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Marleen MHJ van Gelder,1 Pim Beekers,1,2 Yrea RJ van Rijt-Weetink,3 Joris van Drongelen,4 Nel Roeleveld,1 Luc JM Smits5 1Department for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands; 2National Health Care Institute, Diemen, the Netherlands; 3Netherlands Pharmacovigilance Centre Lareb,‘s-Hertogenbosch, the Netherlands; 4Department of Obstetrics & Gynecology, Radboud University Medical Center, Nijmegen, the Netherlands; 5Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the NetherlandsCorrespondence: Marleen MHJ van Gelder, Department for Health Evidence (HP 133), Radboud University Medical Center, P.O. Box 9101, Nijmegen, 6500 HB, the Netherlands, Tel +31 24 3615305, Fax +31 24 3613505, Email Marleen.vanGelder@radboudumc.nlPurpose: Preeclampsia is a leading cause of maternal morbidity and mortality. Calcium-based antacids and proton pump inhibitors (PPIs) are commonly used during pregnancy to treat symptoms of gastroesophageal reflux disease. Both have been hypothesized to reduce the risk of preeclampsia. We determined associations of calcium-based antacid and PPI use during pregnancy with late-onset preeclampsia (≥ 34 weeks of gestation), taking into account dosage and timing of use.Patients and Methods: We included 9058 pregnant women participating in the PRIDE Study (2012– 2019) or The Dutch Pregnancy Drug Register (2014– 2019), two prospective cohorts in The Netherlands. Data were collected through web-based questionnaires and obstetric records. We estimated risk ratios (RRs) for late-onset preeclampsia for any use and trajectories of calcium-based antacid and PPI use before gestational day 238, and hazard ratios (HRs) for time-varying exposures after gestational day 237.Results: Late-onset preeclampsia was diagnosed in 2.6% of pregnancies. Any use of calcium-based antacids (RR 1.2 [95% CI 0.9– 1.6]) or PPIs (RR 1.4 [95% CI 0.8– 2.4]) before gestational day 238 was not associated with late-onset preeclampsia. Use of low-dose calcium-based antacids in gestational weeks 0– 16 (< 1 g/day; RR 1.8 [95% CI 1.1– 2.9]) and any use of PPIs in gestational weeks 17– 33 (RR 1.6 [95% CI 1.0– 2.8]) seemed to increase risks of late-onset preeclampsia. We did not observe associations between late-onset preeclampsia and use of calcium-based antacids (HR 1.0 [95% CI 0.6– 1.5]) and PPIs (HR 1.4 [95% CI 0.7– 2.9]) after gestational day 237.Conclusion: In this prospective cohort study, use of calcium-based antacids and PPIs during pregnancy was not found to reduce the risk of late-onset preeclampsia.Keywords: extended Cox models, gestational hypertension, gastroesophageal reflux disease, longitudinal clustering methods, PRIDE study, The Dutch Pregnancy Drug Register

Cancer has affected around eighteen million people all over the world in 2018. In Portugal, cancer was diagnosed in sixty thousand individuals during 2018, being the second leading cause of death (one in every four deaths). Following the European Directive 2011/24/EU, the Portuguese Health System has been recognizing oncology Reference Centres (RCs), which are focused on delivering best-in-class treatment for cancer patients. This paper performs a survival analysis of cancer patients in Portugal, having hospital episodes with discharge date after the official recognition, in 2016, of the first RCs for hepatobiliary, pancreatic, sarcomas and oesophageal cancer. The aim is to assess the impact of RCs on the survival probability of these patients. For each cancer type, survival curves are estimated using the Kaplan–Meier methodology, and hazard ratios are estimated for different covariates, using multivariate Extended Cox models. The results obtained support the implementation and encourage the further extension of the RC model for oncology in Portugal, as cancer patients treated in an oncology RC, overall, have a better survival probability when compared to patients who had no episode in an RC. These results are clearer for hepatobiliary and pancreatic cancer, but also visible for sarcomas and oesophageal cancer. [ABSTRACT FROM AUTHOR]

Background: As the vaccination campaign against COVID-19 progresses, it becomes crucial to comprehend the lasting effects of vaccination on safeguarding against new infections or reinfections., Objective: This study aimed to assess the risk of new SARS-CoV-2 infections based on the number of vaccine doses, prior infections, and other clinical characteristics., Methods: We defined a cohort of 800 health care workers in a 24-month study (March 2020 to December 2022) in northern Barcelona to determine new infections by SARS-CoV-2. We used extended Cox models, specifically Andersen-Gill (AG) and Prentice-Williams-Peterson, and we examined the risk of new infections. The AG model incorporated variables such as sex, age, job title, number of chronic conditions, vaccine doses, and prior infections. Additionally, 2 Prentice-Williams-Peterson models were adjusted, one for those individuals with no or 1 infection and another for those with 2 or 3 infections, both with the same covariates as the AG model., Results: The 800 participants (n=605, 75.6% women) received 1, 2, 3, and 4 doses of the vaccine. Compared to those who were unvaccinated, the number of vaccine doses significantly reduced (P<.001) the risk of infection by 66%, 81%, 89%, and 99%, respectively. Unit increase in the number of prior infections reduced the risk of infection by 75% (P<.001). When separating individuals by number of previous infections, risk was significantly reduced for those with no or 1 infection by 61% (P=.02), and by 88%, 93%, and 99% (P<.001) with 1, 2, 3, or 4 doses, respectively. In contrast, for those with 2 or 3 previous infections, the reduction was only significant with the fourth dose, at 98% (P<.001). The number of chronic diseases only increased the risk by 28%-31% (P<.001) for individuals with 0-1 previous infections., Conclusions: The study suggests that both prior infections and vaccination status significantly contribute to SARS-CoV-2 immunity, supporting vaccine effectiveness in reducing risk of reinfection for up to 24 months after follow-up from the onset of the pandemic. These insights contribute to our understanding of long-term immunity dynamics and inform strategies for mitigating the impact of COVID-19., (© Pere Torán-Monserrat, Noemí Lamonja-Vicente, Anna Costa-Garrido, Lucía A Carrasco-Ribelles, Bibiana Quirant, Marc Boigues, Xaviera Molina, Carla Chacón, Rosalia Dacosta-Aguayo, Fernando Arméstar, Eva María Martínez Cáceres, Julia G Prado, Concepción Violán, ProHEpiC-19 study group. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org).)

The repeated occurrence of the same event in a process is commonly observed in many domains. Such events are referred to as recurrent events. The time to occurrence of these repeated events varies from unit to unit with a possibility of events not occurring among some of the units. Invariably such data are dealt with using some of the techniques in survival analysis called recurrent event models, which are commonly encountered in epidemiological studies and clinical trials. However, it applies to other domains in science and technology. We illustrate the usefulness of recurrent event models in the context of defect proneness analysis in quality assessment of software. Some of the models in practice are introduced on data collected to study the impact of module size on defect proneness in the Mozilla product. Module size plays a significant role in defect proneness and each defect fix makes the class more susceptible to further defects. The risk estimates obtained from the different models vary owing to the differences in the properties of the models as well as the assumptions underlying it. [ABSTRACT FROM AUTHOR]

Summary: When the same type of event is experienced by a subject more than once it is called recurrent event, which possess two important characteristics, namely "within‐subject correlation" and "time‐varying covariate." As a result, the traditional statistical methods do not work well on recurrent event data. Over the past few decades, many alternatives methods have been proposed for the analysis of recurrent event data. In this article, the six most prominent methods for recurrent event analysis have been compared on pediatric asthma data. Three variance corrected models (viz "Anderson and Gill [AG] model," "Prentice, William, and Peterson‐Counting Process [PWP‐CP] model," and "Prentice, William, and Peterson‐Gap Time [PWP‐GT] model") and three corresponding frailty variants (AG‐frailty, PWP‐CP‐frailty, and PWP‐GT‐frailty) were compared using three mathematical criterion (AIC, BIC, and log‐likelihood) and one graphical criteria (Cox‐Snell goodness of fit, visual test). All model comparison indices showed the PWP‐GT model as the most appropriate model on asthma data over other models. By using PWP‐GT model, seven predictors of asthma exacerbation (viz "abdominal pain at previous visit," "Z5 (%) at previous visit," "diagnosis of asthma at previous visit," "calendar month of exacerbation," "history of maternal asthma," "monthly per capita income," and "emotional stress") were identified. The PWP‐GT model was identified as the most appropriate model over other models on pediatrics asthma data. [ABSTRACT FROM AUTHOR]

Introduction: Repair of Tympanic Membrane (TM) is one of the most common surgeries performed by the otologists. Literature reveals that Indian surgeons have contributed substantially in the research on techniques and graft materials used for the repair of tympanic membrane, though no review has been written so far highlighting their contributions. Aim: To summarize and analyse the contributions of Indian authors who have used different graft materials for repair of TM and their studies listed in Medline search. Materials and Methods: A literature review was conducted using a Medline search using keywords of ‘myringoplasty’ and ‘tympanoplasty’ with ‘India’ on 30th June 2016. A total of 243 articles were found listed onwards from year 1998. Out of these 50 articles in which type 1 tympanoplasty or myringoplasty was performed using different graft materials were selected. The content of each abstract was studied in order to identify studies related to topic. Results: Authors have experimented with a variety of tissues as graft materials. Temporalis Fascia (TF) has been most widely used in 58.6% studies as graft material. The next popular graft is tragal perichondrium. The graft take up rates varied from 68.5% to 100%, while method of reporting of hearing gain in most studies was inconsistent amongst studies, though most studies have reported achievement of serviceable hearing of < 25 dB in most patients. Conclusion: TF was the most prefered material due to anatomic proximity, light material and strength. It was followed in popularity by tragal perichondrium and tragal cartilage. All graft materials have given satisfactory hearing results.

Survival data is a special form of time to event data that is often encountered while modelling risk. The classical Cox proportional hazard model, that is popularly used to analyse survival data, cannot be used for modelling risk when the proportional hazard assumption is violated or when there is recurrent time to event data. In this context we conducted this narrative review to develop an algorithm for selection of advanced methods of analysing survival data in the above-mentioned situations. Findings were synthesized from literature retrieved from searches of Pubmed, Embase, and Google Scholar. Existing literature suggest that for non-proportionality, especially due to categorical predictors stratified Cox model may be useful. An accelerated failure time model is applicable in case of different follow-up time among different experimental groups and the median time to event is the outcome of interest instead of hazard. Extended Cox models and marginal models are used in case of multivariate ordered failure events and the type of model depends upon the presence of clustering and nature of ordering. In the presence of heterogeneity, a shared frailty model is used that is analogous to mixed models. More advanced models, including competing risk and multistate models are required for modelling competing risk, multiple states and multiple transitions. Joint models are used for multiple time dependent outcomes with different attributes. We have developed an algorithm based on the review for appropriate model selection to curb the challenge of modeling survival data and the algorithm is expected to help the naïve researchers in analysing survival data.

Introduction: Repair of Tympanic Membrane (TM) is one of the most common surgeries performed by the otologists. Literature reveals that Indian surgeons have contributed substantially in the research on techniques and graft materials used for the repair of tympanic membrane, though no review has been written so far highlighting their contributions., Aim: To summarize and analyse the contributions of Indian authors who have used different graft materials for repair of TM and their studies listed in Medline search., Materials and Methods: A literature review was conducted using a Medline search using keywords of 'myringoplasty' and 'tympanoplasty' with 'India' on 30th June 2016. A total of 243 articles were found listed onwards from year 1998. Out of these 50 articles in which type 1 tympanoplasty or myringoplasty was performed using different graft materials were selected. The content of each abstract was studied in order to identify studies related to topic., Results: Authors have experimented with a variety of tissues as graft materials. Temporalis Fascia (TF) has been most widely used in 58.6% studies as graft material. The next popular graft is tragal perichondrium. The graft take up rates varied from 68.5% to 100%, while method of reporting of hearing gain in most studies was inconsistent amongst studies, though most studies have reported achievement of serviceable hearing of < 25 dB in most patients., Conclusion: TF was the most prefered material due to anatomic proximity, light material and strength. It was followed in popularity by tragal perichondrium and tragal cartilage. All graft materials have given satisfactory hearing results.

Survival data is a special form of time to event data that is often encountered while modelling risk. The classical Cox proportional hazard model, that is popularly used to analyse survival data, cannot be used for modelling risk when the proportional hazard assumption is violated or when there is recurrent time to event data. In this context we conducted this narrative review to develop an algorithm for selection of advanced methods of analysing survival data in the above-mentioned situations. Findings were synthesized from literature retrieved from searches of Pubmed, Embase, and Google Scholar. Existing literature suggest that for non-proportionality, especially due to categorical predictors stratified Cox model may be useful. An accelerated failure time model is applicable in case of different follow-up time among different experimental groups and the median time to event is the outcome of interest instead of hazard. Extended Cox models and marginal models are used in case of multivariate ordered failure events and the type of model depends upon the presence of clustering and nature of ordering. In the presence of heterogeneity, a shared frailty model is used that is analogous to mixed models. More advanced models, including competing risk and multistate models are required for modelling competing risk, multiple states and multiple transitions. Joint models are used for multiple time dependent outcomes with different attributes. We have developed an algorithm based on the review for appropriate model selection to curb the challenge of modeling survival data and the algorithm is expected to help the naïve researchers in analysing survival data.