Adjuvant treatment strategies in ovarian stimulation for poor responders undergoing IVF: a systematic review and network meta-analysis
Bibliographic record
Abstract
BACKGROUND: Despite great advances in assisted reproductive technology, poor ovarian response (POR) is still considered as one of the most challenging tasks in reproductive medicine. OBJECTIVE AND RATIONALE: The aim of this systemic review is to evaluate the role of different adjuvant treatment strategies on the probability of pregnancy achievement in poor responders undergoing IVF. Randomized controlled trials (RCTs) comparing 10 adjuvant treatments [testosterone, dehydroepiandrosterone (DHEA), letrozole, recombinant LH, recombinant hCG, oestradiol, clomiphene citrate, progesterone, growth hormone (GH) and coenzyme Q10 (CoQ10)] were included. SEARCH METHODS: Relevant studies published in the English language were comprehensively selected using PubMed, Embase and the Cochrane Central Register of Controlled Trials (CENTRAL) until 11 July 2018. We included studies that investigated various adjuvant agents, including androgen and androgen-modulating agents, oestrogen, progesterone, clomiphene citrate, GH and CoQ10, during IVF treatment and reported subsequent pregnancy outcomes. The administration of GnRH analogs and gonadotrophins without adjuvant treatment was set as the control. We measured study quality based on the methodology and categories listed in the Cochrane Collaboration Handbook. This review protocol was registered with PROSPERO (CRD42018086217). OUTCOMES: Of the 1124 studies initially identified, 46 trials reporting on 6312 women were included in this systematic review, while 19 trials defining POR using the Bologna criteria reporting 2677 women were included in the network meta-analysis. Compared with controls, DHEA and CoQ10 treatments resulted in a significantly higher chance of clinical pregnancy [odds ratio (OR) 2.46, 95% CI 1.16 to 5.23; 2.22, 1.08-4.58, respectively]. With regard to the number of retrieved oocytes, HCG, oestradiol and GH treatments had the highest number of oocytes retrieved [weighted mean difference (WMD) 2.08, 0.72 to 3.44; 2.02, 0.23 to 3.81; 1.72, 0.98 to 2.46, compared with controls, respectively]. With regard to the number of embryos transferred, testosterone and GH treatment led to the highest number of embryos transferred (WMD 0.72, 0.11 to 1.33; 0.67, 0.43 to 0.92; compared with controls, respectively). Moreover, GH resulted in the highest oestradiol level on the HCG day (WMD 797.63, 466.45 to 1128.81, compared with controls). Clomiphene citrate, letrozole and GH groups used the lowest dosages of gonadotrophins for ovarian stimulation (WMD 1760.00, -2890.55 to -629.45; -1110.17, -1753.37 to -466.96; -875.91, -1433.29 to -282.52; compared with controls, respectively). CoQ10 led to the lowest global cancelation rate (OR 0.33, 0.15 to 0.74, compared with controls). WIDER IMPLICATIONS: For patients with POR, controlled ovarian stimulation protocols using adjuvant treatment with DHEA, CoQ10 and GH showed better clinical outcomes in terms of achieving pregnancy, and a lower dosage of gonadotrophin required for ovulation induction. Furthermore, high-level RCT studies using uniform standards for POR need to be incorporated into future meta-analyses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".