serono, Germany; 90 mg/day). This support was continued until 10 weeks of gestation.Primary and secondary outcomes were defined as follows:
Primary Outcome: Number of oocytes retrieved.
Secondary Outcomes:
Oocyte failure rate = (Cycles with 0 retrieved oocytes / Total retrieval cycles) × 100%.
Normal fertilization rate = (Number of 2PN zygotes / Total oocytes retrieved) × 100%.
Normal cleavage rate = (Number of cleavage-stage embryos / Number of normally fertilized oocytes) × 100%.
D3 high-quality embryo rate = (Number of high-quality D3 embryos / Number of cleavage-stage embryos) × 100%.
Available embryo formation rate = (Number of available embryos / Number of cleavage-stage embryos) × 100%.
Unusable embryo rate = (Cycles with no usable embryos / Total retrieval cycles) × 100%.
Biochemical pregnancy was defined as a serum hCG ≥ 5 mIU/ml 14 days after transfer.
Implantation rate = (Number of gestational sacs / Number of embryos transferred) × 100%.
Clinical pregnancy was confirmed by ultrasound visualization of a gestational sac with cardiac activity at 5 weeks post-transfer.
Pregnancy loss rate = (Number of spontaneous or therapeutic abortions / Number of clinical pregnancies) × 100%.
Live birth rate = (Number of live births ≥ 28 weeks / Number of transfer cycles) × 100%.
Data statistics and analysis
Data were analyzed using R software (version 3.3.4). Continuous variables were tested for normality with the Shapiro-Wilk test. Normally distributed data are presented as mean ± standard deviation and were compared using one-way ANOVA with Tukey's HSD post-hoc test. Non-normally distributed data are expressed as median [interquartile range, IQR] and were compared using the Kruskal-Wallis test with Dunn's post-hoc test (Bonferroni-adjusted p-values). Categorical data are presented as n (%) and were compared using the Chi-square test or Fisher's exact test, with Bonferroni adjustment for post-hoc pairwise comparisons.
To mitigate potential selection bias and balance baseline characteristics (including female age, BMI, basal FSH, AFC, AMH, infertility type, duration, and causes) across the three groups, we employed propensity score matching (PSM)(17). A 1:1:1 matching ratio was used, resulting in 439 well-matched patients per group for the final analysis.
To account for potential data clustering (where some patients contributed more than one treatment cycle), we utilized a Generalized Estimating Equation (GEE) model based on logistic regression to control for confounding factors when analyzing pregnancy outcomes(18). A p-value < 0.05 was considered significant.
Results
Baseline and Cohort Characteristics Before and After Matching
The patient selection, grouping, and propensity score matching workflow is illustrated in Fig. 1. Prior to PSM, significant disparities existed among the control (n = 1,665), Kuntai (n = 524), and GH (n = 778) groups in several baseline parameters, including basal FSH (median [IQR]: 8.28 [6.43, 11.2] vs. 9.02 [6.78, 12.3] vs. 8.09 [6.36, 10.7] IU/L, p < 0.001), LH (3.70 [2.58, 5.29] vs. 4.17 [2.97, 5.80] vs. 3.82 [2.67, 5.26] IU/L, p < 0.001), AMH (0.60 [0.37, 0.87] vs. 0.55 [0.30, 0.81] vs. 0.68 [0.44, 0.97] µg/L, p < 0.001), AFC (4.00 [3.00, 5.00] vs. 4.00 [3.00, 5.25] vs. 4.00 [3.00, 6.00], p = 0.001), as well as infertility type and causative factors (p < 0.05). Patient age and BMI were comparable across the three cohorts at baseline (p > 0.05, Table 1).
Following 1:1:1 PSM, 439 patients were retained in each group. The matching procedure successfully balanced all recorded baseline characteristics. The matched cohorts demonstrated no significant differences in age (median 36.0 years across all groups, p = 0.955), BMI (median 22.2 kg/m² across all groups, p = 0.950), hormonal profiles (FSH, LH, E₂, AMH), AFC, or infertility-related factors (all p > 0.05, Table 1), confirming the effectiveness of PSM in minimizing selection bias.
Stimulation and Embryological Outcomes in the Matched Cohort
Analysis of the matched cohorts revealed distinct differences in stimulation response and laboratory outcomes (Table 2). The GH group required a significantly higher total gonadotropin dose (1800 [1350–2025] IU) compared to both the control (1500 [1200–1950] IU) and Kuntai groups (1500 [1125–1950] IU; all adjusted p < 0.001). On the trigger day, the GH group exhibited a characteristic endocrine profile, marked by substantially higher serum E₂ levels (607 [388–956] pg/mL) relative to the control (518 [355–776] pg/mL) and Kuntai groups (510 [334–728] pg/mL; adjusted p < 0.001 for both comparisons). Concurrently, LH levels were lower in the GH group (2.91 [1.77–4.34] IU/L) compared to the Kuntai group (3.25 [2.06–4.70] IU/L; adjusted p = 0.011), and progesterone levels were marginally lower than in controls (0.19 [0.10–0.30] vs. 0.20 [0.12–0.31] ng/mL; adjusted p = 0.015).
Control group (n = 439) | Kuntai group (n = 439) | GH group (n = 439) | p | Control VS kuntai | Control VS GH | Kuntai VS GH | ||||
|---|---|---|---|---|---|---|---|---|---|---|
p (unadj) | p (adj) | p (unadj) | p (adj) | p (unadj) | p (adj) | |||||
Total dose of Gn (U) | 1500 [1200;1950] | 1500 [1125;1950] | 1800 [1350;2025] | <0.001 | 0.311 | 0.934 | <0.001 | <0.001 | <0.001 | <0.001 |
Dosing days of Gn (day) | 8.00 [7.00;10.0] | 9.00 [7.00;10.0] | 8.00 [7.00;10.0] | 0.330 | ||||||
E2 on trigger day (pg/mL) | 518 [355;776] | 510 [334;728] | 607 [388;956] | <0.001 | 0.119 | 0.354 | <0.001 | <0.001 | <0.001 | <0.001 |
LH on trigger day (IU/L) | 3.00 [1.88;4.81] | 3.25 [2.06;4.70] | 2.91 [1.77;4.34] | 0.029 | 0.090 | 0.271 | 0.092 | 0.276 | 0.004 | 0.011 |
P on trigger day (ng/mL) | 0.20 [0.12;0.31] | 0.19 [0.12;0.29] | 0.19 [0.10;0.30] | 0.034 | 0.050 | 0.149 | 0.005 | 0.015 | 0.178 | 0.533 |
Oocyte not obtained rate, n (%) | 12 (2.73%) | 22 (5.01%) | 13 (2.96%) | 0.134 | ||||||
Number of oocytes retrieved | 2.00 [1.00;4.00] | 2.00 [1.00;3.00] | 3.00 [2.00;4.00] | <0.001 | 0.020 | 0.061 | <0.001 | <0.001 | <0.001 | <0.001 |
Fertilization*, n (%) | 0.162 | |||||||||
IVF | 304 (72.0%) | 278 (67.8%) | 277 (66.1%) | |||||||
ICSI or rescue icsi | 118 (28.0%) | 132 (32.2%) | 142 (33.9%) | |||||||
Number of normally fertilized embryos* | 2.00 [1.00;3.00] | 2.00 [1.00;2.00] | 2.00 [1.00;3.00] | <0.001 | 0.392 | 1.000 | <0.001 | <0.001 | <0.001 | <0.001 |
Number of cleavages in normally fertilized embryos* | 2.00 [1.00;2.00] | 2.00 [1.00;2.00] | 2.00 [1.00;3.00] | <0.001 | 0.493 | 1.000 | <0.001 | <0.001 | <0.001 | <0.001 |
Number of high-quality embryos on day 3* | 0.00 [0.00;1.00] | 0.00 [0.00;1.00] | 1.00 [0.00;1.00] | 0.021 | 0.449 | 1.000 | 0.007 | 0.020 | 0.010 | 0.029 |
number of available embryos* | 1.00 [1.00;2.00] | 1.00 [1.00;2.00] | 2.00 [1.00;2.00] | 0.004 | 0.239 | 0.717 | <0.001 | 0.002 | 0.007 | 0.020 |
Normal fertilization rate*, n (%) | 813 (68.4%) | 754 (70.3%) | 960 (67.2%) | 0.267 | ||||||
Normal cleavage rate*, n (%) | 790 (97.2%) | 740 (98.1%) | 944(98.3%) | 0.202 | ||||||
high-quality embryos on day 3 rate*, n (%) | 266 (33.7%) | 255 (34.5%) | 321(34.0%) | 0.948 | ||||||
Available embryos formation rate*, n (%) | 564 (71.4%) | 564 (76.2%) | 652 (69.1%) | 0.005 | 0.037 | 0.111 | 0.317 | 0.951 | 0.001 | 0.004 |
unusable embryos rate*, n (%) | 103 (24.4%) | 79 (19.3%) | 83 (19.8%) | 0.135 | ||||||
| Notes: Numerical variables that follow a normal distribution are reported as mean (standard deviation), numerical variables that do not follow a normal distribution are reported as median [interquartile range], and categorical variables are reported as numbers (percentage). | ||||||||||
| Continuous variables are analyzed using the Kruskal-Wallis test, with Dunn’s test (the p-values were adjusted using the bonferroni method.) used for post hoc pairwise analysis when Kruskal-Wallis results were significant. Categorical variables are analyzed using the chi-square test or Fisher's test, with chi-square test or Fisher’s exact test (the p-values were adjusted using the bonferroni method.) used for post hoc pairwise analysis when chi-square test or Fisher’s exact test results were significant. | ||||||||||
| * Some patients were excluded from the statistical analysis of the variables marked with * due to egg freezing, poor egg quality resulting in no fertilization procedure, or failure to retrieve eggs. Therefore, for these variables marked with *, in the control group, the sample size (n) was 422; in the kuntai group, the sample size (n) was 410; in the GH group, the sample size (n) was 419. | ||||||||||
| Abbreviations: PSM, propensity score matching; GN, gonadotropins; E2, estradiol; LH, luteinizing hormone; P, Progesterone; IVF, in vitro fertilization; ICSI, intracytoplasmic sperm injection; GH, growth hormone. | ||||||||||
Oocyte yield was significantly greater in the GH group (3.00 [2.00–4.00]) than in both the control (2.00 [1.00–4.00], adjusted p < 0.001) and Kuntai groups (2.00 [1.00–3.00], adjusted p < 0.001). This advantage extended to subsequent embryological milestones. The GH group yielded more normally fertilized oocytes (2.00 [1.00–3.00]) than the Kuntai group (2.00 [1.00–2.00], adjusted p < 0.001), a greater number of cleaved embryos (2.00 [1.00–3.00] vs. 2.00 [1.00–2.00] in both other groups; adjusted p < 0.001), and more available embryos (2.00 [1.00–2.00]) than the control group (1.00 [1.00–2.00], adjusted p = 0.002). The rate of available embryo formation was also higher in the GH group (69.1%) compared to the Kuntai group (76.2%, adjusted p = 0.004), despite comparable high-quality embryo rates across all groups (p = 0.948).
Conversely, the Kuntai group showed limited improvement over the control group. The only notable difference was a lower unusable embryo rate (19.3% vs. 24.4%, unadjusted p = 0.037), which, however, was not statistically significant after Bonferroni adjustment (adjusted p = 0.111).
Pregnancy and Live Birth Outcomes Following FET
Endometrial thickness and the developmental stage of transferred embryos were similar across groups (p > 0.05). However, the distribution of endometrial preparation protocols differed significantly (p = 0.002), with the Kuntai group employing artificial cycles more frequently (33.3%) than the control group (22.1%, adjusted p = 0.046, Table 3).
Control group (n = 249)* | Kuntai group (n = 240) * | GH group (n = 238)* | p | Control VS kuntai | Control VS GH | Kuntai VS GH | ||||
|---|---|---|---|---|---|---|---|---|---|---|
p (unadj) | p (adj) | p (unadj) | p (adj) | p (unadj) | p (adj) | |||||
Endometrial preparation protocol, n (%) | 0.002 | 0.015 | 0.046 | 0.108 | 0.325 | 0.004 | 0.012 | |||
Artificial cycle | 55 (22.1%) | 80 (33.3%) | 58 (24.4%) | |||||||
Downregulated artificial cycle | 159 (63.9%) | 124 (51.7%) | 161 (67.6%) | |||||||
Other ** | 35 (14.1%) | 36 (15.0%) | 19 (7.98%) | |||||||
Endometrial thickness (mm) | 9.20 [8.30, 10.7] | 9.20 [8.17, 10.4] | 9.20 [8.40, 10.3] | 0.865 | ||||||
No. of embryos transferred | 2.00 [2.00;2.00] | 2.00 [1.00;2.00] | 2.00 [2.00;2.00] | 0.004 | 0.001 | 0.003 | 0.370 | 1.000 | 0.003 | 0.009 |
Stage of embryos transferred, n (%) | 0.226 | |||||||||
Cleavage | 215 (86.3%) | 194 (80.8%) | 195 (81.9%) | |||||||
Other *** | 34 (13.7%) | 46 (19.2%) | 43 (18.1%) | |||||||
Biochemical pregnancy rate, n (%) | 142 (57.3%) | 128 (53.3%) | 159 (67.4%) | 0.006 | 0.435 | 1.000 | 0.028 | 0.083 | 0.002 | 0.007 |
Implantation rate, n (%) | 132 (29.0%) | 128 (31.4%) | 127 (29.7%) | 0.744 | ||||||
Clinical pregnancy rate, n (%) | 110 (44.5%) | 110 (45.8%) | 107 (45.7%) | 0.950 | ||||||
Pregnancy loss rate, n (%) | 26 (28.9%) | 27 (31.8%) | 21 (26.9%) | 0.791 | ||||||
Live birth rate, n (%) | 64 (28.2%) | 58 (27.0%) | 57 (27.8%) | 0.959 | ||||||
| Notes: Numerical variables that follow a normal distribution are reported as mean (standard deviation), numerical variables that do not follow a normal distribution are reported as median [interquartile range], and categorical variables are reported as numbers (percentage). | ||||||||||
| Continuous variables are analyzed using the Kruskal-Wallis test, with Dunn’s test (the p-values were adjusted using the bonferroni method.) used for post hoc pairwise analysis when Kruskal-Wallis results were significant. Categorical variables are analyzed using the chi-square test or Fisher's test, with chi-square test or Fisher’s exact test (the p-values were adjusted using the bonferroni method.) used for post hoc pairwise analysis when chi-square test or Fisher’s exact test results were significant. | ||||||||||
| * The total count is based on the number of thawing cycles, with some patients having a second thawing cycle. | ||||||||||
| ** We grouped natural cycles and ovulation induction cycles into an 'Other' category because their individual frequencies were too low for separate analysis. | ||||||||||
| *** We grouped D5, D6, and sequential embryo transfer (initial transfer of a day3 embryos followed by a day-5/6 blastocyst transfer after 48 hours) into an 'Other' category because their individual frequencies were too low for separate analysis. | ||||||||||
| Abbreviations: PSM, propensity score matching. | ||||||||||
A significant inter-group difference was observed in the biochemical pregnancy rate (p = 0.006). The GH group achieved a higher rate (67.4%) than both the control (57.3%, unadjusted p = 0.028) and Kuntai groups (53.3%, adjusted p = 0.007). Nevertheless, this early advantage did not persist. Clinical pregnancy rates (control: 44.5%, Kuntai: 45.8%, GH: 45.7%; p = 0.950) and live birth rates (control: 28.2%, Kuntai: 27.0%, GH: 27.8%; p = 0.959) were statistically indistinguishable. Pregnancy loss rates were also comparable, ranging from 27% to 32% (p = 0.791).
A slight but significant difference was noted in the number of embryos transferred (p = 0.004), with the Kuntai group more frequently receiving a single embryo (median [IQR]: 2.00 [1.00;2.00]) compared to the control group (2.00 [2.00;2.00], adjusted p = 0.003). Despite this, implantation rates remained consistent across groups (29.0% to 31.4%, p = 0.744). Key laboratory and clinical outcomes are visually summarized in Fig. 2 for direct comparison.
Fig. 2
Comparison of Selected Laboratory and Clinical Outcomes Among Control, Kuntai, and GH Groups after Propensity Score Matching.
Multivariate Analysis Using GEE Models
GEE models, adjusting for confounders, confirmed the null effect of the adjuvants on key outcomes (Table 4). Compared to the control group, neither the Kuntai capsule (adjusted OR 0.77, 95% CI 0.53–1.12; p = 0.176) nor GH pretreatment (adjusted OR 1.40, 95% CI 0.95–2.06; p = 0.090) was associated with a statistically significant change in the odds of biochemical pregnancy. Similarly, no significant treatment effects were identified for clinical pregnancy (Kuntai: adjusted OR 0.99, 95% CI 0.68–1.44; GH: adjusted OR 0.93, 95% CI 0.63–1.36) or live birth (Kuntai: adjusted OR 0.90, 95% CI 0.58–1.39; GH: adjusted OR 0.85, 95% CI 0.54–1.33).
Biochemical pregnancy | Clinical pregnancy | Live birth | ||||
|---|---|---|---|---|---|---|
Adjusted odds ratio (95% CI) | p | Adjusted odds ratio (95% CI) | p | Adjusted odds ratio (95% CI) | p | |
Treatment | ||||||
Control (reference) | ||||||
kuntai | 0.77 (0.53, 1.12) | 0.176 | 0.99 (0.68, 1.44) | 0.942 | 0.90 (0.58, 1.39) | 0.636 |
GH | 1.40 (0.95, 2.06) | 0.09 | 0.93 (0.63, 1.36) | 0.691 | 0.85 (0.54, 1.33) | 0.480 |
Age (year) | ||||||
<35 (reference) | ||||||
35–37 | 1.25 (0.79, 1.98) | 0.333 | 0.89 (0.58, 1.36) | 0.584 | 0.91 (0.57, 1.47) | 0.70 |
>37 | 0.54 (0.38, 0.76) | 0.000 | 0.42 (0.30, 0.60) | 0.000 | 0.36 (0.23 0.55) | 0.000 |
BMI (kg/m2) | ||||||
<18.5 (reference) | ||||||
18.5–24 | 1.59 (0.88, 2.85) | 0.124 | 1.80 (1.00, 3.25) | 0.052 | 2.28 (1.03, 5.04) | 0.043 |
>24 | 1.71 (0.89, 3.27) | 0.104 | 2.11 (1.11, 4.04) | 0.024 | 2.56 (1.09, 6.01) | 0.032 |
Endometrial preparation protocol | ||||||
Artificial cycle (reference) | ||||||
Downregulated artificial cycle | 1.35 (0.93, 1.95) | 0.111 | 1.45 (1.00, 2.08) | 0.047 | 1.15 (0.76, 1.74) | 0.505 |
Other * | 0.90 (0.53, 1.53) | 0.695 | 0.75 (0.43, 1.32) | 0.322 | 0.80 (0.41, 1.57) | 0.520 |
Reason | ||||||
Tubal factor (reference) | ||||||
Male factor | 0.69 (0.46, 1.06) | 0.088 | 0.62 (0.40 0.94) | 0.023 | 0.73 (0.44, 1.20) | 0.213 |
Other factor ** | 0.88 (0.62, 1.26) | 0.483 | 0.75 (0.52, 1.06) | 0.099 | 0.87 (0.58 1.29) | 0.480 |
No. of embryos transferred | 1.07 (0.70, 1.64) | 0.75 | 1.08 (0.73, 1.61) | 0.688 | 1.49 (0.99, 2.23) | 0.005 |
Phase of embryo transferred (D3 vs. Other) *** | 3.53 (1.91, 6.50) | 0.000 | 2.34 (1.37, 4.00) | 0.002 | 1.75 (0.96, 3.16) | 0.066 |
| Notes: * Other endometrial preparation protocol includes natural cycles and ovulation induction cycles. ** Other infertility factors include ovulation disorders, endometriosis, uterine factors, and so on. *** Other phase of embryo transferred include D5, D6, and sequential embryo transfer (initial transfer of a day3 embryos followed by a day-5/6 blastocyst transfer after 48 hours). | ||||||
Patient age emerged as a powerful, independent predictor of success. Women over 37 years of age had substantially reduced odds of achieving a biochemical pregnancy (adjusted OR 0.54, 95% CI 0.38–0.76; p < 0.001), clinical pregnancy (adjusted OR 0.42, 95% CI 0.30–0.60; p < 0.001), and live birth (adjusted OR 0.36, 95% CI 0.23–0.55; p < 0.001) compared to their counterparts under 35 years. Body mass index (BMI) also showed a significant association. Patients with a BMI > 24 kg/m² had higher odds of clinical pregnancy (adjusted OR 2.11, 95% CI 1.11–4.04; p = 0.024) and live birth (adjusted OR 2.56, 95% CI 1.09–6.01; p = 0.032) compared to underweight women (BMI < 18.5 kg/m²). Furthermore, the use of a down-regulated artificial cycle protocol was associated with improved clinical pregnancy rates relative to the standard artificial cycle (adjusted OR 1.45, 95% CI 1.00-2.08; p = 0.047).
Discussion
This large, matched-cohort study yields two pivotal findings that challenge routine clinical practice: first, GH supplementation enhances quantitative ovarian response metrics but fails to improve live birth rates; second, Kuntai capsule pretreatment demonstrates no measurable benefit across the entire spectrum of ovarian and reproductive outcomes. For DOR patients managed with a PPOS and freeze-all strategy, our data do not support the empirical use of either adjuvant to increase the chances of achieving a live birth.
The most salient finding was the clear dissociation between GH's effects on the stimulation phase and the final treatment outcome. GH significantly augmented ovarian responsiveness, evidenced by higher E₂ levels(607 vs 518 pg/mL, p < 0.001), oocyte yield(3 vs 2, p < 0.001), and embryo numbers—an endocrine and laboratory profile suggesting improved follicular recruitment and function. This endocrine profile - characterized by elevated E2 with appropriately suppressed LH and progesterone levels - suggests GH may optimize follicular microenvironment by enhancing granulosa cell function while preventing premature luteinization. These findings are consistent with the existing literature suggesting that growth hormone may enhance granulosa cell sensitivity and responsiveness to gonadotropin or growth hormone stimulation, thereby modulating sex steroid synthesis and follicular development, and improve oocyte quality, embryo competence (19, 20). However, the critical observation is that this early advantage, including a higher biochemical pregnancy rate, did not propagate into improved clinical pregnancy or live birth. Our multivariate GEE model solidly confirmed that GH was not an independent predictor of these ultimate success measures (live birth adjusted OR 0.85, p = 0.48).
Several factors contribute to the ongoing controversy regarding GH's efficacy on clinical pregnancy and live birth outcomes(21–24). First, substantial variations exist in GH administration protocols, including differences in treatment initiation (ranging from during ovarian stimulation to 2–6 weeks pretreatment) and dosage (2-7.5 IU vs. 12–24 IU)(25). Second, the use of different COS protocols (GnRH antagonist vs. agonist regimens) may lead to inconsistent responses(16). A compelling hypothesis, particularly relevant to our study design, is that GH's primary mechanism may be endometrial rather than follicular(26). A freeze-all strategy, by physically separating the stimulated cycle from the embryo transfer, effectively negates any potential endometrial benefit of GH, leaving only its modest ovarian effects which appear insufficient to influence the ultimate outcome of live birth. Additionally, GH's efficacy is age-dependent, yielding significant improvements in embryo quality and live birth rates exclusively in DOR patients aged 35–40 years, with no comparable effects observed in younger (< 35) or older (> 40) patients(27). Thus, within a freeze-all paradigm, the modest ovarian effects of GH appear insufficient to overcome the primary barrier of oocyte quality in DOR, which is predominantly age-driven.
A
Contrary to our initial hypothesis and some previous reports, Kuntai capsule pretreatment demonstrated a notable absence of reproductive benefits in our cohort. We observed no significant enhancement in ovarian responsiveness (trigger-day E₂: 510 [334;728] vs control 518 [355;776] IU/L, adjusted p = 0.354), oocyte yield (2.00 [1.00–3.00] vs 2.00 [1.00–4.00], adjusted p = 0.061), or embryo quality (high-quality embryo rate: 34.5% vs 33.7%, p = 0.948). Most critically, we detected no improvement in the ultimate endpoints of clinical pregnancy (45.8% vs 44.5%, p = 0.950) or live birth (27.0% vs 28.2%, p = 0.959). The GEE model corroborated these findings, indicating that Kuntai was not an independent factor influencing clinical pregnancy (adjusted OR 0.99, 95% CI 0.68–1.44, p = 0.942) or live birth (adjusted OR 0.90, 95% CI 0.58–1.39, p = 0.636). The existing evidence base for Kuntai in improving IVF/ICSI outcomes for DOR is limited and appears context-dependent. Previous reports(8, 11, 12), including two randomized controlled trials (RCT)(12, 13), have suggested that Kuntai capsule may improve ovarian response and clinical outcomes in DOR patients. However, these studies differed fundamentally from our design: they enrolled smaller cohorts (n = 108 and n = 70), administered pretreatment over three menstrual cycles, and exclusively employed fresh embryo transfer protocols. The disparity in outcomes underscores that any potential benefits of Kuntai may be negated within the specific framework of a PPOS-freeze-all strategy.Beyond the interventions, our regression analysis underscores the dominant role of patient-specific factors. The profound negative impact of advanced maternal age (> 37 years) on live birth (adjusted OR 0.36, p < 0.001) reiterates the irreversible influence of chronological age on oocyte competence in DOR patients(28–30). While previous studies have predominantly emphasized the reproductive risks associated with overweight BMI(31, 32), our analysis revealed a more nuanced relationship. Surprisingly, patients with ultra-low BMI (< 18.5 kg/m²) demonstrated the poorest outcomes, showing significantly lower live birth rates compared to both normal-weight (adjust OR 2.28, 95% CI 1.03–5.04, p = 0.043) and overweight groups (adjust OR 2.56, 95% CI 1.09–6.01, p = 0.032). This pattern held consistently across clinical pregnancy rates (BMI 18.5–24: adjust OR 1.80, p = 0.052; BMI > 24: adjust OR 2.11, p = 0.024) and biochemical pregnancy outcomes. Notably, the detrimental effects of low BMI exceeded those of overweight status across all reproductive endpoints.
The limitations of our study, including its retrospective design and single-center nature, necessitate validation through prospective, multicenter trials. Furthermore, the sample size, while large overall, was insufficient for robust, age-stratified subgroup analyses. Future research should prioritize prospective designs that can further elucidate the role of these and other adjuvants within specific DOR subpopulations and treatment protocols.
In summary, this retrospective study supports the following hypotheses regarding DOR patients undergoing PPOS protocol with freeze-all IVF/ICSI-FET cycles: (1) GH pretreatment demonstrates the capacity to enhance ovarian responsiveness, increase oocyte yield, and improve embryo quality, yet fails to translate these advantages into superior clinical pregnancy or live birth rates; (2) Kuntai capsule pretreatment shows no beneficial effects on ovarian response, oocyte retrieval, embryo quality, or ultimate reproductive outcomes.
Fig. 1
Patient screening, grouping, and analysis flowchart.
Before matching | After matching | |||||||
|---|---|---|---|---|---|---|---|---|
Control group (n = 1665) | Kuntai group (n = 524) | GH group (n = 778) | p | Control group (n = 439) | Kuntai group (n = 439) | GH group (n = 439) | p | |
Age(years) | 37.0 [32.0, 41.0] | 36.0 [32.0, 40.0] | 37.0 [33.0, 40.0] | 0.151 | 36.0 [32.0, 40.0] | 36.0 [32.0, 40.0] | 36.0 [32.0, 39.0] | 0.955 |
BMI (kg/m2) | 22.0 [20.3, 24.2] | 22.0 [20.3, 24.0] | 22.0 [20.0, 23.8] | 0.260 | 22.2 [20.4, 24.1] | 22.2 [20.3, 24.0] | 22.2 [20.1, 24.0] | 0.950 |
Basic FSH (IU/L) | 8.28 [6.43, 11.2] | 9.02 [6.78, 12.3] | 8.09 [6.36, 10.7] | <0.001 | 8.58 [6.62, 11.6] | 8.64 [6.64, 11.7] | 8.58 [6.86, 11.2] | 0.963 |
Basic E2 (pg/ml) | 34.0 [24.5, 49.0] | 34.7 [24.3, 51.3] | 37.0 [26.6, 52.2] | 0.001 | 36.1 [27.0, 50.2] | 35.2 [24.2, 51.5] | 36.0 [26.4, 50.8] | 0.544 |
Basic LH (IU/L) | 3.70 [2.58, 5.29] | 4.17 [2.97, 5.80] | 3.82 [2.67, 5.26] | <0.001 | 3.94 [2.70, 5.42] | 4.06 [2.89 5.57] | 3.91 [2.80, 5.46] | 0.643 |
AMH (ug/L) | 0.60 [0.37, 0.87] | 0.55 [0.30, 0.81] | 0.68 [0.44, 0.97] | <0.001 | 0.56 [0.35, 0.78] | 0.57 [0.31, 0.81] | 0.57 [0.34, 0.85] | 0.338 |
AFC | 4.00 [3.00, 5.00] | 4.00 [3.00, 5.25] | 4.00 [3.00, 6.00] | 0.001 | 4.00 [3.00, 5.00] | 4.00 [3.00, 5.50] | 4.00 [3.00, 6.00] | 0.320 |
Infertility duration (years) | 3.00 [2.00, 6.00] | 3.00 [2.00, 6.00] | 4.00 [2.00, 6.00] | 0.037 | 4.00 [2.00, 6.00] | 3.00 [2.00, 6.00] | 4.00 [2.00, 6.00] | 0.632 |
Infertility type, n (%) | 0.021 | 0.936 | ||||||
Second | 1131 (67.9%) | 349 (66.6%) | 567 (72.9%) | 301 (68.6%) | 299 (68.1%) | 296(67.4%) | ||
Primary | 534 (32.1%) | 175 (33.4%) | 211 (27.1%) | 138 (31.4%) | 140 (31.9%) | 143 (32.6%) | ||
Infertility factors, n (%) | <0.001 | 0.770 | ||||||
Tubal factor | 555 (33.3%) | 161 (30.7%) | 272 (35.0%) | 144 (32.8%) | 142 (32.3%) | 136 (31.0%) | ||
Male factor | 415 (24.9%) | 124 (23.7%) | 240 (30.8%) | 107 (24.4%) | 103 (23.5%) | 96(21.9%) | ||
other | 695 (41.7%) | 239 (45.6%) | 266 (34.2%) | 188 (42.8.%) | 194 (44.2%) | 207(47.2%) | ||
| Notes: Numerical variables that follow a normal distribution are reported as mean (standard deviation), numerical variables that do not follow a normal distribution are reported as median [interquartile range], and categorical variables are reported as numbers (percentage). Continuous variables are analyzed using the Kruskal-Wallis test, while categorical variables are analyzed using the chi-square test or Fisher's test. | ||||||||
Other infertility factors include ovulation disorders, endometriosis, uterine factors, and so on.
Abbreviations: PSM, propensity score matching; BMI, body mass index; FSH, follicle stimulating hormone; E2, estradiol; LH, luteinizing hormone; AMH, anti-Müllerian hormone; AFC, antral follicle count; GH, growth hormone.
Declarations
Ethics statement
A
The reproductive medicine ethics committee of Jiangxi Maternal and Child Health Hospital approved this study (SZYY-202504).Clinical trial number
not applicable.
Consent for publication
Not applicable.
A
Data Availability
No datasets were generated or analysed during the current study.
Competing interests
The authors declare that they have no conflicts of interest.
A
Funding
This work was supported by the Scientific Research Project of the Jiangxi Provincial Health Commission (No. 202211108) and the Science and Technology Plan of Jiangxi Provincial Administration of Traditional Chinese Medicine (No. 2022B272).
A
A
Author Contribution
XW conceived and designed the study. MY and XW supervised the study and analyzed the data. ZH performed the data analysis with the help of JT and HYX, and XW wrote the manuscript. All the authors revised and approved the final manuscript.
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