Time as an outcome measure in fertility-related clinical studies: long-awaited

Sunkara, Sesh Kamal; Zheng, Wenjing; D’Hooghe, Thomas; Longobardi, Salvatore; Boivin, Jacky

doi:10.1093/humrep/deaa138

Cited by 21 publications

(16 citation statements)

References 36 publications

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“…The recommended secondary endpoints include the number of oocytes retrieved (both overall and metaphase II oocytes), the number of embryos generated, the FOI ( 20 ), and how effective a specific intervention was in achieving the number of oocytes estimated by the ART calculator ( 30 ). Time to live birth (TTLB) is an additional outcome that should be considered, given that a shorter time in achieving a live birth is a reflection of the clinical and cost-effectiveness of any intervention ( 65 ). Also, in observational studies, particularly those involving big analytics, the frequency of patients fitting each POSEIDON group should be reported, including –if possible– a control group of non-POSEIDON patients for comparison.…”

Section: Resultsmentioning

confidence: 99%

“…However, the use of such endpoints in preference over CDR in POSEIDON studies should always be justified. When considering time-to-pregnancy (TTP) or TTLB as an outcome, the start time point should be oocyte retrieval and the end time point the clinical pregnancy (TTP) or live birth (TTLB) ( 65 ). As POSEIDON interventions should aim to increase the oocyte yield for the low prognosis patients, this justifies the start point from oocyte retrieval for TTP and TTLB outcomes.…”

Section: Discussionmentioning

confidence: 99%

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Improving Reporting of Clinical Studies Using the POSEIDON Criteria: POSORT Guidelines

Esteves¹,

Conforti

Sunkara

et al. 2021

Front. Endocrinol.

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The POSEIDON (Patient-Oriented Strategies Encompassing IndividualizeD Oocyte Number) criteria were developed to help clinicians identify and classify low-prognosis patients undergoing assisted reproductive technology (ART) and provide guidance for possible therapeutic strategies to overcome infertility. Since its introduction, the number of published studies using the POSEIDON criteria has increased steadily. However, a critical analysis of existing evidence indicates inconsistent and incomplete reporting of critical outcomes. Therefore, we developed guidelines to help researchers improve the quality of reporting in studies applying the POSEIDON criteria. We also discuss the advantages of using the POSEIDON criteria in ART clinical studies and elaborate on possible study designs and critical endpoints. Our ultimate goal is to advance the knowledge concerning the clinical use of the POSEIDON criteria to patients, clinicians, and the infertility community.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Improving Reporting of Clinical Studies Using the POSEIDON Criteria: POSORT Guidelines

Esteves¹,

Conforti

Sunkara

et al. 2021

Front. Endocrinol.

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“…Because of the intricacy of IVF, the time to live delivery may be longer than with IUI. To compare the time spent for the two procedures, we utilized the Kaplan-Meier curves, which is recommended for evaluating the CLBR across time in clinical investigations [13]. The ndings showed that when the two groups were censored at 180 days, the live birth rates were not substantially different.…”

Section: Discussionmentioning

confidence: 99%

Intrauterine insemination or in vitro fertilization for the treatment of Poseidon group 3 and unexplained subfertility: A propensity score matching study

Liu

2021

Preprint

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Background Although it is becoming an increasingly significant indication for in-vitro fertilization (IVF), no studies have been done to examine the efficacy of IVF and intrauterine insemination (IUI) for the treatment of young patients with unexplained infertility and low ovarian reserve. The goal of this research was to compare the efficacy of IVF with IUI on Poseidon group 3 patients with unexplained infertility (PG3&UI). Methods This was a retrospective analysis of PG3&UI patients who had IVF/intracytoplasmic sperm injection (ICSI) or IUI at the Third Affiliated Hospital of Guangzhou Medical University between January 1, 2015, and March 31, 2021. To equalize the baseline characteristics of the IVF and IUI groups, propensity score matching (PSM) was utilized. Intention-to-treat (ITT) and per-protocol (PP) analyses were used to compare the differences in live births. To discover variations in time to biochemical pregnancy leading to live birth, Kaplan-Meier curves were produced. To evaluate the expenses per live birth between two procedures, a cost-effective analysis was done. Results According to ITT analysis, the live birth rate for the IVF group was substantially higher than the cumulative live birth rate (CLBR) for the IUI group (22.6% (38/168) vs. 11.3% (19/168), RR 2.00, 95% CI 1.20–3.32, P = 0.006). In the PP analysis, the live birth rate was 23.0% (38/165) in the IVF group and 11.7% (19/162) in the IUI group (RR = 1.96, 95% CI 1.18–3.26, P = 0.007). When censored at 365 days, the Kaplan-Meier analysis revealed that the IVF group had a higher live birth rate than the IUI group (log-rank test χ²= 6.025; P = 0.014). However, when the two groups were censored at 180 days, the live birth rates were not substantially different (log-rank test χ²= 3.847; P = 0.05). The number of visits per live birth in the IUI group was higher than in the IVF group (85 vs. 48). The overall cost of a live birth was comparable across the two groups (¥132242 vs. ¥131611), while the medical expenses for a live delivery from IVF were higher than those from IUI ((¥118955 vs. ¥108279). Conclusions The livebirth rate per IVF cycle with at most one embryo transfer is higher than the CLBR of IUI, with fewer hospital visits and similar expenses.

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“…The first is to consider the effect of an intervention on cumulative live birth rates (CLBR), a term which refers to the proportion of patients having a live birth following some maximum number of treatment attempts or after a given period of follow-up time (Malizia et al 2009). The second is to consider the effect on time to live birth, which refers to how long it takes to have a live birth (Sunkara et al 2020). The two concepts are quite closely related, and in fact, CLBR may be (and often is) estimated using methods for time-toevent analysis.…”

Section: Evaluating Treatment Outcomes Over Multiple Treatment Attemptsmentioning

confidence: 99%

“…In recognition of the fact that fertility treatment is often emotionally and financially burdensome, there is a current interest in identifying treatments and treatment strategies that reduce the duration from treatment initiation to live birth (Sunkara et al 2020). This focus on a patientcentred outcome is laudable.…”

Section: Errors In the Analysis Of Time To Live Birthmentioning

confidence: 99%

Study design flaws and statistical challenges in evaluating fertility treatments

Stocking

2021

Reproduction and Fertility

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Health interventions should be tested before being introduced into clinical practice, to find out whether they work and whether they are harmful. However, research studies will only provide reliable answers to these questions if they are appropriately designed and analysed. But these are not trivial tasks. We review some methodological challenges that arise when evaluating fertility interventions and explain the implications for a non-statistical audience. These include flexibility in outcomes and analyses; use of surrogate outcomes instead of live birth; use of inappropriate denominators; evaluating cumulative outcomes and time to live birth; allowing each patient or couple to contribute to a research study more than once. We highlight recurring errors and present solutions. We conclude by highlighting the importance of collaboration between clinical and methodological experts, as well as people with experience of subfertility, for realising high-quality research. Lay summary We do research to find out whether fertility treatments are beneficial and to make sure they don’t cause harm. However, research will only provide reliable answers if it is done properly. It is not unusual for researchers to make mistakes when they are designing research studies and analysing the data that we get from them. In this review, we describe some of the mistakes people make when they do research about fertility treatments and explain how to avoid them. These include challenges which arise due to the large number of things that can be measured and reported when looking to see if fertility treatments work; failure to check whether the treatment increases the number of live births; failing to include all study participants in calculations;challenges in studies where participants may have more than one treatment attempt. We conclude by highlighting the importance of collaboration between clinical and methodological experts, as well as people with experience of fertility problems.

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Time as an outcome measure in fertility-related clinical studies: long-awaited

Cited by 21 publications

References 36 publications

Improving Reporting of Clinical Studies Using the POSEIDON Criteria: POSORT Guidelines

Improving Reporting of Clinical Studies Using the POSEIDON Criteria: POSORT Guidelines

Intrauterine insemination or in vitro fertilization for the treatment of Poseidon group 3 and unexplained subfertility: A propensity score matching study

Study design flaws and statistical challenges in evaluating fertility treatments

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