Molecular Landscape of Pelvic Organ Prolapse Provides Insights into Disease Etiology.

Pelvic organ prolapse (POP) represents a major health care burden in women, but its underlying pathophysiological mechanisms have not been elucidated. We first used a case-control design to perform an exome chip study in 526 women with POP and 960 control women to identify single nucleotide variants (SNVs) associated with the disease. We then integrated the functional interactions between the POP candidate proteins derived from the exome chip study and other POP candidate molecules into a molecular landscape. We found significant associations between POP and SNVs in 54 genes. The proteins encoded by 26 of these genes fit into the molecular landscape, together with 43 other POP candidate molecules. The POP landscape is located in and around epithelial cells and fibroblasts of the urogenital tract and harbors four interacting biological processes-epithelial-mesenchymal transition, immune response, modulation of the extracellular matrix, and fibroblast function-that are regulated by sex hormones and TGFB1. Our findings were corroborated by enrichment analyses of differential gene expression data from an independent POP cohort. Lastly, based on the landscape and using vaginal fibroblasts from women with POP, we predicted and showed that metformin alters gene expression in these fibroblasts in a beneficial direction. In conclusion, our integrated molecular landscape of POP provides insights into the biological processes underlying the disease and clues towards novel treatments.

Gaining power in multiple testing of interval hypotheses via conditionalization.

In this article, we introduce a novel procedure for improving power of multiple testing procedures (MTPs) of interval hypotheses. When testing interval hypotheses the null hypothesis $P$-values tend to be stochastically larger than standard uniform if the true parameter is in the interior of the null hypothesis. The new procedure starts with a set of $P$-values and discards those with values above a certain pre-selected threshold, while the rest are corrected (scaled-up) by the value of the threshold. Subsequently, a chosen family-wise error rate (FWER) or false discovery rate MTP is applied to the set of corrected $P$-values only. We prove the general validity of this procedure under independence of $P$-values, and for the special case of the Bonferroni method, we formulate several sufficient conditions for the control of the FWER. It is demonstrated that this "filtering" of $P$-values can yield considerable gains of power.

A powerful and efficient two-stage method for detecting gene-to-gene interactions in GWAS.

For over a decade functional gene-to-gene interaction (epistasis) has been suspected to be a determinant in the "missing heritability" of complex traits. However, searching for epistasis on the genome-wide scale has been challenging due to the prohibitively large number of tests which result in a serious loss of statistical power as well as computational challenges. In this article, we propose a two-stage method applicable to existing case-control data sets, which aims to lessen both of these problems by pre-assessing whether a candidate pair of genetic loci is involved in epistasis before it is actually tested for interaction with respect to a complex phenotype. The pre-assessment is based on a two-locus genotype independence test performed in the sample of cases. Only the pairs of loci that exhibit non-equilibrium frequencies are analyzed via a logistic regression score test, thereby reducing the multiple testing burden. Since only the computationally simple independence tests are performed for all pairs of loci while the more demanding score tests are restricted to the most promising pairs, genome-wide association study (GWAS) for epistasis becomes feasible. By design our method provides strong control of the type I error. Its favourable power properties especially under the practically relevant misspecification of the interaction model are illustrated. Ready-to-use software is available. Using the method we analyzed Parkinson's disease in four cohorts and identified possible interactions within several SNP pairs in multiple cohorts.

Robin Hood: A cost-efficient two-stage approach to large-scale simultaneous inference with non-homogeneous sparse effects.

A classical approach to experimental design in many scientific fields is to first gather all of the data and then analyze it in a single analysis. It has been recognized that in many areas such practice leaves substantial room for improvement in terms of the researcher's ability to identify relevant effects, in terms of cost efficiency, or both. Considerable attention has been paid in recent years to multi-stage designs, in which the user alternates between data collection and analysis and thereby sequentially reduces the size of the problem. However, the focus has generally been towards designs that require a hypothesis be tested in every single stage before it can be declared as rejected by the procedure. Such procedures are well-suited for homogeneous effects, i.e. effects of (almost) equal sizes, however, with effects of varying size a procedure that permits rejection at interim stages is much more suitable. Here we present precisely such multi-stage testing procedure called Robin Hood. We show that with heterogeneous effects our method substantially improves on the existing multi-stage procedures with an essentially zero efficiency trade-off in the homogeneous effect realm, which makes it especially useful in areas such as genetics, where heterogeneous effects are common. Our method improves on existing approaches in a number of ways including a novel way of performing two-sided testing in a multi-stage procedure with increased power for detecting small effects.

Two-Stage Testing for Epistasis: Screening and Verification.

Undiscovered gene-to-gene interaction (epistasis) is a possible explanation for the "missing heritability" of complex traits and diseases. On a genome-wide scale, screening for epistatic effects among all possible pairs of genetic markers faces two main complications. Firstly, the classical statistical methods for modeling epistasis are computationally very expensive, which makes them impractical on such large scale. Secondly, straightforward corrections for multiple testing using the classical methods tend to be too coarse and inefficient at discovering the epistatic effects in such a large scale application. In this chapter, we describe both the underlying framework and practical examples of two-stage statistical testing methods that alleviate both of the aforementioned complications.

A Systematic Review of the Impact of Surgeon and Hospital Caseload Volume on Oncological and Nononcological Outcomes After Radical Prostatectomy for Nonmetastatic Prostate Cancer.

CONTEXT: The impact of surgeon and hospital volume on outcomes after radical prostatectomy (RP) for localised prostate cancer (PCa) remains unknown. OBJECTIVE: To perform a systematic review on the association between surgeon or hospital volume and oncological and nononcological outcomes following RP for PCa. EVIDENCE ACQUISITION: Medline, Medline In-Process, Embase, and the Cochrane Central Register of Controlled Trials were searched. All comparative studies for nonmetastatic PCa patients treated with RP published between January 1990 and May 2020 were included. For inclusion, studies had to compare hospital or surgeon volume, defined as caseload per unit time. Main outcomes included oncological (including prostate-specific antigen persistence, positive surgical margin [PSM], biochemical recurrence, local and distant recurrence, and cancer-specific and overall survival) and nononcological (perioperative complications including need for blood transfusion, conversion to open procedure and within 90-d death, and continence and erectile function) outcomes. Risk of bias (RoB) and confounding assessments were undertaken. Both a narrative and a quantitative synthesis were planned if the data allowed. EVIDENCE SYNTHESIS: Sixty retrospective comparative studies were included. Generally, increasing surgeon and hospital volumes were associated with lower rates of mortality, PSM, adjuvant or salvage therapies, and perioperative complications. Combining group size cut-offs as used in the included studies, the median threshold for hospital volume at which outcomes start to diverge is 86 (interquartile range [IQR] 35-100) cases per year. In addition, above this threshold, the higher the caseload, the better the outcomes, especially for PSM. RoB and confounding were high for most domains. CONCLUSIONS: Higher surgeon and hospital volumes for RP are associated with lower rates of PSMs, adjuvant or salvage therapies, and perioperative complications. This association becomes apparent from a caseload of >86 (IQR 35-100) per year and may further improve hereafter. Both high- and low-volume centres should measure their outcomes, make them publicly available, and improve their quality of care if needed. PATIENT SUMMARY: We reviewed the literature to determine whether the number of prostate cancer operations (radical prostatectomy) performed in a hospital affects the outcomes of surgery. We found that, overall, hospitals with a higher number of operations per year have better outcomes in terms of cancer recurrence and complications during or after hospitalisation. However, it must be noted that surgeons working in hospitals with lower annual operations can still achieve similar or even better outcomes. Therefore, making hospital's outcome data publicly available should be promoted internationally, so that patients can make an informed decision where they want to be treated.

Intraoperative Adverse Incident Classification (EAUiaiC) by the European Association of Urology ad hoc Complications Guidelines Panel.

BACKGROUND: A surgical adverse incident (AI) is defined as any deviation from the normal operative course. Current complication-grading systems mostly focus on postoperative events. OBJECTIVE: To propose an intraoperative AI classification (EAUiaiC) to facilitate reporting. DESIGN, SETTING, AND PARTICIPANTS: The classification was developed using a modified Delphi process in which experts answered two rounds of survey questionnaires organised by the European Association of Urology ad hoc Complications Guidelines Panel. Experts evaluated AI terminology using a 5-point Likert scale for clarity, exhaustiveness, hierarchical order, mutual exclusivity, clinical utility, and quality improvement. OUTCOME MEASURES AND STATISTICAL ANALYSIS: We considered ≥70% agreement for inclusion or exclusion. The resultant EAUiaiC was evaluated using ten sample clinical scenarios. Numerical and graphical statistical techniques were used to report the results. RESULTS AND LIMITATIONS: In total, 343 respondents participated. The proposed EAUiaiC system comprises eight AI grades ranging from grade 0 (no deviation and no consequence to the patient) to grade 5B (wrong surgery site or intraoperative death). In the validation stage, EAUiaiC was rated highly favourably in terms of relevance and reliability (consistency) by 126 experts. Ratings for self-reported ease of use were at acceptable levels. CONCLUSIONS: We propose a novel intraoperative AI classification (EAUiaiC) for use for urological procedures. Both the initial assessment of feasibility and the subsequent assessment of reliability suggest that it is a simple and effective tool for classifying intraoperative complications. PATIENT SUMMARY: Complications in surgery are common. It is helpful to classify complications in a uniform and objective manner so that surgeons can easily compare outcomes and learn from complications. Here we propose a new classification system for complications that occur during urological surgical procedures. An abstract of this work was presented at the 2018 congress of the European Association of Urology.

Prognostic Value of Biochemical Recurrence Following Treatment with Curative Intent for Prostate Cancer: A Systematic Review.

CONTEXT: In men with prostate cancer (PCa) treated with curative intent, controversy exists regarding the impact of biochemical recurrence (BCR) on oncological outcomes. OBJECTIVE: To perform a systematic review of the existing literature on BCR after treatment with curative intent for nonmetastatic PCa. Objective 1 is to investigate whether oncological outcomes differ between patients with or without BCR. Objective 2 is to study which clinical factors and tumor features in patients with BCR have an independent prognostic impact on oncological outcomes. EVIDENCE ACQUISITION: Medline, Medline In-Process, Embase, and the Cochrane Central Register of Controlled Trials were searched. For objective 1, prospective and retrospective studies comparing survival outcomes of patients with or without BCR following radical prostatectomy (RP) or radical radiotherapy (RT) were included. For objective 2, all studies with at least 100 participants and reporting on prognostic patient and tumor characteristics in patients with BCR were included. Risk-of-bias and confounding assessments were performed according to the Quality in Prognosis Studies tool. Both a narrative synthesis and a meta-analysis were undertaken. EVIDENCE SYNTHESIS: Overall, 77 studies were included for analysis, of which 14 addressed objective 1, recruiting 20 406 patients. Objective 2 was addressed by 71 studies with 29 057, 11 301, and 4272 patients undergoing RP, RT, and a mixed population (mix of patients undergoing RP or RT as primary treatment), respectively. There was a low risk of bias for study participation, confounders, and statistical analysis. For most studies, attrition bias, and prognostic and outcome measurements were not clearly reported. BCR was associated with worse survival rates, mainly in patients with short prostate-specific antigen doubling time (PSA-DT) and a high final Gleason score after RP, or a short interval to biochemical failure (IBF) after RT and a high biopsy Gleason score. CONCLUSIONS: BCR has an impact on survival, but this effect appears to be limited to a subgroup of patients with specific clinical risk factors. Short PSA-DT and a high final Gleason score after RP, and a short IBF after RT and a high biopsy Gleason score are the main factors that have a negative impact on survival. These factors may form the basis of new BCR risk stratification (European Association of Urology BCR Risk Groups), which needs to be validated formally. PATIENT SUMMARY: This review looks at the risk of death in men who shows rising prostate-specific antigen (PSA) in the blood test performed after curative surgery or radiotherapy. For many men, rising PSA does not mean that they are at a high risk of death from prostate cancer in the longer term. Men with PSA that rises shortly after they were treated with radiotherapy or rapidly rising PSA after surgery and a high tumor grade for both treatment modalities are at the highest risk of death. These factors may form the basis of new risk stratification (European Association of Urology biochemical recurrence Risk Groups), which needs to be validated formally.