Causal Inference When Counterfactuals Depend on the Proportion of All Subjects Exposed

The assumption that no subject's exposure affects another subject's outcome, known as the no-interference assumption, has long held a foundational position in the study of causal inference. However, this assumption may be violated in many settings, and in recent years has been relaxed considerably. Often this has been achieved with either the aid of a known underlying network, or the assumption that the population can be partitioned into separate groups, between which there is no interference, and within which each subject's outcome may be affected by all the other subjects in the group via the proportion exposed (the stratified interference assumption). In this paper, we instead consider a complete interference setting, in which each subject affects every other subject's outcome. In particular, we make the stratified interference assumption for a single group consisting of the entire sample. This can occur when the exposure is a shared resource whose efficacy is modified by the number of subjects among whom it is shared. We show that a targeted maximum likelihood estimator for the i.i.d.~setting can be used to estimate a class of causal parameters that includes direct effects and overall effects under certain interventions. This estimator remains doubly-robust, semiparametric efficient, and continues to allow for incorporation of machine learning under our model. We conduct a simulation study, and present results from a data application where we study the effect of a nurse-based triage system on the outcomes of patients receiving HIV care in Kenyan health clinics.Comment: 23 pages main article, 23 pages supplementary materials + references, 4 tables, 1 figur

Follicle Stimulating Hormone is an accurate predictor of azoospermia in childhood cancer survivors

Funding: RTM is supported by a Wellcome Trust Intermediate Clinical Fellowship (grant no: 098522), https://wellcome.ac.uk/what-we-do/directories/intermediate-clinical-fellowships-people-funded. TWK is supported by Engineering and Physical Sciences Research Council grant EP/P015638/1, http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/P015638/1.The accuracy of Follicle Stimulating Hormone as a predictor of azoospermia in adult survivors of childhood cancer is unclear, with conflicting results in the published literature. A systematic review and post hoc analysis of combined data (n = 367) were performed on all published studies containing extractable data on both serum Follicle Stimulating Hormone concentration and semen concentration in survivors of childhood cancer. PubMed and Medline databases were searched up to March 2017 by two blind investigators. Articles were included if they contained both serum FSH concentration and semen concentration, used World Health Organisation certified methods for semen analysis, and the study participants were all childhood cancer survivors. There was no evidence for either publication bias or heterogeneity for the five studies. For the combined data (n = 367) the optimal Follicle Stimulating Hormone threshold was 10.4 IU/L with specificity 81% (95% CI 76%–86%) and sensitivity 83% (95% CI 76%–89%). The AUC was 0.89 (95%CI 0.86–0.93). A range of threshold FSH values for the diagnosis of azoospermia with their associated sensitivities and specificities were calculated. This study provides strong supporting evidence for the use of serum Follicle Stimulating Hormone as a surrogate biomarker for azoospermia in adult males who have been treated for childhood cancer.Publisher PDFPeer reviewe

Long-term treatment of osteoporosis: safety and efficacy appraisal of denosumab

Athanasios D Anastasilakis,1 Konstantinos A Toulis,1 Stergios A Polyzos,2 Chrysostomos D Anastasilakis,3 Polyzois Makras41Department of Endocrinology, 424 General Military Hospital, 2Second Medical Clinic, Medical School, Aristotle University of Thessaloniki, Ippokration Hospital, 3Department of Pharmacology, 424 General Military Hospital, Thessaloniki; 4Department of Endocrinology and Diabetes, 251 Hellenic Air Force and VA General Hospital, Athens, GreeceAbstract: Denosumab is a fully human monoclonal antibody to the receptor activator of nuclear factor-κB ligand (RANKL), a member of the tumor necrosis factor receptor superfamily essential for osteoclastogenesis. Denosumab treatment is associated with a rapid, sustained, and reversible reduction in bone turnover markers, a continuous marked increase in bone mineral density at all sites, and a marked decrease in the risk of vertebral, hip, and nonvertebral fractures in women with postmenopausal osteoporosis. Therefore, it could be considered as an effective alternative to previous bisphosphonate treatment as well as first-line treatment of severe osteoporosis. Cost-effectiveness studies support this suggestion. In addition, denosumab seems to be the safest treatment option in patients with impaired renal function. Denosumab is characterized by reversibility of its effect after treatment discontinuation, in contrast with bisphosphonates. Large-scale clinical trials, including the extension of FREEDOM trial for up to 5 years, are reassuring for its safety. However, given its brief post-market period, vigilance regarding adverse events related to putative RANKL inhibition in tissues other than bone, as well as those related to bone turnover oversuppression, is advised.Keywords: adverse event, denosumab, efficacy, fracture, osteoporosis, safet