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Background: The objective of this study was to explore the abilities of atezolizumab plus chemotherapy in preventing brain metastases (BMs) among metastatic non–small cell lung cancer (NSCLC) without initial BMs, as well as the risk factors of BMs. Methods: Individual patient data from three trials involving first‐line atezolizumab for metastatic NSCLC (IMpower130, IMpower131, and IMpower150) were pooled. Among patients without baseline BMs and without epidermal growth factor receptor (EGFR) and/or anaplastic lymphoma kinase (ALK) mutations, those receiving atezolizumab + chemotherapy ± bevacizumab were classified as the atezolizumab plus chemotherapy group and those receiving placebo + chemotherapy ± bevacizumab were classified as the chemotherapy group. The cumulative incidences of BM (CI‐BMs) between the two groups were compared. Other factors associated with the CI‐BM were analyzed by Cox regression analyses. Results: With a median follow‐up of 17.6 months (range, 0.03–33.64 months), 74 (3.1%) of the 2380 enrolled patients developed BMs, including 50 (3.1%) and 24 (3.0%) in the atezolizumab plus chemotherapy group (n = 1589) and the chemotherapy group (n = 791), respectively. The CI‐BMs at 6, 12, and 24 months were 1.7%, 2.8%, and 3.3%, respectively. After taking competing risk events into account, there was no significant difference in the CI‐BMs between the two groups (p =.888). Nevertheless, the use of bevacizumab and the histology of nonsquamous NSCLC were found to be independently associated with the risk of BMs. Conclusions: In patients with metastatic EGFR/ALK wild‐type NSCLC without baseline BMs, adding atezolizumab in the first‐line treatment might not reduce the CI‐BM. However, the administration of bevacizumab may reduce the risk of BMs. In patients with metastatic EGFR/ALK wild‐type non–small cell lung cancer without baseline brain metastases (BMs), adding atezolizumab in the first‐line treatment could not reduce the cumulative incidence of BM. However, administration of bevacizumab may reduce the risk of BMs. [ABSTRACT FROM AUTHOR]

Data on retrospective compensation claims for injuries caused by pharmaceutical drugs are prone to selection and reporting biases. Nevertheless, this case study of the antidiabetic drug benfluorex shows that such data can be used to estimate the cumulative incidence of drug‐related injury, and to provide insights into its epidemiology. To this end, we develop a modelling framework for under‐reporting of retrospective claims for compensation arising from drug damage. The model involves a longitudinal component related to attrition of cases over time, and a cross‐sectional component related to incomplete reporting. We apply this model to cardiac valve surgery necessitated by exposure to benfluorex. Benfluorex was marketed in France between 1976 and 2009, when it was withdrawn because it caused valvular heart disease. A scandal erupted in 2010 over the scale of the damage caused by the drug. Since then, no further estimates of cumulative incidence have been published, though thousands of claims for compensation have been processed. The analysis combines compensation claims data and sociological survey data on benfluorex users, together with data on benfluorex sales and duration of treatment. We find a threshold of toxicity at about 6 months' exposure, and that at least 1690 individuals (95% CI 1290 to 2320) needed heart surgery to replace or repair valves damaged by exposure to benfluorex in France: a cumulative incidence of 3.68 per 10,000 (95% CI 2.68 to 5.34) benfluorex users or 3.22 per 10,000 (95% CI 2.48 to 4.39) person‐years at risk above the exposure threshold. While these findings are tentative, they are consistent with those obtained previously using very different methods. [ABSTRACT FROM AUTHOR]

Influenza infection is associated with cardiovascular complications that range significantly in presentation and severity. The cumulative incidence of cardiovascular complications due to laboratory‐confirmed influenza, however, is not reported in the literature. We conducted a systematic review and random‐effects meta‐analysis to evaluate the cumulative incidence and mortality rate of influenza virus‐related cardiovascular complications in hospitalized patients. We searched the PubMed and EMBASE databases for studies reporting acute myocardial infarction (AMI), heart failure (HF), arrhythmia of any kind, stroke or transient ischemic attack (TIA), and myocarditis in hospitalized patients with laboratory‐confirmed influenza virus infection. Prospective studies, retrospective cohort studies, and randomized controlled trials (RCTs) were included in the analysis. We followed the PRISMA checklist and used 95% confidence intervals (CIs) to report meta‐analysis outcomes. This study was registered on PROSPERO (CRD42023427849). After retrieving 2803 studies, we identified 19 studies (18 observational and 1 RCT) with relevant data, and we included 6936 patients in our analysis, of whom 690 (9.9%) developed a cardiovascular outcome of interest. The cumulative incidence of HF was 17.47% (95% CI: 5.06%–34.54%), arrhythmia of any kind 6.12% (95% CI: 0.00%–21.92%), myocarditis 2.56% (95% CI: 0.66%–5.38%), AMI 2.19% (95% CI: 1.03%–3.72%), and stroke or TIA 1.14% (95% CI: 0.00%–4.05%). The in‐hospital mortality rate from cardiovascular events was 1.38% (95% CI: 0.00%–4.80%). Cardiovascular complications occur in patients with influenza virus infection, with the cumulative incidence of specific cardiac manifestations varying considerably (1.51%–17.47%). Preventive strategies and close clinical monitoring after infection remain a priority. [ABSTRACT FROM AUTHOR]

Background and purpose: Idiopathic Parkinson's disease (IPD) is a progressive neurodegenerative disorder that is strongly associated with age. The aim of the present study was to describe current sex‐ and age‐specific trends and regional differences in the incidence of IPD diagnosed in older people in Germany. Methods: This study was based on nationwide outpatient claims and drug prescription data from the German Statutory Health Insurance, covering approximately 87% of the general population. We conducted a cohort study in patients aged 50 years or older with observation time of at least 4 years. To assess the robustness of nationwide annual IPD incidence trends from 2013 to 2019, three case definitions with varying levels of stringency regarding coded outpatient diagnoses and drug prescriptions were applied. Results: In 2019, the population at risk comprised 30,575,726 persons. Using the primary and most specific case definition, annual age‐ and sex‐standardized cumulative IPD incidence decreased stepwise from 137 (2013) to 106 (2019) new cases per 100,000 persons. The decline in incidence was seen in both sexes, in all age groups and in the majority of German regions. The relative decrease (2013–2019) in the annual age‐ and sex‐standardized IPD incidence varied from 23% to 28% among case definitions. Conclusion: Our findings indicate a nationwide decline in the age‐ and sex‐standardized incidence of IPD from 2013 to 2019 in Germany. This trend was consistent using different case definitions. Further research is needed to elucidate the factors underlying this trend. [ABSTRACT FROM AUTHOR]

Methotrexate (MTX)‐associated lymphoproliferative disorder (MTX‐LPD) is a troublesome problem in patients receiving MTX for rheumatoid arthritis (RA). However, its incidence, prognosis, and risk factors remain unclear. In this retrospective study, we evaluated the actual incidence, prognostic impact, and risk factors of MTX‐LPD. Of the 986 patients with RA treated with MTX, 90 patients experienced 95 new malignancies (NMs), with LPD as the most frequent in 26 patients. The cumulative LPD incidences were 1.3% and 4.7% at 5 and 10 years after MTX initiation, respectively. Among the 24 patients who discontinued MTX after developing LPD, 15 showed sustained regression, without difference in overall survival between patients with LPD and without NM. Inflammatory markers and absolute lymphocyte counts were not useful for early LPD development detection, but most of the patients with LPD had persistently elevated erythrocyte sedimentation ratios. Regarding concomitant drugs, tacrolimus increased the risk only if patients were not receiving biological disease‐modifying antirheumatic drugs (bDMARDs). bDMARDs did not increase the risk for any of the drugs or the number of classes used. The number of LPD cases was lower in patients with IL‐6A even after a long period after MTX, although with no statistically significant difference. Thus, approximately 1 in 20 patients with RA developed MTX‐LPD over the 10 years of MTX treatment, but it did not affect the survival of patients with RA. Tacrolimus increased the risk of developing LPD for certain patients and should be used with caution. [ABSTRACT FROM AUTHOR]

Competing risks data are commonly encountered in randomized clinical trials or observational studies. Ignoring competing risks in survival analysis leads to biased risk estimates and improper conclusions. Often, one of the competing events is of primary interest and the rest competing events are handled as nuisances. These approaches can be inadequate when multiple competing events have important clinical interpretations and thus of equal interest. For example, in COVID‐19 in‐patient treatment trials, the outcomes of COVID‐19 related hospitalization are either death or discharge from hospital, which have completely different clinical implications and are of equal interest, especially during the pandemic. In this paper we develop nonparametric estimation and simultaneous inferential methods for multiple cumulative incidence functions (CIFs) and corresponding restricted mean times. Based on Monte Carlo simulations and a data analysis of COVID‐19 in‐patient treatment clinical trial, we demonstrate that the proposed method provides global insights of the treatment effects across multiple endpoints. [ABSTRACT FROM AUTHOR]

Objectives: To investigate if the risk of prostate cancer (PC) differs based on the order of primary PC diagnosed in first‐degree relatives (FDRs) given possibly different risk factors for PC as first primary cancer (PCa‐1) and second primary cancer (PCa‐2). Subjects and Methods: In this Swedish nationwide cohort, PC diagnosis was followed for among 149,985 men with one FDR affected by PCa‐1, 10,972 with one FDR affected by PCa‐2 and 2,896,561 without any FDRs affected by cancer in a maximum of 57 years. PC patients were further followed for death due to PC since diagnosis. Relative risk (RR) of PC was estimated with Poisson regression and hazard ratio (HR) with Cox proportional hazard model. Results: Compared to men without any FDRs affected by cancer, the RRs of PC in men with one FDR affected by PCa‐1 and PCa‐2 were 2.12 (95% confidence interval [CI]: 2.07–2.17) and 1.69 (1.54–1.85), respectively. The risk in men with one FDR affected by PCa‐2 was significantly lower than those with one FDR affected by PCa‐1 after additionally adjusting for family relationship (father‐son and brothers) and age at diagnosis of PC in FDR (RR PCa‐2 vs PCa‐1, 0.85, 95% CI, 0.78–0.94). PC patients with a family history of PCa‐2 were more likely to be detected at late‐stage and less likely to be diagnosed by screening, compared to those with a family history of PCa‐1. Patients whose PC was diagnosed after the diagnosis of PCa‐1 in FDRs had a better survival than those without a family history of cancer (HR, 0.88, 95% CI, 0.80–0.97), but no such association was observed among patients with a family history of PCa‐2. Conclusion: Our study indicates a discrepancy between PC risks associated with a family history of PCa‐1 and PC‐2 and the reason behind it may be multifactorial. [ABSTRACT FROM AUTHOR]

Background: The aim of the present study was to establish a competing risk nomogram to predict parotid gland cancer‐specific mortality (PGC‐SM). Methods: Seven thousand nine hundred and sixty‐two patients extracted from SEER database were randomly categorized into training and validation sets. The competing risk model was used to identify factors associated with PGC‐SM. The nomogram was evaluated via concordance indexes (C‐indexes), calibration plots, and decision curve analysis (DCA). Results: Male, elderly, white, widowed, larger tumor, no surgery, advanced tumor grade, lymph node (LN) metastasis, adenocarcinoma (ADC), and higher TNM stage were associated with higher incidence of PGC‐SM. Calibration plots showed that the nomogram was well calibrated. C‐indexes for nomogram were 0.84 (95% CI: 0.81–0.86) and 0.84 (95% CI: 0.82–0.86) in training and validation sets, respectively. DCA demonstrated the clinical usefulness of nomogram. Conclusions: The competing risk nomogram shows high performance in predicting PGC‐SM, which might enable clinicians formulate suitable treatment protocols for patients with parotid gland carcinoma (PGC). [ABSTRACT FROM AUTHOR]

For competing risks data, it is often important to predict a patient's outcome status at a clinically meaningful time point after incorporating the informative censoring due to competing risks. This can be done by adopting a regression model that relates the cumulative incidence probabilities to a set of covariates. To assess the performance of the resulting prediction tool, we propose an estimator of the polytomous discrimination index applicable to competing risks data, which can quantify a prognostic model's ability to discriminate among subjects from different outcome groups. The proposed estimator allows the prediction model to be subject to model misspecification and enjoys desirable asymptotic properties. We also develop an efficient computation algorithm that features a computational complexity of O(nlogn). A perturbation resampling scheme is developed to achieve consistent variance estimation. Numerical results suggest that the estimator performs well under realistic sample sizes. We apply the proposed methods to a study of monoclonal gammopathy of undetermined significance. [ABSTRACT FROM AUTHOR]

Survival data with competing or semi‐competing risks are common in observational studies. As an alternative to cause‐specific and subdistribution hazard ratios, the between‐group difference in cause‐specific restricted mean times lost (RMTL) gives the mean difference in life expectancy lost to a specific cause of death or in disease‐free time lost, in the case of a nonfatal outcome, over a prespecified period. To adjust for covariates, we introduce an inverse probability weighted estimator and its variance for the marginal difference in RMTL. We also introduce an inverse probability of censoring weighted regression model for the RMTL. In simulation studies, we examined the finite sample performance of the proposed methods under proportional and nonproportional subdistribution hazards scenarios. We illustrated both methods with competing risks data from the Framingham Heart Study. We estimated sex differences in atrial fibrillation (AF)‐free times lost over 40 years. We also estimated sex differences in mean lifetime lost to cardiovascular disease (CVD) and non‐CVD death over 10 years among individuals with AF. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) treatment and patient survival improved greatly. Consequently an increased incidence of non‐cancer‐related deaths is observed. This study analyzed the causes of non‐cancer death for people suffering from CRC based on the year of diagnosis, follow‐up time, and patient's age. Methods: The data from patients diagnosed with CRC in the years 2000–2016 were taken from the Surveillance, Epidemiology, and End Results 18 database. Patients were categorized according to: death from CRC, non‐CRC cancer, and non‐cancer. Constituent ratios and standardized mortality ratios (SMRs) were calculated to describe the death causes distribution and relative death risks. Results: Between 2000 and 2016, a stable and rapid drop for the original diagnosis as death cause for CRC patients was observed (70.19% to 49.35%). This was coupled to an increase in non‐cancer‐associated death reasons (23.38% to 40.00%). The most common non‐cancer death cause was heart disease, especially for elderly patients. However, deaths from accidents and adverse effects were frequent in younger CRC patients. Patients died from septicemia more often within the first follow‐up year; however, a 6‐fold increase in death from Alzheimer's disease was found for after at least 180 months follow‐up time. The SMRs of all 25 non‐cancer death causes initially decreased in all CRC subgroups, followed by an increase with follow‐up times. Gradually decreasing SMR values were observed with increasing age of CRC patients. Conclusions: These findings could help modify and sharpen preventive measures and clinical management and raise physician's awareness to potential non‐CRC death risk factors for CRC patients. [ABSTRACT FROM AUTHOR]

Background: Venous thromboembolism (VTE) is a hospital‐associated severe complication that may adversely affect patient prognosis. In this study, we evaluated the incidence of VTE and its risk factors in patients with epithelial ovarian cancer (EOC). Methods: We retrospectively analyzed the electronic health record data of 1268 patients with EOC who received primary treatment at the National Cancer Center, Korea between January 2007 and December 2017 to identify patients who developed VTE. Demographic, clinical, and surgical characteristics of these patients were ascertained. Competing risks analyses were performed to estimate the cumulative incidence of VTE according to the treatment type. The associations between putative risk factors and the incidence of VTE were evaluated using the Fine–Gray regression models accounting for competing risks of death. Results: VTE was the most prevalent cardiovascular event, found in 9.6% (n = 122) of all patients. Of these VTE events, 115 (94.3%) occurred within 2 years of EOC diagnosis. Advanced cancer stage at diagnosis (distant vs. localized, hazards ratio [HR])= 14.49, p = 0.015) and extended hospital stay (≥15 days, HR =3.87, p = 0.004) were associated with the incidence of VTE. There was no significant difference in the cumulative incidence of VTE between primary cytoreductive surgery followed by adjuvant chemotherapy and neoadjuvant chemotherapy followed by interval cytoreductive surgery (HR =0.81, p = 0.390). Conclusions: Approximately 10% of patients with EOC were diagnosed with VTE, which was the most common cardiovascular disease found in this study. The assessment of VTE risks in patients with advanced‐stage EOC with an extended hospital stay is needed to facilitate adequate prophylactic treatment. [ABSTRACT FROM AUTHOR]

Background: Respiratory syncytial virus (RSV) infection is implicated in subsequent development of asthma/wheezing (AW) among term and pre‐term infants. We describe the cumulative incidence of AW among hospitalized and ambulatory neonates/infants/toddlers following RSV infection diagnosis over three independent follow‐up periods. Methods: Between January 1, 2007 and March 31, 2016, patients aged 0‐2 years old with first clinical diagnosis of RSV infection were identified using the Optum® integrated electronic health records and claims database. Patients diagnosed with AW ≤ 30 days post‐RSV diagnosis were excluded. Three cohorts with 1, 3, and 5 years of follow‐up were stratified by presence or absence of specific RSV high‐risk factors, including pre‐term birth and pre‐defined, pre‐existing comorbidities. Descriptive statistics and logistic regression results were reported. Results: Overall, 9811, 4524, and 1788 RSV‐infected high‐risk factor negative patients were included in 1, 3, and 5‐year independent cohorts, respectively. Of these, 6.5%, 6.9%, and 5.8%, respectively had RSV‐related hospitalization. By the end of follow‐up, 14.9%, 28.2%, and 36.3% had AW events. Overall, 3030, 1378, and 552 RSV‐infected high‐risk factor positive patients were included in the respective cohorts. Of these, 11.4%, 11.1%, and 11.6%, respectively were hospitalized with initial RSV infection and 18.1%, 32.9%, and 37.9% had subsequent AW events within the follow‐up period. Logistic regression confirmed RSV‐related hospitalization significantly increased the likelihood of developing AW (P <.05) in high‐risk factor positive and negative patients. Conclusions: In infants diagnosed with RSV infection, RSV‐related hospitalization was associated with a significantly increased likelihood of AW development for at least 5 years, compared with non‐hospitalized patients. [ABSTRACT FROM AUTHOR]

A cause‐specific cumulative incidence function (CIF) is the probability of failure from a specific cause as a function of time. In randomized trials, a difference of cause‐specific CIFs (treatment minus control) represents a treatment effect. Cause‐specific CIF in each intervention arm can be estimated based on the usual non‐parametric Aalen–Johansen estimator which generalizes the Kaplan–Meier estimator of CIF in the presence of competing risks. Under random censoring, asymptotically valid Wald‐type confidence intervals (CIs) for a difference of cause‐specific CIFs at a specific time point can be constructed using one of the published variance estimators. Unfortunately, these intervals can suffer from substantial under‐coverage when the outcome of interest is a rare event, as may be the case for example in the analysis of uncommon adverse events. We propose two new approximate interval estimators for a difference of cause‐specific CIFs estimated in the presence of competing risks and random censoring. Theoretical analysis and simulations indicate that the new interval estimators are superior to the Wald CIs in the sense of avoiding substantial under‐coverage with rare events, while being equivalent to the Wald CIs asymptotically. In the absence of censoring, one of the two proposed interval estimators reduces to the well‐known Agresti–Caffo CI for a difference of two binomial parameters. The new methods can be easily implemented with any software package producing point and variance estimates for the Aalen–Johansen estimator, as illustrated in a real data example. [ABSTRACT FROM AUTHOR]

We suggest a regression approach to estimate the excess cumulative incidence function (CIF) when matched data are available. In a competing risk setting, we define the excess risk as the difference between the CIF in the exposed group and the background CIF observed in the unexposed group. We show that the excess risk can be estimated through an extended binomial regression model that actively uses the matched structure of the data, avoiding further estimation of both the exposed and the unexposed CIFs. The method naturally deals with two time scales, age and time since exposure and simplifies how to deal with the left truncation on the age time-scale. The model makes it easy to predict individual excess risk scenarios and allows for a direct interpretation of the covariate effects on the cumulative incidence scale. After introducing the model and some theory to justify the approach, we show via simulations that our model works well in practice. We conclude by applying the excess risk model to data from the ALiCCS study to investigate the excess risk of late events in childhood cancer survivors. [ABSTRACT FROM AUTHOR]

The Fine–Gray proportional subdistribution hazards model has been puzzling many people since its introduction. The main reason for the uneasy feeling is that the approach considers individuals still at risk for an event of cause 1 after they fell victim to the competing risk of cause 2. The subdistribution hazard and the extended risk sets, where subjects who failed of the competing risk remain in the risk set, are generally perceived as unnatural. One could say it is somewhat of a riddle why the Fine–Gray approach yields valid inference. To take away these uneasy feelings, we explore the link between the Fine–Gray and cause‐specific approaches in more detail. We introduce the reduction factor as representing the proportion of subjects in the Fine–Gray risk set that has not yet experienced a competing event. In the presence of covariates, the dependence of the reduction factor on a covariate gives information on how the effect of the covariate on the cause‐specific hazard and the subdistribution hazard relate. We discuss estimation and modeling of the reduction factor, and show how they can be used in various ways to estimate cumulative incidences, given the covariates. Methods are illustrated on data of the European Society for Blood and Marrow Transplantation. [ABSTRACT FROM AUTHOR]

Background: Some patients with Kawasaki disease (KD) develop cardiac sequelae, which increase the risk of subsequent ischemic heart events. Knowing the cumulative incidence (CI) of KD with cardiac sequelae may contribute to developing health policies to prevent subsequent ischemic events in these patients. Methods: Study participants consisted of 254 984 patients aged 0–9 years with KD who were registered in nationwide surveys in Japan from 1991–2016. We calculated the incidence probabilities by dividing the number of patients with KD aged 0–9 years by the population used in vital statistics of each calendar year. We calculated the cumulative proportion of those not affected by KD, by multiplying each probability in patients aged from age 0–9 years. The CI of KD was obtained by subtracting this value from 1. We also calculated the number of patients in each birth cohort (BC). The same was done to calculate the CI of KD‐related cardiac sequelae. Results: The CIBC steadily increased from 0.005067 in males and 0.003668 in females in 1991 to 0.011431 in males and 0.0088253 in females in 2007. The CIBC of KD with cardiac sequelae decreased from 0.000478 in males and 0.000213 in females in 1997 to 0.000339 in males and 0.000169 in females in 2007. Conclusion: The increasing CIBC of KD indicates an increased susceptibility to KD in accordance with birth year. The decreasing CIBC of cardiac sequelae suggests the efficacy of KD treatment. [ABSTRACT FROM AUTHOR]

Introduction: Relationship between age and dementia at extreme old ages is still an open question, yet population‐based studies in this high‐risk age segment are rare. Methods: The Monzino 80‐plus is a population‐based study among residents 80 years and older in the Varese province, Italy. Of 1371 eligible individuals, 1294 (94.4%), of whom 64 are centenarians, were included in the incidence study. Results: Since 2002, 584 new cases of all‐cause dementia were identified over 15 years. The overall incidence rate was 7.9 per 100 person‐years. Dementia risk rose with age (IRR: 1.06), with the cubic model providing the best fit (R2 = 0.91–0.96). Cumulative incidences of dementia unadjusted and adjusted for competing mortality risk progressively diverged with age. Conclusion: Dementia incidence also keeps rising in nonagenarians and centenarians. Slowing down in growing risk of developing dementia with age is mainly attributable to increasing competing risk of death and resulting selective survival of individuals at lower risk of dementia. [ABSTRACT FROM AUTHOR]

Misclassification of outcomes or event types is common in health sciences research and can lead to serious bias when estimating the cumulative incidence functions in settings with competing risks. Recent work has shown how to estimate nonparametric cumulative incidence functions in the presence of nondifferential outcome misclassification when the misclassification probabilities are known. Here, we extend this approach to account for misclassification that is differential with respect to important predictors of the outcome using misclassification probabilities estimated from external validation data. Moreover, we propose a bootstrap approach in which the observations from both the main study data and the external validation study are resampled to allow the uncertainty in the misclassification probabilities to propagate through the analysis into the final confidence intervals, ensuring appropriate confidence interval coverage probabilities. The proposed estimator is shown to be uniformly consistent and simulation studies indicate that both the estimator and the standard error estimation approach perform well in finite samples. The methodology is applied to estimate the cumulative incidence of death and disengagement from HIV care in a large cohort of HIV infected individuals in sub-Saharan Africa, where a significant death underreporting issue leads to outcome misclassification. This analysis uses external validation data from a separate study conducted in the same country. [ABSTRACT FROM AUTHOR]

Aim: Low bone mineral density occurs more commonly in patients with haemophilia (PWH) than the general population. However, the risk of haemophilia‐related osteoporotic fractures has not been well established. We aim to explore the relationship between haemophilia and the development of osteoporotic fractures following haemophilia. Methods: This was a nationwide population‐based cohort study based on the data in the Taiwan National Health Insurance Research Database (TNHIRD). Patients who were diagnosed with haemophilia were selected. A comparison cohort was formed of patients without haemophilia who were matched according to age and sex. The incidence rate and the hazard ratios (HRs) of new‐onset osteoporotic fractures were calculated for both cohorts. Results: The haemophilia cohort consisted of 75 patients, and the comparison cohort comprised 300 matched control patients without haemophilia. The risk of osteoporotic fractures was higher in the haemophilia cohort than in the comparison cohort (HR = 5.41, 95% confidence interval [CI] = 2.42‐12.1, P < 0.001). After adjustments for age, sex, comorbidities, urbanizations and socio‐economic status, PWH were 4.37 times more likely to develop osteoporotic fractures (95% CI = 1.88‐10.17, P = 0.001) as compared to matched cohort. In addition, the incidence of newly diagnosed osteoporotic fractures was significantly increased after 5‐year follow‐up durations. Conclusion: Though our study by TNHIRD presented methodologic flaws by its design nature, we observed that haemophilia may increase the risk of osteoporotic fractures and the cumulative incidence was significantly higher for PWH diagnosed more than 5 years. Clinicians should pay particular attention to osteoporotic fractures following haemophilia in PWH as they age. [ABSTRACT FROM AUTHOR]

A pregnancy may end up with (at least) three possible events: live birth, spontaneous abortion, or elective termination, yielding a competing risks issue when studying an association between a risk factor and a pregnancy outcome. Cumulative incidences (probabilities to end up with the different outcomes depending on gestational age) can be estimated via the Aalen–Johansen estimate. Another issue is that women are usually not entering such an observational study from the first day of pregnancy, resulting in delayed entries. As in traditional survival analysis, this can be solved by considering "at risk" at a given gestational age only for those women who entered the study before that age. However, the number of women at risk at an early gestational age might be extremely low, such that the estimates of cumulative incidence may increase exaggeratedly at that age because of a single event. One solution to reduce the problem has been recently proposed in the literature, which is to ignore simply those early events, creating a small mean bias but enhancing stability of estimates. In the present paper, we propose an alternative computationally simple approach to tackle this problem that consists to postpone to later gestational ages (rather than to ignore) those early events. The two approaches are compared with respect to bias, stability, and sensitivity on the smoothing parameter via simulations reproducing realistic pregnancy scenarios, and are illustrated with data from a study on the effects of statins on pregnancy outcomes. We also outline that all three approaches are asymptotically equivalent. [ABSTRACT FROM AUTHOR]

Sequential designs and competing risks methodology are both well established. Their combined use has recently received some attention from a theoretical perspective, but their joint application in practice has been discussed less. The aim of this paper is to provide the applied statistician with a basic understanding of both sequential design theory and competing risks methodology and how to combine them in practice. Relevant references to more detailed theoretical discussions are provided, and all discussions are illustrated using a real case study. Extensive R and SAS code is provided in the online Supplementary Material. [ABSTRACT FROM AUTHOR]

Background: With continuous increases in survival rates following breast cancer (BC) diagnosis, the challenge of multiple primary cancers has become an issue. The data on familial risk of SPCs after BC diagnosis and the related mortality in BC patients are scarce. Methods: A total of 87 752 female BC patients were followed for SPC diagnoses and records of death. Relative risks (RRs) of SPC in BC patients who had first‐degree relatives (parents or siblings) affected by the same cancer were compared to the patients without family history. Causes of death were compared between patients with and without SPC. Results: After a median follow‐up of 5 years, 14 952 BC patients developed SPCs, among which 10 280 (68.8%) had first‐degree relatives diagnosed with cancer. Familial risks were significant for 14 site‐specific SPCs, and the highest risk was for second ovarian cancer (RR = 6.28, 95%CI: 4.50‐8.75), compared to those without family history (1.49, 1.34‐1.65). In patients with SPC, SPC was the main cause of death, including diverse cancers and BC in approximately equal proportions. Conclusions: Family history contributed to the excess number of patients with SPCs, and SPC was the leading cause of death in patients with SPC. Taking family history at diagnosis of BC may provide warning signs with regard to possible subsequent SPCs and may offer possibilities for counseling, intervention and management. Family history contributed to the excess number of BC patients with SPC. SPC was found the leading cause of death in BC patients with SPC. [ABSTRACT FROM AUTHOR]

This population‐based study examined the natural course of hepatitis B e antigen (HBeAg)‐positive or HBeAg‐negative persistent hepatitis B virus (HBV) infection, adjusted by age and liver disease states using a Markov model. Using 12 417 person‐years data (n = 862), annual transition probabilities were estimated, and age‐adjusted cumulative incidence and natural history of persistent HBV infection were simulated in both sexes of groups 1 (HBeAg‐negative status with HBV DNA level <4.0 log IU/mL at entry) and 2 (persistent HBeAg‐positive status throughout the study). In group 1, 15.26% of 30‐years old men with chronic hepatitis (CH) were expected to remain in the same state at age 65 years, 28.32% subsided into an hepatitis B surface antigen (HBsAg)‐negative state, and 13.20% developed hepatocellular carcinoma (HCC). The expectations for 40‐years old men in group 1 were 21.43%, 19.86%, and 15.04%, respectively. The expectations for 30 years women in group 1 were 30.57%, 21.15%, and 4.08%, respectively. These results suggest that HBeAg positivity caused a higher risk of HCC onset in persistent HBV infection after adjustments for age, sex, and liver disease state. HCC was likely to develop, but unlikely to subside into HBsAg clearance, remaining in a CH state with aging, regardless of HBeAg state. Furthermore, both HCC development and HBsAg clearance occurred more frequently in men than in women, irrespective of HBeAg status. Highlights: 1.HBeAg‐positive state per se is one of the risk factor for severe liver complications.2.The rate of HBsAg clearance was higher in males than in females.3.Markov model is useful to simulate the age‐matched survival rate or cumulative incidence using 1‐year transition probability. [ABSTRACT FROM AUTHOR]

Background: The incidence and risk factors of chronic thromboembolic pulmonary hypertension (CTEPH) in patients with acute pulmonary embolism (PE) have been well reported. However, in real world, patients diagnosed with PE for the first time were usually composed of acute PE, sub‐acute PE, and chronic PE, and the cumulative incidence and risk factors of CTEPH in this cohort were still unknown. Methods: A prospective, long‐term, follow‐up study was conducted to assess the incidence of symptomatic CTEPH in consecutive patients with PE diagnosed for the first time. Patients with unexplained persistent dyspnea during follow‐up underwent transthoracic echocardiography and, if the findings indicated pulmonary hypertension, ventilation‐perfusion lung scanning and right heart catheterization. CTEPH was confirmed if perfusion defects were present, mean pulmonary artery pressure (mPAP) ≥25 mmHg and pulmonary artery wedge pressure (PAWP) ≤15 mmHg. Results: The cumulative incidence of CTEPH in patients with PE diagnosed for the first time was 11.2% at 3 months, 12.7% at 1 year, 13.4% at 2 years, and 14.5% at 3 years. The following factors increased the risk of CTEPH: time from symptoms to treatment of PE ≥1 month (odds ratio (OR), 14.77), intermediate (OR, 37.63) to high risk PE (OR, 39.81), segmental and sub‐segmental branch location of embolism (OR, 8.30) and PE‐related primary risk factors (OR, 5.01). 9.4% of CTEPH patients developed from acute PE, and 90.6% from sub‐acute and chronic PE. Conclusions: In real world, CTEPH is a relatively common and serious complication in PE patients diagnosed for the first time. Early diagnosis and treatment of PE will decrease the incidence of CTEPH in these unspecified patients. [ABSTRACT FROM AUTHOR]

We investigate different primary efficacy analysis approaches for a 2-armed randomized clinical trial when interest is focused on a time to event primary outcome that is subject to a competing risk. We extend the work of Friedlin and Korn (2005) by considering estimation as well as testing and by simulating the primary and competing events' times from both a cause-specific hazards model as well as a joint subdistribution-cause-specific hazards model. We show that the cumulative incidence function can provide useful prognostic information for a particular patient but is not advisable for the primary efficacy analysis. Instead, it is preferable to fit a Cox model for the primary event which treats the competing event as an independent censoring. This is reasonably robust for controlling type I error and treatment effect bias with respect to the true primary and competing events' cause-specific hazards model, even when there is a shared, moderately prognostic, unobserved baseline frailty for the primary and competing events in that model. However, when it is plausible that a strongly prognostic frailty exists, combining the primary and competing events into a composite event should be considered. Finally, when there is an a priori interest in having both the primary and competing events in the primary analysis, we compare a bivariate approach for establishing overall treatment efficacy to the composite event approach. The ideas are illustrated by analyzing the Women's Health Initiative clinical trials sponsored by the National Heart, Lung, and Blood Institute. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To investigate risk factors for the development and progression of diabetic retinopathy (DR) and long‐term visual outcomes in Dutch patients with type 1 diabetes mellitus (T1DM). Methods: Cumulative incidences were calculated for DR, vision‐threatening DR (VTDR), defined as (pre)proliferative DR and diabetic macular oedema, and best‐corrected visual acuity (BCVA) <0.5 and <0.3 at the most recent eye examination. The following factors were assessed: duration of diabetes, age of onset of T1DM, gender, mean HbA1c, HbA1c variability (defined as coefficient of variation of five separate HbA1c measurements), mean arterial blood pressure, body mass index, albuminuria and lipid profile. We used multivariable Cox regression models to identify factors associated with DR development and progression to VTDR. Results: We found 25‐year cumulative incidences of 63% for DR, 21% for VTDR, 2% for BCVA <0.5, and 1% for BCVA <0.3. Mean HbA1c (HR 1.023, p < 0.001), HbA1c variability (HR 1.054, p < 0.001), age of onset of T1DM (HR 1.024, p < 0.001), HDL cholesterol (HR 0.502, p = 0.002) and total cholesterol (HR 1.210, p = 0.029) showed an independent association with faster development of any form of DR. The mean HbA1c (HR 1.023, p < 0.001) and the presence of albuminuria (HR 2.940, p = 0.028) were associated with faster progression to VTDR. Conclusion: These data show relatively low cumulative incidences of DR, VTDR and visual impairment. Higher mean HbA1c, HbA1c variability, age of onset of T1DM and total cholesterol were independently associated with the risk of DR development, and a protective association was found for HDL cholesterol in subjects with T1DM. Mean HbA1c and presence of albuminuria were associated with progression of DR. [ABSTRACT FROM AUTHOR]

In a competing risks analysis, interest lies in the cause-specific cumulative incidence function (CIF) that can be calculated by either (1) transforming on the cause-specific hazard or (2) through its direct relationship with the subdistribution hazard. We expand on current competing risks methodology from within the flexible parametric survival modelling framework (FPM) and focus on approach (2). This models all cause-specific CIFs simultaneously and is more useful when we look to questions on prognosis. We also extend cure models using a similar approach described by Andersson et al for flexible parametric relative survival models. Using SEER public use colorectal data, we compare and contrast our approach with standard methods such as the Fine & Gray model and show that many useful out-of-sample predictions can be made after modelling the cause-specific CIFs using an FPM approach. Alternative link functions may also be incorporated such as the logit link. Models can also be easily extended for time-dependent effects. [ABSTRACT FROM AUTHOR]

Abstract: Background: Although the incidence rates of Kawasaki disease (KD) in Japan have been determined in nationwide surveys, the cumulative incidence, that is, the proportion of those with a history of KD in the general population of 10‐year‐olds, is currently unknown. The aim of this study was therefore to assess the cumulative incidence of KD in Japan. Methods: Using the age‐ and sex‐specific incidence rate of KD in Japan from the results of the nationwide surveys, incidence probabilities, that is, the age‐specific number of KD patients divided by the population used in the vital statistics, and cumulative proportions of those not affected by KD up to the end of 9 years of age, were calculated. The cumulative incidence was then defined as 1 minus the cumulative proportion. The observed age classes were 0, 1, 2, 3, 4, and 5–9 years. All data were calculated by sex. Results: The cumulative incidence was 0.004833 for boys and 0.003474 for girls in 1991, but was 0.015284 and 0.012145 in 2014, respectively. According to these figures, 15.284 per 1,000 boys and 12.145 per 1,000 girls have been affected by KD by the age of 10 years. The birth‐cohort cumulative incidences had similar trends. Conclusions: More than 10 persons in 1,000 have a history of KD at age 10 years in Japan. [ABSTRACT FROM AUTHOR]

The diagnostic criteria for follicular lymphoma ( FL) transformation vary among the largest series, which commonly exclude histologically-documented transformation ( HT) mandatorily. The aims of this retrospective observational multicentre study by the Spanish Grupo Español de Linfoma y Transplante Autólogo de Médula Ósea, which recruited 1734 patients (800 males/934 females; median age 59 years), diagnosed with FL grades 1-3A, were, (i) the cumulative incidence of HT ( CI- HT); (ii) risk factors associated with HT; and (iii) the role of treatment and response on survival following transformation ( SFT). With a median follow-up of 6·2 years, 106 patients developed HT. Ten-year CI- HT was 8%. Considering these 106 patients who developed HT, median time to transformation was 2·5 years. High-risk FL International Prognostic Index [Hazard ratio ( HR) 2·6, 95% confidence interval ( CI): 1·5-4·5] and non-response to first-line therapy ( HR 2·9, 95% CI: 1·3-6·8) were associated with HT. Seventy out of the 106 patients died (5-year SFT, 26%). Response to HT first-line therapy ( HR 5·3, 95% CI: 2·4-12·0), autologous stem cell transplantation ( HR 3·9, 95% CI: 1·5-10·1), and revised International Prognostic Index ( HR 2·2, 95% CI: 1·1-4·2) were significantly associated with SFT. Response to treatment and HT were the variables most significantly associated with survival in the rituximab era. Better therapies are needed to improve response. Inclusion of HT in clinical trials with new agents is mandatory. [ABSTRACT FROM AUTHOR]

Background Survival studies on head and neck cancers are frequently reported with inadequate account for competing causes of death. Realistic descriptions and predictions of postdiagnosis mortality should be based on proper competing risks methodology. Methods Prognosis of patients with oral squamous cell carcinoma (OSCC) in terms of mortality from OSCC and from other causes, respectively, was analyzed according to recent methodological recommendations using cumulative incidence functions and models for cause-specific hazards and subdistribution hazards in 306 patients treated in a tertiary care center in Northern Finland. Results More coherent and informative descriptions and predictions of mortality by cause were obtained with state-of-the-art statistical methods for competing risks than using the prevalent but questionable practice to graph 'disease-specific survival.' Conclusion From the patients' perspective, proper competing risks analysis offers more relevant prognostic scenarios than naïve analyses of 'disease-specific survival'; therefore, it should be used in prognostic studies of head and neck cancers. © 2016 Wiley Periodicals, Head Neck 39: 56-62, 2017 [ABSTRACT FROM AUTHOR]

In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event status is replaced by a jackknife pseudo-value based on the Aalen-Johansen method. We combine a stagewise regression technique with the pseudo-value approach to provide variable selection while allowing for time-varying effects. This is implemented by coupling variable selection between the grid times, but determining estimates separately. The effect estimates are regularized to also allow for model fitting with a low to moderate number of observations. This technique is illustrated in an application using clinical cancer registry data from hepatocellular carcinoma patients. The results are contrasted with traditional hazard-based modeling. In addition to a more straightforward interpretation, when using the proposed technique, the identification of time-varying effect patterns on the cumulative incidence is seen to be feasible with a moderate number of observations. [ABSTRACT FROM AUTHOR]

Cancer patients may die from causes other than the diagnosed cancer. In a study of patients treated for soft tissue sarcoma, the patients may die from the disease or die without experiencing disease recurrence. In addition, a substantial proportion of the patients will remain cancer-free after surgical resection of the tumour, and therefore will not be at increased risk of any type of failure. Our goal is to describe the effect of adjuvant chemotherapy simultaneously on the probabilities of long-term survival, death from cancer, or death from other causes. To this end, we propose a semiparametric mixture model to determine the effects of factors on the probability of occurrence, allowing the surviving fraction, and the hazard rate conditional on each of the failure types. These quantities are combined in the mixture approach using a multinomial logistic model and a class of semiparametric transformation models. Estimation of the regression and nonparametric parameters is achieved with a novel nonparametric maximum likelihood approach. Statistical inferences can be conveniently made from the inverse of the observed information matrix. Simulation studies show that the procedures work well in practical settings. The methodology is illustrated with data from the soft tissue sarcoma study. The Canadian Journal of Statistics 43: 420-435; 2015 © 2015 Statistical Society of Canada [ABSTRACT FROM AUTHOR]

Background and purpose Brain tumors represent a rare and relatively uncharacterized tumor type in Lynch syndrome. Methods The national Danish Hereditary Nonpolyposis Colorectal Cancer Register was utilized to estimate the cumulative life-time risk for brain tumors in Lynch syndrome, and the mismatch repair ( MMR) status in all tumors available was evaluated. Results Primary brain tumors developed in 41/288 families at a median age of 41.5 (range 2-73) years. Biallelic MMR gene mutations were linked to brain tumor development in childhood. The risk of brain tumors was significantly higher (2.5%) in MSH2 gene mutation carriers compared to patients with mutations in MLH1 or MSH6. Glioblastomas predominated (56%), followed by astrocytomas (22%) and oligodendrogliomas (9%). MMR status was assessed in 10 tumors, eight of which showed MMR defects. None of these tumors showed immunohistochemical staining suggestive of the IDH1 R132H mutation. Conclusion In Lynch syndrome brain tumors occurred in 14% of the families with significantly higher risks for individuals with MSH2 gene mutations and development of childhood brain tumors in individuals with constitutional MMR defects. [ABSTRACT FROM AUTHOR]

Purpose To evaluate whether diabetes is a risk factor for breast cancer considering confounders and potential detection examinations. Methods National Health Insurance data on 501 747 women without breast cancer were retrieved. Three-year cumulative incidence (2003-2005) and risk ratios ( RRs) between diabetic and nondiabetic women were calculated. Potential detection examinations were compared between diabetic and nondiabetic women by chi-square test. Odds ratios ( ORs) were estimated by logistic regression for diabetes status/duration with and without adjustment for potential detection examinations and confounders. Results The crude RR (95% confidence interval [ CI]) for all ages, and age groups < 50, 50-64 and ≥ 65 years, was 2·62 (2·31-2·91), 2·69 (2·11-3·44), 1·39 (1·15-1·68) and 1·37 (1·03-1·84), respectively. Patients with diabetes more frequently received potential detection examinations than nondiabetes (17·5% vs. 7·4%, P-value < 0·001). The unadjusted OR (95% CI) for breast cancer for diabetes status (yes vs. no) was 2·63 (2·31-2·98) and was significant for any diabetes duration. The OR for diabetes status was 1·81 (95% CI: 1·59-2·06) after adjustment for potential detection examinations. In models adjusted for potential detection examinations, age, living region, occupation, comorbidities and used medications, OR for diabetes status attenuated to 1·13 (95% CI 0·96-1·32, P-value = 0·14) and none was significant for any diabetes duration. Potential detection examinations were associated with a fivefold to sevenfold higher risk in various models, indicating a strong impact of detection bias. Conclusions An association between diabetes and breast cancer is observed, but this can be due to potential detection bias and confounders. [ABSTRACT FROM AUTHOR]

Purpose To investigate and compare the cumulative incidence of diagnosed open-angle glaucoma (OAG) in an age cohort of elderly people, of which one group was screened. Methods Cohort study comprising all 856 individuals born in 1915 and living in the municipality of Skellefteå in 1981. A randomly selected subgroup of the cohort (40%) was repeatedly screened, and suspected OAG cases were followed until 2002 for the development of OAG. Medical records were collected and analysed for OAG. The numbers of OAG cases were compared between the screened group and the remaining part of the cohort (the unscreened group). Results The cohort consisted of 339 screened and 517 unscreened persons. Before 1981, there were six known cases of OAG in the screened group and nine cases in the unscreened group. During the follow-up from 1981 to 2002, there were 33 new cases in the screened group and 31 new cases of OAG in the unscreened group. The incidence of diagnosed OAG in women was higher in the screened group than in the unscreened group, incidence rate ratio = 1.94 (p = 0.035). In contrast, the cumulative incidence of diagnosed OAG in men was similar in the two groups (p = 0.58). For the whole population, there was no significant difference (p = 0.053). Conclusion In this population with a high prevalence of PEX and increased risk for glaucoma, there was a non-significant difference between the screened and unscreened groups regarding the proportion of diagnosed OAG. The failure to reach significance may be due to the limited sample size. OAG was diagnosed twice as often among women in the screened group than in the unscreened group. [ABSTRACT FROM AUTHOR]

Transform methods have proved effective for networks describing a progression of events. In semi-Markov networks, we calculated the transform of time to a terminating event from corresponding transforms of intermediate steps. Saddlepoint inversion then provided survival and hazard functions, which integrated, and fully utilised, the network data. However, the presence of censored data introduces significant difficulties for these methods. Many participants in controlled trials commonly remain event-free at study completion, a consequence of the limited period of follow-up specified in the trial design. Transforms are not estimable using nonparametric methods in states with survival truncated by end-of-study censoring. We propose the use of parametric models specifying residual survival to next event. As a simple approach to extrapolation with competing alternative states, we imposed a proportional incidence (constant relative hazard) assumption beyond the range of study data. No proportional hazards assumptions are necessary for inferences concerning time to endpoint; indeed, estimation of survival and hazard functions can proceed in a single study arm. We demonstrate feasibility and efficiency of transform inversion in a large randomised controlled trial of cholesterol-lowering therapy, the Long-Term Intervention with Pravastatin in Ischaemic Disease study. Transform inversion integrates information available in components of multistate models: estimates of transition probabilities and empirical survival distributions. As a by-product, it provides some ability to forecast survival and hazard functions forward, beyond the time horizon of available follow-up. Functionals of survival and hazard functions provide inference, which proves sharper than that of log-rank and related methods for survival comparisons ignoring intermediate events. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

With improvement in survival, it is important to evaluate the impact of treatment on secondary cancers in acute lymphoblastic leukaemia ( ALL) survivors. A retrospective cohort study comprising 2918 children diagnosed with ALL and enrolled on Tokyo Children's Cancer Study Group ( TCCSG) protocols between 1984 and 2005 was conducted to evaluate the incidence of secondary cancers and associated factors including treatment protocol, cranial irradiation and other characteristics of the primary ALL. Thirty-seven patients developed secondary cancers, including acute myeloid leukaemia ( n = 11), myelodysplastic syndrome ( n = 5), non- Hodgkin lymphoma ( n = 2), brain tumours ( n = 13) and other solid carcinomas ( n = 6) within a median follow-up duration of 9·5 years. The cumulative incidence of any secondary cancers was 1·0% (95% confidence interval ( CI), 0·7-1·4%) at 10 years and 2·4% (95% CI, 1·5-3·7%) at 20 years, respectively. Standardized incidence rate ratio of secondary cancers was 9·3 (95% CI, 6·5-12·8). Multivariate analyses showed an increased risk of secondary cancers associated with the recent treatment protocol and cranial irradiation. There was no evidence of a reduction in secondary cancer incidence despite marked decreases in cranial irradiation use in the recent protocols. [ABSTRACT FROM AUTHOR]

Camera trapping, paired with analytical methods for estimating occupancy, abundance and other ecological parameters, can yield information with direct consequences for wildlife management and conservation. Although ecological information is the primary target of most camera trap studies, detectability influences every aspect from design to interpretation., Concepts and methods of time-to-event analysis are directly applicable to camera trapping, yet this statistical field has thus far been ignored as a way to analyse photographic capture data. To illustrate the use of time-to-event statistics and to better understand how photographic evidence accumulates, we explored patterns in two related measures of detectability: detection probability and time to detection. We analysed camera trap data for three sympatric carnivores (snow leopard, red fox and stone marten) in the mountains of northern Pakistan and tested predictions about patterns in detectability across species, sites and time., We found species-specific differences in the magnitude of detectability and the factors influencing it, reinforcing the need to consider determinants of detectability in study design and to account for them during analysis. Photographic detectability of snow leopard was noticeably lower than that of red fox, but comparable to detectability of stone marten. Site-specific attributes such as the presence of carnivore sign (snow leopard), terrain (snow leopard and red fox) and application of lures (red fox) influenced detectability. For the most part, detection probability was constant over time., Species-specific differences in factors determining detectability make camera trap studies targeting multiple species particularly vulnerable to misinterpretation if the hierarchical origin of the data is ignored. Investigators should consider not only the magnitude of detectability, but also the shape of the curve describing the cumulative process of photographic detection, as this has consequences for both determining survey effort and the selection of analytical models. Weighted time-to-event analysis can complement occupancy analysis and other hierarchical methods by providing additional tools for exploring camera trap data and testing hypotheses regarding the temporal aspect of photographic evidence accumulation. [ABSTRACT FROM AUTHOR]

Background Referrals to the Greater Glasgow Community Autism Team (CAT) made before the child's sixth birthday were analysed to obtain an estimation of the proportion of children in Greater Glasgow with childhood autism and investigate whether there were any variations in diagnosis rates, or in age at referral and diagnosis, depending on deprivation or geographical location. Methods An analysis was made of the database recording referrals to Greater Glasgow CAT, between 2004 and 2007 inclusive, of children referred by age 6 years, comprising 584 cases. Cumulative incidence was calculated for childhood autism. Ages at referral and diagnosis were also analysed. Results For this subset of children, there were 246 diagnosed cases of childhood autism, a cumulative incidence from 2004 until 2007 of 11.1 per year per 10 000 children aged 0-6 years. Of children with an eventual diagnosis of autism by age 6, 72% were referred by the age of 4 years. Deprivation was found to have an association with referral and diagnostic rates, with higher rates seen in the most deprived. There was geographical variation in the cumulative incidence of autism. Conclusion Given that the populations were not known to differ in any manner that would lead to a true variation, the geographical variation in the cumulative incidence of autism in children up to 6 years in Greater Glasgow observed in this study is likely to represent differences in the care pathway between areas. Such differences may also explain the observed association with deprivation. Reasons for the variation are being explored. [ABSTRACT FROM AUTHOR]

Background The global impact of the 2009 influenza A( H1 N1) pandemic ( H1 N1pdm) is not well understood. Objectives We estimate overall and age-specific prevalence of cross-reactive antibodies to H1 N1pdm virus and rates of H1 N1pdm infection during the first year of the pandemic using data from published and unpublished H1 N1pdm seroepidemiological studies. Methods Primary aggregate H1 N1pdm serologic data from each study were stratified in standardized age groups and evaluated based on when sera were collected in relation to national or subnational peak H1 N1pdm activity. Seropositivity was assessed using well-described and standardized hemagglutination inhibition ( HI titers ≥32 or ≥40) and microneutralization ( MN ≥ 40) laboratory assays. The prevalence of cross-reactive antibodies to the H1 N1pdm virus was estimated for studies using sera collected prior to the start of the pandemic (between 2004 and April 2009); H1 N1pdm cumulative incidence was estimated for studies in which collected both pre- and post-pandemic sera; and H1 N1pdm seropositivity was calculated from studies with post-pandemic sera only (collected between December 2009- June 2010). Results Data from 27 published/unpublished studies from 19 countries/administrative regions - Australia, Canada, China, Finland, France, Germany, Hong Kong SAR, India, Iran, Italy, Japan, Netherlands, New Zealand, Norway, Reunion Island, Singapore, United Kingdom, United States, and Vietnam - were eligible for inclusion. The overall age-standardized pre-pandemic prevalence of cross-reactive antibodies was 5% (95% CI 3-7%) and varied significantly by age with the highest rates among persons ≥65 years old (14% 95% CI 8-24%). Overall age-standardized H1 N1pdm cumulative incidence was 24% (95% CI 20-27%) and varied significantly by age with the highest in children 5-19 (47% 95% CI 39-55%) and 0-4 years old (36% 95% CI 30-43%). Conclusions Our results offer unique insight into the global impact of the H1 N1 pandemic and highlight the need for standardization of seroepidemiological studies and for their inclusion in pre-pandemic preparedness plans. Our results taken together with recent global pandemic respiratory-associated mortality estimates suggest that the case fatality ratio of the pandemic virus was approximately 0·02%. [ABSTRACT FROM AUTHOR]

In the analysis of time-to-event data, the problem of competing risks occurs when an individual may experience one, and only one, of m different types of events. The presence of competing risks complicates the analysis of time-to-event data, and standard survival analysis techniques such as Kaplan-Meier estimation, log-rank test and Cox modeling are not always appropriate and should be applied with caution. Fine and Gray developed a method for regression analysis that models the hazard that corresponds to the cumulative incidence function. This model is becoming widely used by clinical researchers and is now available in all the major software environments. Although model selection methods for Cox proportional hazards models have been developed, few methods exist for competing risks data. We have developed stepwise regression procedures, both forward and backward, based on AIC, BIC, and BICcr (a newly proposed criteria that is a modified BIC for competing risks data subject to right censoring) as selection criteria for the Fine and Gray model. We evaluated the performance of these model selection procedures in a large simulation study and found them to perform well. We also applied our procedures to assess the importance of bone mineral density in predicting the absolute risk of hip fracture in the Women's Health Initiative-Observational Study, where mortality was the competing risk. We have implemented our method as a freely available R package called crrstep. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Clinical trials are often performed using a group sequential design in order to allow investigators to review the accumulating data sequentially and possibly terminate the trial early for efficacy or futility. Standard methods for comparing survival distributions have been shown under varying levels of generality to follow an independent increments structure. In the presence of competing risks, where the occurrence of one type of event precludes the occurrence of another type of event, researchers may be interested in inference on the cumulative incidence function, which describes the probability of experiencing a particular event by a given time. This manuscript shows that two commonly used tests for comparing cumulative incidence functions, a pointwise comparison at a single point, and Gray's test, also follow the independent increments structure when used in a group sequential setting. A simulation study confirms the theoretical derivations even for modest trial sample sizes. We used two examples of clinical trials in hematopoietic cell transplantation to illustrate the techniques. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In survival analysis with competing risks, the transformation model allows different functions between the outcome and explanatory variables. However, the model's prediction accuracy and the interpretation of parameters may be sensitive to the choice of link function. We review the practical implications of different link functions for regression of the absolute risk (or cumulative incidence) of an event. Specifically, we consider models in which the regression coefficients β have the following interpretation: The probability of dying from cause D during the next t years changes with a factor exp( β) for a one unit change of the corresponding predictor variable, given fixed values for the other predictor variables. The models have a direct interpretation for the predictive ability of the risk factors. We propose some tools to justify the models in comparison with traditional approaches that combine a series of cause-specific Cox regression models or use the Fine-Gray model. We illustrate the methods with the use of bone marrow transplant data. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Please cite this paper as: Burmaa et al. (2012) Cumulative incidence of pandemic influenza A (H1N1) 2009 by a community-based serological cohort study in Selenghe Province, Mongolia. Influenza and Other Respiratory Viruses 6(601), e97-e104. Background Large community outbreaks of pandemic A (H1N1) 2009 occurred between October and December 2009 in Mongolia. A serological study was conducted among the general population by testing paired sera collected before and after the first wave of pandemic in Selenghe province, Mongolia. None of the study participants had been vaccinated for pandemic A (H1N1) 2009 before the second samples were collected. Objective The objective of this study was to estimate cumulative incidence of pandemic A (H1N1) 2009 in different age-groups of Selenghe province residents. Methods After informed consent was obtained from apparently healthy volunteers, the paired sera and background information were collected. Antibody titers were measured using hemagglutinin inhibition (HI) and microneutralization (MN) assays for A/California/07/2009pdm. A fourfold rise in antibody titers was regarded as the evidence of infection. Results The overall cumulative incidences in the study group for all ages were 28·8% (76/264) by HI, 35·2% (93/264) by MN, and 25·0% (66/264) by both HI and MN. Cumulative incidences of infection varied among age-groups, with children aged 2-4 and 5-9 years having high cumulative incidence of infection. Overall cumulative incidences of infection in the whole population were estimated to be 23·0% (4946/21 460) by HI, 30·2% (6473/21 460) by MN, and 18·8% (4036/21 460) by both HI and MN. Conclusions This study indicates that about one-fourth of the total population in Selenghe province was infected with pandemic A (H1N1) 2009 virus during the first wave of the pandemic. [ABSTRACT FROM AUTHOR]

The article discusses the application of absolute risk and its properties in breast cancer counseling and prevention. Absolute risk is defined as the probability of a person to develop a disease, which also considers the set of risk factors and free of the disease of interest at age α. In terms of preventive intervention, absolute risk models can be used so that the high-risk subsets of the population can lesser their chances of acquiring a disease. The authors concluded that increased used of absolute models can be possible with further research.

The article presents information on a study which determined the survival and long-term morbidities of children with nasopharyngeal carcinoma (NPC). Information on the incidence of NPC in the U.S. and related studies is presented. Data reviewed were from children with NPC who treated at Saint Jude Children's Research Hospital between 1961 and 2004. Prognostic factors for overall survival and event-free survival are age at diagnosis, lymph node classification and race, among others.

Purpose: To determine cumulative incidence and predictors of new-onset seizures in mild Alzheimer's disease (AD) with a cohort followed prospectively. Limited information is available on the incidence of seizures, and no reports exist of seizure predictors in AD patients. Methods: Mild AD patients were prospectively followed at 6-month intervals to estimate incidence of unprovoked seizures, compare age-specific risk of unprovoked seizures with population norms, and identify characteristics at baseline (demographics, duration and severity of AD, physical and diagnostic test findings, and comorbid medical and psychiatric conditions) influencing unprovoked seizure risk. Review of study charts and medical records supplemented coded end-point data. Results: The cumulative incidence of unprovoked seizures at 7 years was nearly 8%. In all age groups, risk was increased compared with a standard population, with an 87-fold increase in the youngest group (age 50–59 years) and more than a threefold increase in the oldest group (age 85+ years). In multivariate modeling, independent predictors of unprovoked seizures were younger age [relative risk (RR), 0.89 per year increase in age; 95% confidence interval (CI), 0.82–0.97], African-American ethnic background (RR, 7.35; 95% CI, 1.42–37.98), more-severe dementia (RR, 4.15; 95% CI, 1.06–16.27), and focal epileptiform findings on electroencephalogram (EEG) (RR, 73.36; 95% CI, 1.75–3075.25). Conclusions: Seizure incidence is increased in people starting with mild-to-moderate AD. Younger individuals, African Americans, and those with more-severe disease or focal epileptiform findings on EEG were more likely to have unprovoked seizures. [ABSTRACT FROM AUTHOR]