Left-censored recurrent event analysis in epidemiological studies: a proposal for when the number of previous episodes is unknown

Background When dealing with recurrent events in observational studies it is common to include subjects who became at risk before follow-up. This phenomenon is known as left censoring, and simply ignoring these prior episodes can lead to biased and inefficient estimates. We aimed to propose a statistical method that performs well in this setting. Methods Our proposal was based on the use of models with specific baseline hazards. In this, the number of prior episodes were imputed when unknown and stratified according to whether the subject had been at risk of presenting the event before t = 0. A frailty term was also used. Two formulations were used for this “Specific Hazard Frailty Model Imputed” based on the “counting process” and “gap time.” Performance was then examined in different scenarios through a comprehensive simulation study. Results The proposed method performed well even when the percentage of subjects at risk before follow-up was very high. Biases were often below 10% and coverages were around 95%, being somewhat conservative. The gap time approach performed better with constant baseline hazards, whereas the counting process performed better with non-constant baseline hazards. Conclusions The use of common baseline methods is not advised when knowledge of prior episodes experienced by a participant is lacking. The approach in this study performed acceptably in most scenarios in which it was evaluated and should be considered an alternative in this context. It has been made freely available to interested researchers as R package miRecSurv.

An Introspective Overview of the Dynamics of Recurrent Events Data Analysis

A recurrent event remains the outcome variable of interest in many biometric studies. Recurrent events can be explained as events of defined interest that can occur to same person more than once during the study period. This study presents an overview of different pertinent recurrent models for analyzing recurrent events. Aims: To introduce, compare, evaluate and discuss pros and cons of four models in analyzing recurrent events, so as to validate previous findings in respect of the superiority or appropriateness of these models. Study Design: A comparative studies based on simulation of recurrent event models applied to a tertiary data on cancer studies. Methodology: Codes in R were implemented for simulating four recurrent event models, namely; The Andersen and Gill model; Prentice, Williams and Peterson models; Wei, Lin and Weissferd; and Cox frailty model. Finally, these models were applied to analyze the first forty subjects from a study of Bladder Cancer Tumors. The data set contained the first four repetitions of the tumor for each patient, and each recurrence time was recorded from the entry time of the patient into the study. An isolated risk interval is defined by each time to an event or censoring. Results: The choice and usage of any of the models lead to different conclusions, but the choice depends on: risk intervals; baseline hazard; risk set; and correlation adjustment or simplistically, type of data and research question. The PWP-GT model could be used if the research question is focused on whether treatment was effective for the event since the previous event happened. However, if the research question is designed to find out whether treatment was effective for the event since the start of treatment, then we could use the PWP- TT. The AG model will be adequate if a common baseline hazard could be assumed, but the model lacks the details and versatility of the event-specific models. The WLW model is very suitable for data with diverse events for the same person, which underscores a potentially different baseline hazard for each type. Conclusion: PWP-GT has proven to be the most useful model for analyzing recurrent event data.

Recurrent ST-Elevation Myocardial Infarction: Case Report of A Rare Complication of Caseous Mitral Annular Calcification

Background Caseous mitral annular calcification is an under-diagnosed division of calcific mitral valve disease that has recently been reported to have increased propensity for embolic disease. Early recognition of this entity as a cause of embolic disease can lead to prevention of occlusive vascular disease and long-standing complications. Case Summary We present the case of a patient with end-stage renal disease who presented for evaluation of chest pain and was found to have ST-segment myocardial infarction. Despite thrombectomy and stenting, he had multiple recurrent events, and imaging evaluation demonstrated caseous mitral annular calcification with mobile components. He was taken for surgical replacement of the mitral valve, with pathology confirming diagnosis. Discussion Caseous mitral annular calcification may represent an increased risk of embolic disease. Better understanding of this pathology and it’s propensity for embolic disease will be important to best determine treatment plans and timing of operative intervention.

Pertussis immunisation in infancy and atopic outcomes: A protocol for a population-based cohort study using linked administrative data

Introduction The burden of IgE-mediated food allergy in Australian born children is reported to be among the highest globally. This illness shares risk factors and frequently coexists with asthma, one of the most common noncommunicable diseases of childhood. Findings from a case-control study suggest that compared to immunisation with acellular pertussis vaccine, early priming of infants with whole-cell pertussis vaccine may be associated with a lower risk of subsequent IgE-mediated food allergy. If whole-cell vaccination is protective of food allergy and other atopic diseases, especially if protective against childhood asthma, the population-level effects could justify its preferential recommendation. However, the potential beneficial effects of whole-cell pertussis vaccination for the prevention of atopic diseases at a population-scale are yet to be investigated. Methods and analysis Analyses of population-based record linkage data will be undertaken to compare the rates of admissions to hospital for asthma in children aged between 5 and 15 years old, who were born in Western Australia (WA) or New South Wales (NSW) between 1997 and 1999 (329,831) when pertussis immunisation in Australia transitioned from whole-cell to acellular only schedules. In the primary analysis we will estimate hazard ratios and 95% confidence intervals for the time-to-first-event (hospital admissions as above) using Cox proportional hazard models in recipients of a first dose of whole-cell versus acellular pertussis-containing vaccine before 112 days old (~4 months of age). Similarly, we will also fit time-to-recurrent events analyses using Andersen-Gill models, and robust variance estimates to account for potential within-child dependence. Hospitalisations for all-cause anaphylaxis, food anaphylaxis, venom, all-cause urticaria and atopic dermatitis will also be examined in children who received at least one dose of pertussis-containing vaccine by the time of the cohort entry, using analogous statistical methods. Presentations to the emergency departments will be assessed separately using the same statistical approach.

The incidence and predictors of new brain metastases in patients with non–small cell lung cancer following discontinuation of systemic therapy

OBJECTIVE Patients with non–small cell lung cancer (NSCLC) metastatic to the brain are living longer. The risk of new brain metastases when these patients stop systemic therapy is unknown. The authors hypothesized that the risk of new brain metastases remains constant for as long as patients are off systemic therapy. METHODS A prospectively collected registry of patients undergoing radiosurgery for brain metastases was analyzed. Of 606 patients with NSCLC, 63 met the inclusion criteria of discontinuing systemic therapy for at least 90 days and undergoing active surveillance. The risk factors for the development of new tumors were determined using Cox proportional hazards and recurrent events models. RESULTS The median duration to new brain metastases off systemic therapy was 16.0 months. The probability of developing an additional new tumor at 6, 12, and 18 months was 26%, 40%, and 53%, respectively. There were no additional new tumors 22 months after stopping therapy. Patients who discontinued therapy due to intolerance or progression of the disease and those with mutations in RAS or receptor tyrosine kinase (RTK) pathways (e.g., KRAS, EGFR) were more likely to develop new tumors (hazard ratio [HR] 2.25, 95% confidence interval [CI] 1.33–3.81, p = 2.5 × 10−3; HR 2.51, 95% CI 1.45–4.34, p = 9.8 × 10−4, respectively). CONCLUSIONS The rate of new brain metastases from NSCLC in patients off systemic therapy decreases over time and is uncommon 2 years after cessation of cancer therapy. Patients who stop therapy due to toxicity or who have RAS or RTK pathway mutations have a higher rate of new metastases and should be followed more closely.

Overview towards improved understanding of the mechanisms leading to heavy precipitation in the western Mediterranean: lessons learned from HyMeX

Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean (WMed). Every year, recurrent events affect the area with fatal consequences for infrastructure and personal losses. Despite this being a well-known issue widely investigated in the past, open questions still remain. Particularly, the understanding of the underlying mechanisms and the modeling representation of the events must be improved. One of the major goals of the Hydrological Cycle in the Mediterranean Experiment (HyMeX; 2010–2020) has been to advance knowledge on this topic. In this article, we present an overview of the most recent lessons learned from HyMeX towards an improved understanding of the mechanisms leading to HP in the WMed. The unique network of instruments deployed as well as the use of finer model resolutions and coupled models provided an unprecedented opportunity to validate numerical model simulations, develop improved parameterizations, and design high-resolution ensemble modeling approaches and sophisticated assimilation techniques across scales. All in all, HyMeX, and particularly the science team heavy precipitation, favored the evidencing of theoretical results, the enrichment of our knowledge on the genesis and evolution of convection in a complex topography environment, and the improvement of precipitation forecasts. Illustratively, the intervention of cyclones and warm conveyor belts in the occurrence of heavy precipitation has been pointed out, and the crucial role of the spatiotemporal distribution of atmospheric water vapor for the understanding and accurate forecast of the timing and location of deep convection has been evidenced, as has the complex interaction among processes across scales. The importance of soil and ocean conditions and the interactions among systems were highlighted, and such systems were specifically developed in the framework of HyMeX to improve the realism of weather forecasts. Furthermore, the benefits of cross-disciplinary efforts within HyMeX have been a key asset in bringing our knowledge about heavy precipitation in the Mediterranean region a step forward.

Bayesian inference on the number of recurrent events: A joint model of recurrence and survival

The number of recurrent events before a terminating event is often of interest. For instance, death terminates an individual’s process of rehospitalizations and the number of rehospitalizations is an important indicator of economic cost. We propose a model in which the number of recurrences before termination is a random variable of interest, enabling inference and prediction on it. Then, conditionally on this number, we specify a joint distribution for recurrence and survival. This novel conditional approach induces dependence between recurrence and survival, which is often present, for instance, due to frailty that affects both. Additional dependence between recurrence and survival is introduced by the specification of a joint distribution on their respective frailty terms. Moreover, through the introduction of an autoregressive model, our approach is able to capture the temporal dependence in the recurrent events trajectory. A non-parametric random effects distribution for the frailty terms accommodates population heterogeneity and allows for data-driven clustering of the subjects. A tailored Gibbs sampler involving reversible jump and slice sampling steps implements posterior inference. We illustrate our model on colorectal cancer data, compare its performance with existing approaches and provide appropriate inference on the number of recurrent events.

Analysis of Recurrent Events with Associated Informative Censoring: Application to HIV Data

In this study, we adapt a Cox-based model for recurrent events; the Prentice, Williams and Peterson Total -Time (PWP-TT) that has largely, been used under the assumption of non-informative censoring and evaluate it under an informative censoring setting. Empirical evaluation was undertaken with the aid of the semi-parametric framework for recurrent events suggested by Huang [1] and implemented in R Studio software. For validation we used data from a typical HIV care setting in Kenya. Of the three models under consideration; the standard Cox Model had gender hazard ratio (HR) of 0.66 (p-value=0.165), Andersen-Gill had HR 0.46 (with borderline p-value=0.054) and extended PWP TT had HR 0.22 (p-value=0.006). The PWP-TT model performed better as compared to other models under informative setting. In terms of risk factors under informative setting, LTFU due to stigma; gender [base=Male] had HR 0.544 (p-value =0.002), age [base is < 37] had HR 0.772 (p-value=0.008), ART regimen [base= First line] had HR 0.518 (p-value= 0.233) and differentiated care model (Base=not on DCM) had HR 0.77(p-value=0.036). In conclusion, in spite of the multiple interventions designed to address incidences of LTFU among HIV patients, within-person cases of LTFU are usually common and recurrent in nature, with the present likelihood of a person getting LTFU influenced by previous occurrences and therefore informative censoring should be checked.

NCMP-16. MANAGEMENT AND LONG-TERM OUTCOMES OF PATIENTS WITH RECURRENT STROKE-LIKE EPISODES AFTER CRANIAL RADIOTHERAPY

Stroke-Like Migraine Attacks after Radiation Therapy (SMART) is a descriptive clinical entity consisting of transient hemispheric dysfunction. We were interested in pragmatic management patterns for patients with Recurrent Stroke-Like Episodes (R-SLE) of transient negative neurologic symptoms after cranial radiotherapy (RT) to define optimal management strategy and assess long-term outcomes. We conducted a retrospective review of all patients with recurrent negative neurologic symptoms after cranial RT who were treated at Mayo Clinic (Rochester), with follow-up extending until February 2021. Descriptive statistics and Chi-Square analysis was performed to assess for differences between patients with clinical cessation of symptoms, death, progressive encephalopathy and therapeutic class, patient and primary treatment characteristics (i.e. whole brain RT). We identified 27 patients with R-SLE after RT. 25 patients were included in analyses. Median age at diagnosis was 28.7 years (3.0-65.8 years, SD: 15.0 years). Median time from RT to symptom onset was 14.6 years (3.3-30.5 years, SD: 8.9 years). The most common presentations included hemiparesis (55.6%), hemisensory loss (22.2%), transient visual field loss (33.3%), encephalopathy (18.5%), and aphasia (22.2%). Antiseizure medications were most used for management of R-SLE (92%) followed by anti-platelets (68%), verapamil (52%), statins (48%), glucocorticoids (24%), antivirals (20%), and ACE inhibitors/angiotensin receptor blockers (16%). Beta blockers were not used. Verapamil use was frequently associated with clinical cessation of recurrent events with cessation being achieved in 64.7% of patients on verapamil versus 35.3% not on verapamil (p=0.0638). Other medical interventions did not approach clinical or statistical significance. Progressive encephalopathy was more common in patients without clinical cessation (87.5% vs. 23.5%, p=0.0026). All patients who died at last follow-up had progressive encephalopathy. We found cessation of recurrent negative neurologic symptoms after cranial RT in most patients. Verapamil use was associated with clinical cessation. Progressive encephalopathy was more common in patients without clinical cessation of recurrent events.