Fertility in Populations and in Patients: Population studies on natural fertility and prediction of treatment outcome in anovulatory infertile patients

__Abstract__ In most western societies, reproductive behavior is nowadays controlled to a high degree: observed fertility patterns in a population -how many children do couples get and when do they get them- are the result of choices made by individuals rather than biological factors. This is in marked contrast with previous times, in which it was the biological destiny of women to have children - or to remain childless involuntarily. The driving force behind the change that has occurred is undoubtedly the availability of reliable contraception (Leridon, 1998), which has gone hand in hand with changes in social attitudes with respect to reproduction (e.g. secularization, emancipation of women (Blossfeld, 1995)). In many Western European societies, the number of children per woman has dropped below the natural replacement level (Von Cube, 1986), and everywhere couples who want to have children carefully plan when to have them. In many countries women delay childbearing to later age, the most pronounced example being the Netherlands in which the mean age at first childbirth has risen from 24.6 years in 1970 to 29.2 years in 2001. Since pregnancy chances decrease with age of the women (Schwartz and Mayaux, 1982) (van Noord-Zaadstra et al., 1991), postponement of the first child has led to an increase in incidence of subfertility (te Velde, 1991)

Age-related differences in features associated with polycystic ovary syndrome in normogonadotrophic oligo-amenorrhoeic infertile women of reproductive years

OBJECTIVE: To assess the effect of age on clinical, endocrine and sonographic features associated with polycystic ovary syndrome (PCOS) in normogonadotrophic anovulatory infertile women of reproductive years

Meta-analysis approach as a gene selection method in class prediction: Does it improve model performance? A case study in acute myeloid leukemia

Background: Aggregating gene expression data across experiments via meta-analysis is expected to increase the precision of the effect estimates and to increase the statistical power to detect a certain fold change. This study evaluates the potential benefit of using a meta-analysis approach as a gene selection method prior to predictive modeling in gene expression data. Results: Six raw datasets from different gene expression experiments in acute myeloid leukemia (AML) and 11 different classification methods were used to build classification models to classify samples as either AML or healthy control. First, the classification models were trained on gene expression data from single experiments using conventional supervised variable selection and externally validated with the other five gene expression datasets (referred to as the individual-classification approach). Next, gene selection was performed through meta-analysis on four datasets, and predictive models were trained with the selected genes on the fifth dataset and validated on the sixth dataset. For some datasets, gene selection through meta-analysis helped classification models to achieve higher performance as compared to predictive modeling based on a single dataset; but for others, there was no major improvement. Synthetic datasets were generated from nine simulation scenarios. The effect of sample size, fold change and pairwise correlation between differentially expressed (DE) genes on the difference between MA- and individual-classification model was evaluated. The fold change and pairwise correlation significantly contributed to the difference in performance between the two methods. The gene selection via meta-analysis approach was more effective when it was conducted using a set of data with low fold change and high pairwise correlation on the DE genes. Conclusion: Gene selection through meta-analysis on previously published studies potentially improves the performance of a predictive model on a given gene expression data

Patient predictors for outcome of gonadotrophin ovulation induction in women with normogonadotrophic anovulatory infertility: a meta-analysis

A systematic review was conducted to determine whether initial screening characteristics of wo

Predictors of chances to conceive in ovulatory patients during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility

The present prospective follow-up study was designed to identify whether clinical, endocrine, or ultrasound characteristics assessed by standardized initial screening of normogonadotropic oligo/amenorrheic infertile patients could predict conception in 160 women who reached ovulation after clomiphene citrate (CC) medication. Additional inclusion criteria were total motile sperm count of the partner above 1 million and a negative history for any tubal disease. Daily CC doses of 50 mg (increasing up to 150 mg in case of absent ovarian response) from cycle days 3-7 were used. First conception (defined as a positive urinary pregnancy test) was the end point for this study. A cumulative conception rate of 73% was reached within 9 CC-induced ovulatory cycles. Patients who did conceive presented more frequently with lower age (P < 0.0001) and amenorrhea (P < 0.05) upon initial screening. In a univariate analysis, patients with elevated initial serum LH concentrations (>7.0 IU/L) had a higher probability of conceiving (P < 0.01). In a multivariate analysis, age and cycle history (oligomenorrhea vs. amenorrhea) were identified as the only significant parameters for prediction of conception. These observations suggest that there is more to be gained from CC ovulation induction in younger women presenting with profound oligomenorrhea or amenorrhea. Screening characteristics involved in the prediction of ovulation after CC medication in normogonadotropic oligo/amenorrheic patients (body weight and hyperandrogenemia, as shown previously) are distinctly different from predictors of conception in ovulatory CC patients (age and the severity of cycle abnormality). This disparity suggests that the FSH threshold (magnitude of FSH required for stimulation of ongoing follicle growth and ovulation) and oocyte quality (chances for conception in ovulatory cycles) may be differentially regulated

High singleton live birth rate following classical ovulation induction in normogonadotrophic anovulatory infertility (WHO 2)

BACKGROUND: Medical induction of ovulation using clomiphene citrate (CC) as first line and exogenous gonadotrophins as second line forms the classical treatment algorithm in normogonadotrophic anovulatory infertility. Because the chances of success following classical ovulation induction are not well established, a shift in first-line therapy can be observed towards alternative treatment. The study aim was to: (i) reliably assess the probability of singleton live birth following classical induction of ovulation; and (ii) construct a prediction model, based on individual patient characteristics assessed upon standardized initial screening, to help identify patients with poor chances of success. METHODS: A total of 240 consecutive women visiting a specialist academic fertility unit with a history of infertility, oligomenorrhoea or amenorrhoea, and normal FSH and estradiol serum concentrations (WHO group 2) was prospectively followed. The women had not been previously treated with ovulation-inducing agents. All patients commenced with CC. Patients who did not ovulate within three treatment cycles of incremental daily doses up to 150 mg for 5 consecutive days or ovulatory CC patients who did not conceive within six cycles, subsequently underwent gonadotrophin induction of ovulation applying a step-down dose regimen. The main outcome measure was pregnancy resulting in singleton live birth. Cox regression was used to construct a multivariable prediction model. RESULTS: Overall, there were 134 pregnancies ending in a singleton live birth (56% of women). The cumulative pregnancy rate after 12 and 24 months of follow-up was 50% and 71% respectively. Polycystic ovary syndrome (PCOS) patients (49%), clearly non-PCOS patients (13%) and the in-between group did not differ in prognosis (P = 0.9). The multivariable Cox regression model contained the woman's age, the insulin:glucose ratio and duration of infertility. With a cut-off value of 30% for low chance, the model predicted probabilities at 12 months lower than this cut-off for 25 out of 240 patients (10.4%). CONCLUSIONS: Classical ovulation induction produces very good results in normogonadotrophic anovulatory infertility. Alternative treatment options may not be indicated as first-line therapy in these patients, except for subgroups with poor prognosis. These women can be identified by older age, longer duration of infertility and higher insulin:glucose ratio

Predictors of patients remaining anovulatory during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility

The diagnostic criteria used to identify patients suffering from polycystic ovary syndrome remain controversial. The present prospective longitudinal follow-up study was designed to identify whether certain criteria assessed during standardized initial screening could predict the response to ovulation induction with clomiphene citrate (CC) in 201 patients presenting with oligomenorrhea or amenorrhea and infertility. Serum FSH levels were within the normal range (1-10 IU/L), and all patients underwent spontaneous or progestin-induced withdrawal bleeding. Initial CC doses were 50 mg daily for 5 days starting on cycle day 3. In the case of an absent response, doses were increased to 100 and 150 mg daily in subsequent cycles. First ovulation with CC was used as the end point. After a complete follow-up (in the case of a nonresponse, at least 3 treatment cycles with daily CC doses up to 150 mg), 156 patients (78%) ovulated. The free androgen index (FAI = testosterone/sex hormone-binding globulin ratio), body mass index (BMI), cycle history (oligomenorrhea vs. amenorrhea), serum androgen (testosterone and/or androstenedione) levels, and mean ovarian volume assessed by transvaginal sonography were all significantly different (P < 0.01) in responders from those in nonresponders. FAI was chosen to be the best predictor in univariate analysis. The area under the receiver operating characteristics curve in a multivariate prediction model including FAI, BMI, cycle history, and mean ovarian volume was 0.82. Patients whose ovaries are less likely to respond to stimulation by FSH due to CC treatment can be predicted on the basis of initial screening characteristics, such as FAI, BMI, cycle history (oligomenorrhea or amenorrhea), and mean ovarian volume. These observations may add to ongoing discussion regarding etiological factors involved in ovarian dysfunction in these patients and classification of normogonadotropic anovulatory infertile women

Age at menopause as a risk factor for cardiovascular mortality

Background. Although an association of occurrence of menopause and subsequent oestrogen deficiency with increased cardiovascular disease has been postulated, studies on this association have not shown convincing results. We investigated whether age at menopause is associated with cardiovascular mortality risk. Methods. We

Realizing a desired family size: When should couples start?

STUDY QUESTION Until what age can couples wait to start a family without compromising their chances of realizing the desired number of children? SUMMARY ANSWER The latest female age at which a couple should start trying to become pregnant strongly depends on the importance attached to achieving a desired family size and on whether or not IVF is an acceptable option in case no natural pregnancy occurs. WHAT IS KNOWN ALREADY It is well established that the treatment-independent and treatment-dependent chances of pregnancy decline with female age. However, research on the effect of age has focused on the chance of a first pregnancy and not on realizing more than one child. STUDY DESIGN, SIZE, DURATION An established computer simulation model of fertility, updated with recent IVF success rates, was used to simulate a cohort of 10 000 couples in order to assess the chances of realizing a one-, two- or three-child family, for different female ages at which the couple starts trying to conceive. PARTICIPANTS/MATERIALS, SETTING, METHODS The model uses treatment-independent pregnancy chances and pregnancy chances after IVF/ICSI. In order to focus the discussion, we single out three levels of importance that couples could attach to realizing a desired family size: (i) Very important (equated with aiming for at least a 90% success chance). (ii) Important but not at all costs (equated with a 75% success chance) (iii) Good to have children, but a life without children is also fine (equated with a 50% success chance). MAIN RESULTS AND THE ROLE OF CHANCE In order to have a chance of at least 90% to realize a one-child family, couples should start trying to conceive when the female partner is 35 years of age or younger, in case IVF is an acceptable option. For two children, the latest starting age is 31 years, and for three children 28 years. Without IVF, couples should start no later than age 32 years for a one-child family, at 27 years for a two-child family, and at 23 years for three children. When couples accept 75% or lower chances of family completion, they can start 4-11 years later. The results appeared to be robust for plausible changes in model assumptions. LIMITATIONS, REASONS FOR CAUTION Our conclusions would have been more persuasive if derived directly from large-scale prospective studies. An evidence-based simulation study (as we did) is the next best option. We recommend that the simulations should be updated every 5-10 years with new evidence because, owing to improvements in IVF technology, the assumptions on IVF success chances in particular run the risk of becoming outdated. WIDER IMPLICATIONS OF THE FINDINGS Information on the chance of family completion at different starting ages is important for prospective parents in planning their family, for preconception counselling, for inclusion in educational courses in human biology, and for increasing public awareness on human reproductive possibilities and limitations

Comparing methods to combine functional loss and mortality in clinical trials for amyotrophic lateral sclerosis

Objective: Amyotrophic lateral sclerosis (ALS) clinical trials based on single end points only partially capture the full treatment effect when both function and mortality are affected, and may falsely dismiss efficacious drugs as futile. We aimed to investigate the statistical properties of several strategies for the simultaneous analysis of function and mortality in ALS clinical trials. Methods: Based on the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, we simulated longitudinal patterns of functional decline, defined by the revised amyotrophic lateral sclerosis functional rating scale (ALSFRS-R) and conditional survival time. Different treatment scenarios with varying effect sizes were simulated with follow-up ranging from 12 to 18 months. We considered the following analytical strategies: 1) Cox model; 2) linear mixed effects (LME) model; 3) omnibus test based on Cox and LME models; 4) composite time-to-6-point decrease or death; 5) combined assessment of function and survival (CAFS); and 6) test based on joint modeling framework. For each analytical strategy, we calculated the empirical power and sample size. Results: Both Cox and LME models have increased false-negative rates when treatment exclusively affects either function or survival. The joint model has superior power compared to other strategies. The composite end point increases false-negative rates among all treatment scenarios. To detect a 15% reduction in ALSFRS-R decline and 34% decline in hazard with 80% power after 18 months, the Cox model requires 524 patients, the LME model 794 patients, the omnibus test 526 patients, the composite end poi