Abstract
Objective: To investigate the efficacy and safety of dydrogesterone and progesterone in the treatment of threatened miscarriage due to corpus luteum insufficiency. Methods: A prospective cohort study was designed and a total of 1,285 patients with threatened miscarriage due to corpus luteum insufficiency were recruited, in which 665 participants received dydrogesterone treatment (dydrogesterone group), and the other 620 received progesterone treatment (progesterone group). The time for clinical symptom relief, changes of sex hormone levels in serum, the rate of miscarriage prevention, delivery outcome, and adverse effects were compared between the two groups. XGBoost algorithm was applied to analyze the factors impacting the efficacy and safety of each treatment. Results: There was no significant difference regarding the time for clinical symptom relief and the rate of miscarriage prevention between the two groups (P>0.05, RR=1.01, 95% CI: 0.97-1.06, P=0.566). However, after 4 weeks of treatment, compared with the progesterone group, the level of sex hormones was significantly upregulated, while the preterm birth rate (9.65% vs. 14.04%), the postpartum hemorrhage rate (3.10% vs. 5.62%), and the incidence of adverse effects (17.44% vs. 32.58%) were considerably reduced in the dydrogesterone group (all P<0.05). XGBoost algorithm analysis demonstrated that dydrogesterone treatment was correlated with a lower incidence of preterm birth rate, postpartum hemorrhage, and adverse effects, ranking the 3rd, 2nd and 1st, respectively, in the weight of dependent variables. Conclusion: Compared with progesterone, dydrogesterone can improve the delivery outcome and demonstrate a higher safety in the treatment of threatened miscarriage due to corpus luteum insufficiency.
Keywords: Threatened miscarriage, dydrogesterone, progesterone, efficacy, XGBoost, influencing factors
Introduction
Threatened miscarriage is a common disease during early pregnancy, with a morbidity of 30% to 40%, which could develop into a complete miscarriage or dystocia without timely treatment [1]. Many pathogenic factors contribute to the threatened miscarriage, of which lacking progestogens due to the endocrine dysfunction of corpus luteum is one of the main culprits [2,3]. Therefore, supplementation of progestogens is a primary therapeutic strategy for the treatment of threatened miscarriage due to corpus luteum insufficiency, among which progesterone and dydrogesterone are the leading medications in clinical practice [3-6]. Progesterone is an endogenous progestogen sex hormone secreted by the corpus luteum. Supplementation of progesterone is a direct way to elevate progesterone levels caused by insufficient corpus luteum secretion, which is involved in the treatment of threatened miscarriage [7]. Dydrogesterone is an analog of the progestogen, which is highly similar to endogenous progesterone in terms of the structure, function, and biological characteristics [5]. In recent years, dydrogesterone has been widely used in the treatment of threatened miscarriage and assisted reproductive technology, showing promising outcomes [8].
However, currently, golden standard for the pharmaceutical dosage and the treatment course of dydrogesterone is not available in clinical practice. On the other hand, an accurate methodology for the judgment of luteal function is absent. So far, there is still a lack of high-quality and evidence-based research regarding the clinical efficacy and safety of dydrogesterone treatment [5,8]. In addition, there are few studies reporting the safety of dydrogesterone in the treatment of threatened miscarriage due to corpus luteum insufficiency [9,10]. XGBoost algorithm is an extended variant of boosting, which can be used as an effective prediction model for uneven data sets and is able to process highly diversified descriptors and complex feature spaces [11,12]. In this study, we designed a prospective cohort study to compare the effect of droprogesterone and progesterone in the treatment of threatened miscarriage due to corpus luteum insufficiency, applied the machine learning XGBoost algorithm to analyze the clinical data of 1,285 patients, and established a model to accurately evaluate the safety and efficacy of dydrogesterone in the treatment of threatened miscarriage.
Materials and methods
Patients
A total of 1,285 patients treated in the outpatient of the Sixth People’s Hospital of Zhuji from January 2013 to December 2017 with threatened miscarriage due to corpus luteum insufficiency were recruited in this study. Among them, 665 received dydrogesterone treatment (dydrogesterone group), and 620 received progesterone treatment (progesterone group). Inclusion criteria: ① Patients showed symptoms of early pregnancy, which was confirmed by B-ultrasound, urine hCG test, and history of menopause. ② The gestational week was between the 6th to 10th week. ③ Patients were diagnosed with threatened miscarriage due to corpus luteum insufficiency [13]. ④ Patients were administered dydrogesterone or progesterone soft capsules. Exclusion criteria: ① Patients were diagnosed with ectopic pregnancy. ② Patients were combined with severe heart, liver, lung, kidney, and other organ disorders. ③ Patients had a history of recurrent miscarriage. ④ Patients were allergic to the target drug. ⑤ Patients and their family members were not willing to prevent the miscarriage. ⑥ Patients had poor treatment compliance or incomplete clinical data.
Ethics statement
This study complied with the Declaration of Helsinki and was approved by the Ethics Committee of the Sixth People’s Hospital of Zhuji. All patients were informed and signed the consent form.
Treatment methods
Dydrogesterone group was treated with Dydrogesterone tablets (Abbott Healthcare, Netherlands). The first oral dose was 40 mg, and the subsequent oral dose was 10 mg/time, 3 times/day, 2 weeks as a course of treatment. Except for patients whose pregnancy was terminated, the rest patients were treated till 12 weeks of gestation.
Progesterone group was treated with progesterone soft capsules (Zhejiang Pharmaceutical Co., Ltd., China) orally, 0.1 g/time, 2 times/day, 2 weeks as a course of treatment. Except for patients whose pregnancy was terminated, the rest were treated till 12 weeks of gestation.
Measurements of sex hormone levels
Before treatment and 4 weeks after treatment, 4 mL of fasting peripheral venous blood was collected from the patients in two groups in the early morning, followed by centrifugation for 15 min (3,000 r/min) to isolate the supernatant for testing. Electrochemiluminescence (ECL) method was applied to quantify the levels of estradiol (E2), human chorionic gonadotropin (HCG), and progesterone (P). E2, HCG, and P kits were purchased from Wuhan Mingde Biotechnology Co., Ltd., China.
Follow-up
All patients were followed up till the end of gestation. The adverse effects during the treatment were recorded, and patients’ gestation and delivery outcome, including the gestational week of delivery, delivery method, and complications during delivery were also recorded.
Evaluation criteria
① Successful miscarriage prevention: gestation ≥28 weeks was considered as successful, and less than 28 weeks or no gestational week information was regarded as unsuccessful. ② Preterm birth: gestation ≥28 weeks, but less than 37 weeks was considered as preterm birth [14].
XGBoost algorithm analysis
Establishment of XGBoost algorithm analysis database
① Data collection: the clinical data of 1,285 patients with threatened miscarriage due to corpus luteum insufficiency were collected, including the patients’ general information, testing data, and medication data. ② Establishment of the database: the above data were filtered and preprocessed to create an XGBoost analysis database.
Variable system set-up
Target variables and condition variables were set up. Target variables include the success rate of miscarriage prevention, preterm birth, postpartum hemorrhage, and the incidence of adverse effects. Condition variables include indicators such as general information of the patients, pregnancy information, medication regimen, combined medication, and testing information.
XGBoost algorithm was adopted to establish an evaluation model for the safety and efficacy of dydrogesterone in the treatment of threatened miscarriage
① The above two types of data were imported, respectively. ② All discontinuous variables were processed to reduce the dimensionality via principal component analysis (PCA) and other methods to preliminarily filter important variables. ③ Different parameter combinations were iterated and tested using grid search method to refine the important factors for endpoints. ④ Finally, the data were extracted, constructed via decision tree, and processed by correlation analysis to establish an evaluation model for the safety and efficacy of dydrogesterone in the treatment of miscarriage.
Outcome measurements
The primary outcome measurements included the success rate of miscarriage prevention, delivery outcome, incidence of adverse effects, and the results of XGBoost analysis in the two groups. The secondary outcome measurements included the time for clinical symptom relief in the two groups and serum sex hormone levels before and after treatment.
Statistical analysis
SPSS 23.0 (SPSS, Inc., Chicago, IL, USA) software was applied for the statistical analysis. The count data were presented as the number (n, %) and analyzed by χ2 test. The quantitative data with normal distribution were presented as mean ± standard deviation (x̅ ± sd). The comparison between the two groups was conducted by independent sample t-test, while the comparison before and after treatment within the same group was carried out by paired t-test. The significance level was defined by two-sided α=0.05. P<0.05 indicated the statistically significant difference.
Results
General information of the two groups of patients
A total of 1,285 patients with threatened miscarriage due to corpus luteum insufficiency were recruited in this study, of which 665 patients received dydrogesterone treatment as dydrogesterone group, and the other 620 patients were given progesterone soft capsules as progesterone group. There was no significant difference in terms of age, gestational week, parity, pregnant times, number of single births, proportion of habitual abortion history, and number of cases of hypertension during pregnancy between the two groups of patients (P>0.05, Table 1).
Table 1.
Comparison of general information of the two groups of patients
| Category | Dydrogesterone group (n=665) | Progesterone group (n=620) | χ2/t | P |
|---|---|---|---|---|
| Age (x̅ ± sd, years) | 27.6±5.6 | 28.0±5.8 | 1.256 | 0.209 |
| Gestational weeks (x̅ ± sd, weeks) | 8.1±1.4 | 8.2±1.5 | 1.233 | 0.218 |
| Parity (n (%)) | 2.724 | 0.256 | ||
| ≤1 | 302 (45.41) | 310 (50.00) | ||
| 2 | 223 (33.53) | 192 (30.97) | ||
| ≥3 | 140 (21.05) | 118 (19.03) | ||
| Pregnant times (n (%)) | 0.957 | 0.620 | ||
| ≤1 | 125 (18.80) | 130 (20.97) | ||
| 2 | 442 (66.47) | 402 (64.84) | ||
| ≥3 | 98 (14.74) | 88 (14.19) | ||
| Number of single birth (n (%)) | 505 (75.94) | 483 (77.90) | 0.696 | 0.404 |
| Hypertension during pregnancy (n (%)) | 85 (12.78) | 72 (11.61) | 0.409 | 0.523 |
Efficacy
The clinical symptoms of the two groups of patients were significantly improved after receiving dydrogesterone or progesterone treatment for about 4 days. There was no significant difference in terms of time for low-back pain relief, time for abdominal pain relief, and hemostasis time between the two groups (P>0.05, Table 2). After 4 weeks of treatment, the levels of serum sex hormones were significantly increased in the two groups as compared with those before treatment (P<0.001). Of note, the levels of HCG, E2, and P were significantly higher in the dydrogesterone group than those of the progesterone group (P<0.05, Figure 1).
Table 2.
Relief time of clinical symptoms in the two groups of patients
| Group | Case | Time for low-back pain relief (d) | Time for abdominal pain relief (d) | Hemostasis time (d) |
|---|---|---|---|---|
| Dydrogesterone group | 665 | 4.15±1.20 | 3.83±1.32 | 3.79±1.06 |
| Progesterone group | 620 | 4.20±1.37 | 3.92±1.41 | 3.87±1.21 |
| t | 0.694 | 1.179 | 1.257 | |
| P | 0.488 | 0.239 | 0.209 |
Figure 1.
Serum sex hormone levels before and 4 weeks after treatment in the two groups of patients. A: Human chorionic gonadotropin (HCG) level; B: Estradiol (E2) level; C: Progesterone (P) level. Compared with before treatment, ***P<0.001; compared with the progesterone group, #P<0.05, ##P<0.01, ###P<0.001. E2: estradiol; HCG: human chorionic gonadotropin.
The success rate of miscarriage prevention and delivery outcome in the two groups of patients
Among the 665 patients in the dydrogesterone group, miscarriage was successfully prevented in 580 cases while 85 cases failed, with a success rate of 87.22%. Among the 620 patients in the progesterone group, miscarriage was successfully prevented in 534 cases while 86 cases failed, with a success rate of 86.13%. There was no significant difference regarding the rate of miscarriage prevention between the two groups of patients (RR=1.01, 95% CI: 0.97-1.06, P=0.566). Compared with the progesterone group, the preterm birth rate (9.65% vs. 14.04%) and postpartum hemorrhage rate (3.10% vs. 5.62%) were significantly lower in the dydrogesterone group. However, there was no significant difference in terms of the occurrence of placenta previa, placental adhesion, and premature rupture of fetal membranes between the two groups of patients (P>0.05, Table 3).
Table 3.
Comparison of delivery outcomes between the two groups of patients (n, %)
| Category | Dydrogesterone group (n=580) | Progesterone group (n=534) | χ2 | P |
|---|---|---|---|---|
| Preterm birth | 56 (9.66) | 75 (14.04) | 5.163 | 0.023 |
| Complications during delivery | ||||
| Postpartum hemorrhage | 18 (3.10) | 30 (5.62) | 4.264 | 0.039 |
| Placenta previa | 9 (1.55) | 13 (2.43) | 1.119 | 0.290 |
| Placental adhesion | 6 (1.03) | 10 (1.87) | 1.380 | 0.240 |
| Premature rupture of fetal membranes | 28 (4.83) | 35 (6.55) | 1.554 | 0.213 |
Safety evaluation
The major adverse effects during treatment included nausea, headache, breast tenderness, and breast induration. Compared with the progesterone group, the total incidence of adverse effects was significantly reduced in the dydrogesterone group (P<0.001, Table 4).
Table 4.
Comparison of the incidence of adverse effects between the two groups of patients (n, %)
| Category | Dydrogesterone group (n=665) | Progesterone group (n=620) | χ2 | P |
|---|---|---|---|---|
| Nausea | 36 (5.41) | 56 (9.03) | 6.321 | 0.012 |
| Headache | 55 (8.27) | 74 (11.94) | 4.772 | 0.290 |
| Breast tenderness | 10 (1.50) | 8 (1.29) | 0.106 | 0.745 |
| Breast induration | 15 (2.26) | 64 (10.32) | 36.188 | <0.001 |
| Total incidence (%) | 116 (17.44) | 202 (32.58) | 39.477 | <0.001 |
Establishment of variables via XGBoost analysis
XGBoost data pool was constructed by using the clinical data of 1,285 patients. A total of 1,114 cases successfully achieved miscarriage prevention and 171 cases failed. There were 1,154 cases of normal delivery and 131 cases of preterm birth. There were 48 cases of postpartum hemorrhage and 318 cases of adverse effects, with a total incidence of 24.75%. A total of 665 cases were treated with dydrogesterone and 620 cases were treated with progesterone. The combined medication included 15 kinds of Chinese medicines such as multivitamins, Baotai Wuyou Tablet, nifedipine, etc. A total of 10 parameters including white blood cell count, red blood cell count, lymphocyte population and hematocrit were included in the test, in which only the data of early pregnancy were included. The size of final data unit was 1,285×40 (Table 5).
Table 5.
Establishment of variables via XGBoost analysis
| Variable | Category | Variable description |
|---|---|---|
| Target variable | ||
| Miscarriage prevention | Categorical variable | 1 successful miscarriage prevention, 0 unsuccessful miscarriage prevention |
| Preterm birth | Categorical variable | 0 normal delivery, 1 preterm birth |
| Postpartum hemorrhage | Categorical variable | 0 no hemorrhage, 1 hemorrhage |
| Adverse effects | Continuous variable | Unit: % |
| General information | ||
| Age | Continuous variable | Unit: year |
| Marriage | Categorical variable | Unmarried, married, divorced, other |
| Occupation | Categorical variable | Others, staff, unemployed, national civil servant, professional and technical personnel, freelancer, worker |
| Medical history | Categorical variable | Endometrial abnormalities, appendectomy, penicillin allergy |
| Pregnant information | ||
| Pregnancy times | Continuous variable | Number of previous pregnancies |
| Parity | Continuous variable | Number of past delivery |
| Number of fetuses | Continuous variable | Number of fetuses in this pregnancy |
| Hypertension during pregnancy | Continuous variable | 0 no hypertension, 1 hypertension |
| Previous pregnant history | Categorical variable | Artificial abortion, spontaneous abortion, fetal arrest, medical abortion |
| Body weight gain during pregnancy | Continuous variable | Unit: kg |
| Treatment strategy | ||
| Medication | Categorical variable | 1 dydrogesterone, 0 progesterone soft capsules |
| Course of treatment | Continuous variable | The course of taking dydrogesterone or progesterone soft capsules |
| Combined medication | ||
| Multivitamins | Categorical variable | 1 yes, 0 no |
| Baotai Wuyou Tablet | Categorical variable | 1 yes, 0 no |
| Ritodrine hydrochloride | Categorical variable | 1 yes, 0 no |
| Nifedipine | Categorical variable | 1 yes, 0 no |
| Testing data | ||
| White blood cell count_early pregnancy | Continuous variable | Unit: ×10^9/L |
| Red blood cell count_early pregnancy | Continuous variable | Unit: ×10^9/L |
| Eosinophil population_late pregnancy | Continuous variable | Unit: % |
| Basophil population_late pregnancy | Continuous variable | Unit: % |
XGBoost analysis results
The XGBoost analysis was performed with “successful miscarriage prevention”, “preterm birth”, “postpartum hemorrhage”, and “incidence of adverse effects” as the target variables, and the top 10 variables based on variable importance scores were selected. The results showed that the importance of dydrogesterone in the influencing factors of preterm birth, postpartum hemorrhage, and incidence of adverse effects ranked the 3rd, 2nd, and 1st, respectively, in patients with threatened miscarriage due to corpus luteum insufficiency (Table 6).
Table 6.
Ranking of the importance of factors affecting the outcome of miscarriage prevention
| Variable importance ranking | Successful miscarriage prevention | Preterm birth | Postpartum hemorrhage | Incidence of adverse effects |
|---|---|---|---|---|
| 1 | Parity | Parity | Hypertension during pregnancy | Dydrogesterone treatment |
| 2 | Pregnant times | Pregnant times | Parity | Age |
| 3 | Hematocrit | Dydrogesterone treatment | Dydrogesterone treatment | Course of treatment |
| 4 | Baotai Wuyou Tablet | Hypertension during pregnancy | Nifedipine | Nifedipine |
| 5 | Hypertension during pregnancy | Parity | Pregnant times | Hypertension during pregnancy |
| 6 | Age | Past pregnant history | Past pregnant history | Ritodrine hydrochloride |
| 7 | Course of treatment | Baotai Wuyou Tablet | Hematocrit | Monocyte population |
| 8 | Lymphocyte population | Course of treatment | Baotai Wuyou Tablet | Baotai Wuyou Tablet |
| 9 | White blood cell count | Body weight gain during pregnancy | Course of treatment | Lymphocyte population |
| 10 | Monocyte population | Age | Parity | Multivitamins |
Discussion
When the corpus luteum function is insufficient, the secretion of maternal progesterone and other progestogens are not enough, which cannot effectively inhibit the frequent contractions of the uterus and the immune rejection of embryonic antigens, leading to the threatened miscarriage [13,15]. Therefore, normal corpus luteum function plays important roles in the successful implantation of the zygote, maintenance of gestation, and normal embryonic development. Thus, the most direct and effective treatment strategy is the supplementation of progestogens [16].
In this study, we designed a prospective cohort study to evaluate the efficacy of dydrogesterone and progesterone in the treatment of threatened miscarriage due to corpus luteum insufficiency. The results demonstrated that there is no significant difference regarding the time for symptom relief and miscarriage prevention between the dydrogesterone group and the progesterone group, which may be due to the fact that both treatment approaches could stimulate estrogen secretion and inhibit uterine smooth muscle contraction. However, progesterone has a slower onset of action but a rapid inactivation by the liver after uptake by the body, resulting in a very short half-life and poor efficacy in some patients [17]. Studies have also reported that long-term use of progesterone may cause adverse effects such as muscle twitches and gastrointestinal discomfort, leading to limited clinical applications [18]. In our study, serum sex hormone levels were elevated and the preterm birth rate was significantly reduced in patients treated with dydrogesterone. Manuck has also reported that dydrogesterone could effectively reduce the preterm birth rate [19]. Hudic et al. have revealed that dydrogesterone treatment could effectively upregulate the levels of the blocking factor and interleukin (IL)-10 in pregnant women with a high risk of preterm birth, and regulate the ratio of Th1/Th2 to extend the gestational period [20]. In addition, the rate of postpartum hemorrhage and adverse effects were significantly reduced in the dydrogesterone group of this study. Other studies have also demonstrated that dydrogesterone could effectively reduce the incidence of hypertension and preeclampsia during pregnancy, which may be one of the mechanisms by which dydrogesterone could reduce the incidence of preterm birth and postpartum hemorrhage [21,22]. Compared with progesterone soft capsules, the advantages of dydrogesterone in the treatment of patients with threatened miscarriage due to corpus luteum insufficiency include: ① As a progesterone analog, dydrogesterone can be quickly absorbed via oral administration, and has a higher affinity and specificity for progesterone receptors; ② It can be orally administered, with few adverse effects and higher medication compliance; ③ It demonstrates a good immunomodulatory effect, effectively reduces maternal immune response to embryos, and promotes embryo implantation; ④ It can inhibit the synthesis and release of prostaglandins in the endometrium and provide a favorable environment for embryo development [23-25].
We further adopted the machine learning XGBoost algorithm to evaluate the efficacy and safety of dydrogesterone. Through the analysis of the correlation between the patients’ clinical data and endpoints after treatment, the important factors related to these endpoints were discovered, and the evaluation model for the safety and efficacy of dydrogesterone in the treatment of threatened miscarriage was established, which greatly improved the reliability of our data. The results revealed that dydrogesterone treatment was correlated with a lower incidence of preterm birth, postpartum hemorrhage, and adverse effects, ranking 3rd, 2nd, and 1st, respectively, in the weight of dependent variables.
In summary, compared with progesterone, dydrogesterone can significantly improve the delivery outcome, showing a higher safety in the treatment of threatened miscarriage due to corpus luteum insufficiency.
Disclosure of conflict of interest
None.
References
- 1.El Zowalaty AE, Li R, Zheng Y, Lydon JP, DeMayo FJ, Ye X. Deletion of RhoA in progesterone receptor-expressing cells leads to luteal insufficiency and infertility in female mice. Endocrinology. 2017;158:2168–2178. doi: 10.1210/en.2016-1796. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Zhang Y, Yan W, Ge PF, Li Y, Ye Q. Study on prevention effect of zishen yutai pill combined with progesterone for threatened abortion in rats. Asian Pac J Trop Med. 2016;9:577–581. doi: 10.1016/j.apjtm.2016.04.002. [DOI] [PubMed] [Google Scholar]
- 3.Mirza FG, Patki A, Pexman-Fieth C. Dydrogesterone use in early pregnancy. Gynecol Endocrinol. 2016;32:97–106. doi: 10.3109/09513590.2015.1121982. [DOI] [PubMed] [Google Scholar]
- 4.Ozlü T, Güngör AC, Dönmez ME, Duran B. Use of progestogens in pregnant and infertile patients. Arch Gynecol Obstet. 2012;286:495–503. doi: 10.1007/s00404-012-2340-4. [DOI] [PubMed] [Google Scholar]
- 5.Lee HJ, Park TC, Kim JH, Norwitz E, Lee B. The influence of oral dydrogesterone and vaginal progesterone on threatened abortion: a systematic review and meta-analysis. Biomed Res Int. 2017;2017:3616875. doi: 10.1155/2017/3616875. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Greene MF. Progesterone for threatened abortion. N Engl J Med. 2019;380:1867–1868. doi: 10.1056/NEJMe1903069. [DOI] [PubMed] [Google Scholar]
- 7.Mueck AO, Ruan X. Will estradiol/progesterone capsules for oral use become the best choice for menopausal hormone therapy? Climacteric. 2019;22:535–537. doi: 10.1080/13697137.2019.1663625. [DOI] [PubMed] [Google Scholar]
- 8.Griesinger G, Blockeel C, Tournaye H. Oral dydrogesterone for luteal phase support in fresh in vitro fertilization cycles: a new standard? Fertil Steril. 2018;109:756–762. doi: 10.1016/j.fertnstert.2018.03.034. [DOI] [PubMed] [Google Scholar]
- 9.Schindler AE, Carp H, Druckmann R, Genazzani AR, Huber J, Pasqualini J, Schweppe KW, Szekeres-Bartho J. European progestin club guidelines for prevention and treatment of threatened or recurrent (habitual) miscarriage with progestogens. Gynecol Endocrinol. 2015;31:447–449. doi: 10.3109/09513590.2015.1017459. [DOI] [PubMed] [Google Scholar]
- 10.Coomarasamy A, Williams H, Truchanowicz E, Seed PT, Small R, Quenby S, Gupta P, Dawood F, Koot YE, Bender Atik R, Bloemenkamp KW, Brady R, Briley AL, Cavallaro R, Cheong YC, Chu JJ, Eapen A, Ewies A, Hoek A, Kaaijk EM, Koks CA, Li TC, MacLean M, Mol BW, Moore J, Ross JA, Sharpe L, Stewart J, Vaithilingam N, Farquharson RG, Kilby MD, Khalaf Y, Goddijn M, Regan L, Rai R. A randomized trial of progesterone in women with recurrent miscarriages. N Engl J Med. 2015;373:2141–2148. doi: 10.1056/NEJMoa1504927. [DOI] [PubMed] [Google Scholar]
- 11.Ogunleye AA, Wang QG. XGBoost model for chronic kidney disease diagnosis. IEEE/ACM Trans Comput Biol Bioinform. 2020;17:2131–2140. doi: 10.1109/TCBB.2019.2911071. [DOI] [PubMed] [Google Scholar]
- 12.Babajide Mustapha I, Saeed F. Bioactive molecule prediction using extreme gradient boosting. Molecules. 2016;21:893. doi: 10.3390/molecules21080983. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Zhou J, Huang Z, Pan X, Leung WT, Li C, Chen L, Zhang Y, Wang L, Sima Y, Zhang N, Qiu X, Li L, Wang L. New thoughts in exploring the pathogenesis, diagnosis, and treatment of threatened abortion. Biosci Trends. 2019;13:284–285. doi: 10.5582/bst.2019.01155. [DOI] [PubMed] [Google Scholar]
- 14.Suff N, Story L, Shennan A. The prediction of preterm delivery: what is new? Semin Fetal Neonatal Med. 2019;24:27–32. doi: 10.1016/j.siny.2018.09.006. [DOI] [PubMed] [Google Scholar]
- 15.Tangco K, Sigue AJ, Gorgonio N. EP28.24: corpus luteum of pregnancy: prognostic signficance of the transvaginal ultrasound morphology and volume in early pregnancy outcome. Ultrasound Obstet Gynecol. 2019;54:416–417. [Google Scholar]
- 16.Carp HJ. Progestogens in the prevention of miscarriage. Horm Mol Biol Clin Investig. 2016;27:55–62. doi: 10.1515/hmbci-2015-0058. [DOI] [PubMed] [Google Scholar]
- 17.Greene MF. Progesterone for threatened abortion a commentary on a randomized trial of progesterone in women with bleeding in early pregnancy. Obstet Anesth Dig. 2019;39:211. [Google Scholar]
- 18.Alimohamadi S, Javadian P, Gharedaghi MH, Javadian N, Alinia H, Khazardoust S, Borna S, Hantoushzadeh S. Progesterone and threatened abortion: a randomized clinical trial on endocervical cytokine concentrations. J Reprod Immunol. 2013;98:52–60. doi: 10.1016/j.jri.2013.01.004. [DOI] [PubMed] [Google Scholar]
- 19.Manuck TA. Pharmacogenomics of preterm birth prevention and treatment. BJOG. 2016;123:368–375. doi: 10.1111/1471-0528.13744. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hudic I, Schindler AE, Szekeres-Bartho J, Stray-Pedersen B. Dydrogesterone and pre-term birth. Horm Mol Biol Clin Investig. 2016;27:81–83. doi: 10.1515/hmbci-2015-0064. [DOI] [PubMed] [Google Scholar]
- 21.Schindler AE. New data about preeclampsia: some possibilities of prevention. Gynecol Endocrinol. 2018;34:636–637. doi: 10.1080/09513590.2018.1441401. [DOI] [PubMed] [Google Scholar]
- 22.Zainul Rashid MR, Lim JF, Nawawi NH, Luqman M, Zolkeplai MF, Rangkuty HS, Mohamad Nor NA, Tamil A, Shah SA, Tham SW, Schindler AE. A pilot study to determine whether progestogen supplementation using dydrogesterone during the first trimester will reduce the incidence of gestational hypertension in primigravidae. Gynecol Endocrinol. 2014;30:217–220. doi: 10.3109/09513590.2013.860960. [DOI] [PubMed] [Google Scholar]
- 23.Tournaye H, Sukhikh GT, Kahler E, Griesinger G. A phase III randomized controlled trial comparing the efficacy, safety and tolerability of oral dydrogesterone versus micronized vaginal progesterone for luteal support in in vitro fertilization. Hum Reprod. 2017;32:1019–1027. doi: 10.1093/humrep/dex023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Griesinger G, Tournaye H, Macklon N, Petraglia F, Arck P, Blockeel C, van Amsterdam P, Pexman-Fieth C, Fauser BC. Dydrogesterone: pharmacological profile and mechanism of action as luteal phase support in assisted reproduction. Reprod Biomed Online. 2019;38:249–259. doi: 10.1016/j.rbmo.2018.11.017. [DOI] [PubMed] [Google Scholar]
- 25.Neumann K, Depenbusch M, Schultze-Mosgau A, Griesinger G. Characterization of early pregnancy placental progesterone production by utilization of dydrogesterone in programmed frozen-thawed embryo transfer cycles. Reprod Biomed Online. 2020;40:743–751. doi: 10.1016/j.rbmo.2020.01.019. [DOI] [PubMed] [Google Scholar]