Modeling cumulative incidence function for competing risks data

Enhanced Cohort Methods for HIV Research and Epidemiology (ENCORE): Protocol for a Nationwide Hybrid Cohort for Transgender Women in the United States

BACKGROUND

In the United States, transgender women are disproportionately impacted by HIV and prioritized in the national strategy to end the epidemic. Individual, interpersonal, and structural vulnerabilities underlie HIV acquisition among transgender women and fuel syndemic conditions, yet no nationwide cohort monitors their HIV and other health outcomes.

OBJECTIVE

Our objective is to develop a nationwide cohort to estimate HIV incidence, identify risk factors, and investigate syndemic conditions co-occurring with HIV vulnerability or acquisition among US transgender women. The study is informed by the Syndemics Framework and the Social Ecological Model, positing that stigma-related conditions are synergistically driven by shared multilevel vulnerabilities.

METHODS

To address logistical and cost challenges while minimizing technology barriers and research distrust, we aim to establish a novel, hybrid community hub-supported digital cohort (N=3000). The digital cohort is the backbone of the study and is enhanced by hubs strategically located across the United States for increased engagement and in-person support. Study participants are English or Spanish speakers, are aged ≥18 years, identify as transgender women or along the transfeminine spectrum, reside in 1 of the 50 states or Puerto Rico, and do not have HIV (laboratory confirmed). Participants are followed for 24 months, with semiannual assessments. These include a questionnaire and laboratory-based HIV testing using self-collected specimens. Using residential zip codes, person-level data will be merged with contextual geolocated data, including population health measures and economic, housing, and other social and structural factors. Analyses will (1) evaluate the contribution of hub support to the digital cohort using descriptive statistics; (2) estimate and characterize syndemic patterns among transgender women using latent class analysis; (3) examine the role of contextual factors in driving syndemics and HIV prevention over time using multilevel regression models; (4) estimate HIV incidence in transgender women and examine the effect of syndemics and contextual factors on HIV incidence using Poisson regression models; and (5) develop dynamic, compartmental models of multilevel combination HIV prevention interventions among transgender women to simulate their impact on HIV incidence through 2030.

RESULTS

Enrollment launched on March 15, 2023, with data collection phases occurring in spring and fall. As of February 24, 2024, a total of 3084 individuals were screened, and 996 (32.3%) met the inclusion criteria and enrolled into the cohort: 2.3% (23/996) enrolled at a hub, and 53.6% (534/996) enrolled through a community hub-supported strategy. Recruitment through purely digital methods contributed 61.5% (1895/3084) of those screened and 42.7% (425/996) of those enrolled in the cohort.

CONCLUSIONS

Study findings will inform the development of evidence-based interventions to reduce HIV acquisition and syndemic conditions among US transgender women and advance efforts to end the US HIV epidemic. Methodological findings will also have critical implications for the design of future innovative approaches to HIV research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/59846.

Time to prerandomization seizure count design sufficiently assessed the safety and tolerability of perampanel for the treatment of primary generalized tonic-clonic seizures

OBJECTIVE

Static assignment of participants in randomized clinical trials to placebo or ineffective treatment confers risk from continued seizures. An alternative trial design of time to exceed prerandomization monthly seizure count (T-PSC) has replicated the efficacy conclusions of traditionally designed trials, with shorter exposure to placebo and ineffective treatment. Trials aim to evaluate efficacy as well as safety and tolerability; therefore, we evaluated whether this T-PSC design also could replicate the trial's safety and tolerability conclusions.

METHODS

We retrospectively applied the T-PSC design to analyze treatment-emergent adverse events (TEAEs) from a blinded, placebo-controlled trial of perampanel for primary generalized tonic-clonic seizures (NCT01393743). The safety analysis set consisted of 81 and 82 participants randomized to perampanel and placebo arms, respectively. We evaluated the incidences of TEAEs, treatment-related TEAEs, serious TEAEs, and TEAEs of special interest that occurred before T-PSC relative to those observed during the full-length trial.

RESULTS

Of the 67 and 59 participants who experienced TEAEs in the perampanel and placebo arms during full-length trial, 66 (99%) and 54 (92%) participants experienced TEAEs with onset occurring before T-PSC, respectively. When limited to treatment-related TEAEs, 55 of 56 (98%) and 32 of 37 (86%) participants reported treatment-related TEAEs that occurred before T-PSC in the perampanel and placebo arms, respectively. There were more TEAEs after T-PSC with placebo as compared to perampanel (Fisher exact odds ratio = 8.6, p = .035), which resulted in overestimation of the difference in TEAE rate. There was a numerical reduction in serious TEAEs (3/13 occurred after T-PSC, one in placebo and two in perampanel).

SIGNIFICANCE

Almost all TEAEs occurred before T-PSC. More treatment-related TEAEs occurred after T-PSC for participants randomized to placebo than perampanel, which may be due to either a shorter T-PSC or delayed time to TEAE for placebo.

Blood donor return behavior in South Africa and the United States before and during the COVID-19 pandemic

BACKGROUND

Studies preceding the COVID-19 pandemic found that slower time-to-return was associated with first-time, deferred, and mobile drive blood donors. How donor return dynamics changed during the COVID-19 pandemic is not well understood.

METHODS

We analyzed visits by whole blood donors from 2017 to 2022 in South Africa (SA) and the United States (US) stratified by mobile and fixed environment, first-time and repeat donor status, and pre-COVID19 (before March 2020) and intra-COVID19. We used Kaplan-Meier curves to characterize time-to-return, cumulative incidence functions to analyze switching between donation environments, and Cox proportional hazards models to analyze factors influencing time-to-return.

RESULTS

Overall time-to-return was shorter in SA. Pre-COVID19, the proportion of donors returning within a year of becoming eligible was lower for deferred donors in both countries regardless of donation environment and deferral type. Intra-COVID19, the gap between deferred and non-deferred donors widened in the US but narrowed in SA, where efforts to schedule return visits from deferred donors were intensified, particularly for non-hemoglobin-related deferrals. Intra-COVID19, the proportion of donors returning within a year in SA was higher for deferred first-time donors (>81%) than for successful first-time donors (80% at fixed sites; 69% at mobile drives).

CONCLUSIONS

The pandemic complicated efforts to recruit new donors and schedule returning visits after completed donations. Concerted efforts to improve time-to-return for deferred donors helped mitigate donation loss in SA during the public health emergency.

SurvdigitizeR: an algorithm for automated survival curve digitization

BACKGROUND

Decision analytic models and meta-analyses often rely on survival probabilities that are digitized from published Kaplan-Meier (KM) curves. However, manually extracting these probabilities from KM curves is time-consuming, expensive, and error-prone. We developed an efficient and accurate algorithm that automates extraction of survival probabilities from KM curves.

METHODS

The automated digitization algorithm processes images from a JPG or PNG format, converts them in their hue, saturation, and lightness scale and uses optical character recognition to detect axis location and labels. It also uses a k-medoids clustering algorithm to separate multiple overlapping curves on the same figure. To validate performance, we generated survival plots form random time-to-event data from a sample size of 25, 50, 150, and 250, 1000 individuals split into 1,2, or 3 treatment arms. We assumed an exponential distribution and applied random censoring. We compared automated digitization and manual digitization performed by well-trained researchers. We calculated the root mean squared error (RMSE) at 100-time points for both methods. The algorithm's performance was also evaluated by Bland-Altman analysis for the agreement between automated and manual digitization on a real-world set of published KM curves.

RESULTS

The automated digitizer accurately identified survival probabilities over time in the simulated KM curves. The average RMSE for automated digitization was 0.012, while manual digitization had an average RMSE of 0.014. Its performance was negatively correlated with the number of curves in a figure and the presence of censoring markers. In real-world scenarios, automated digitization and manual digitization showed very close agreement.

CONCLUSIONS

The algorithm streamlines the digitization process and requires minimal user input. It effectively digitized KM curves in simulated and real-world scenarios, demonstrating accuracy comparable to conventional manual digitization. The algorithm has been developed as an open-source R package and as a Shiny application and is available on GitHub: https://github.com/Pechli-Lab/SurvdigitizeR and https://pechlilab.shinyapps.io/SurvdigitizeR/ .

Persistent poverty disparities in incidence and outcomes among oral and pharynx cancer patients

PURPOSE

Disparities in oral cavity and pharyngeal cancer based on race/ethnicity and socioeconomic status have been reported, but the impact of living within areas that are persistently poor at the time of diagnosis and outcome is unknown. This study aimed to investigate whether the incidence, 5-year relative survival, stage at diagnosis, and mortality among patients with oral cavity and pharyngeal cancers varied by persistent poverty.

METHODS

Data were drawn from the SEER database (2006-2017) and included individuals diagnosed with oral cavity and pharyngeal cancers. Persistent poverty (at census tract) is defined as areas where ≥ 20% of the population has lived below the poverty level for ~ 30 years. Age-adjusted incidence and 5-year survival rates were calculated. Multivariable logistic regression was used to estimate the association between persistent poverty and advanced stage cancer. Cumulative incidence and multivariable subdistribution hazard models were used to evaluate mortality risk. In addition, results were stratified by cancer primary site, sex, race/ethnicity, and rurality.

RESULTS

Of the 90,631 patients included in the analysis (61.7% < 65 years old, 71.6% males), 8.8% lived in persistent poverty. Compared to non-persistent poverty, patients in persistent poverty had higher incidence and lower 5-year survival rates. Throughout 10 years, the cumulative incidence of cancer death was greater in patients from persistent poverty and were more likely to present with advanced-stage cancer and higher mortality risk. In the stratified analysis by primary site, patients in persistent poverty with oropharyngeal, oral cavity, and nasopharyngeal cancers had an increased risk of mortality compared to the patients in non-persistent poverty.

CONCLUSION

This study found an association between oral cavity and pharyngeal cancer outcomes among patients in persistent poverty indicating a multidimensional strategy to improve survival.

Mutations in myeloid transcription factors and activated signaling genes predict chronic myeloid leukemia outcomes

ABSTRACT

Advancements in genomics are transforming the clinical management of chronic myeloid leukemia (CML) toward precision medicine. The impact of somatic mutations on treatment outcomes is still under debate. We studied the association of somatic mutations in epigenetic modifier genes and activated signaling/myeloid transcription factors (AS/MTFs) with disease progression and treatment failure in patients with CML after tyrosine kinase inhibitor (TKI) therapy. A total of 394 CML samples were sequenced, including 254 samples collected at initial diagnosis and 140 samples taken during follow-up. Single-molecule molecular inversion probe (smMIP)-based next-generation sequencing (NGS) was conducted targeting recurrently mutated loci in 40 genes, with a limit of detection of 0.2%. Seventy mutations were detected in 57 diagnostic samples (22.4%), whereas 64 mutations were detected in 39 of the follow-up samples (27.9%). Carrying any mutation at initial diagnosis was associated with worse outcomes after TKI therapy, particularly in AS/MTF genes. Patients having these mutations at initial diagnosis and treated with imatinib showed higher risks of treatment failure (hazard ratio, 2.53; 95% confidence interval, 1.13-5.66; P = .0239). The adverse prognostic impact of the mutations was not clear for patients treated with second-generation TKIs. The multivariate analysis affirmed that mutations in AS/MTF genes independently serve as adverse prognostic factors for molecular response, failure-free survival, and progression risk. Additionally, there was an observable nonsignificant trend indicating a heightened risk of progression to advanced disease and worse overall survival. In conclusion, mutations in the AS/MTF genes using smMIP-based NGS can help identify patients with a potential risk of both treatment failure and progression and may help upfront TKI selection.

Retrospective review of the toxicities and change in dosing patterns for pegaspargase in patients with acute lymphoblastic leukemia/lymphoma and T-cell lymphoma

INTRODUCTION

Pegaspargase (PEG) is a key component of standard regimens for acute lymphoblastic leukemia/lymphoma (ALL) and extranodal natural killer/T-cell lymphoma (NKTCL). Emerging evidence suggests an opportunity to decrease incidence of PEG-associated toxicities with dose capping, but evidence is limited. This study aims to evaluate whether a significant difference in PEG-associated toxicities related to dosing strategy exists and to identify patient-specific or regimen-specific factors for PEG-related toxicity.

METHODS

A retrospective analysis of PEG-associated toxicities was completed in adult patients with ALL or NKTCL who received PEG within Cancer and Leukemia Group B (CALGB) 10403 or modified dexamethasone, methotrexate, ifosfamide, L-asparaginase, etoposide (mSMILE) regimens at the UW Medical Center/Fred Hutchinson Cancer Center. PEG-associated toxicities that occurred through 8 weeks after PEG doses were noted.

RESULTS

Twenty-eight patients received dose-capped PEG, and 29 received noncapped PEG. Fewer all-grade and grade 3/4 toxicities were observed in the dose-capped cohort. Grade 3/4 toxicities observed were hepatotoxicity, hyperglycemia, hypersensitivity, and hypertriglyceridemia. In addition, fewer grade 3/4 pancreatitis and thrombosis events occurred in the dose-capped cohort. Hypertriglyceridemia and hepatotoxicity were associated with the highest cumulative incidence proportions among all toxicities.

CONCLUSION

Dose capping of PEG was associated with a similar or later median onset for most toxicities, a less heterogeneic toxicity profile, and a lower recurrence of most toxicities upon PEG rechallenge compared to the non-dose-capped cohort. Standardizing PEG dose capping in the CALGB 10403 and mSMILE regimens may translate to improved tolerance compared to a historical standard of no dose capping PEG.

Methodological biases in observational hospital studies of COVID-19 treatment effectiveness: pitfalls and potential

Introduction

This study aims to discuss and assess the impact of three prevalent methodological biases: competing risks, immortal-time bias, and confounding bias in real-world observational studies evaluating treatment effectiveness. We use a demonstrative observational data example of COVID-19 patients to assess the impact of these biases and propose potential solutions.

Methods

We describe competing risks, immortal-time bias, and time-fixed confounding bias by evaluating treatment effectiveness in hospitalized patients with COVID-19. For our demonstrative analysis, we use observational data from the registry of patients with COVID-19 who were admitted to the Bellvitge University Hospital in Spain from March 2020 to February 2021 and met our predefined inclusion criteria. We compare estimates of a single-dose, time-dependent treatment with the standard of care. We analyze the treatment effectiveness using common statistical approaches, either by ignoring or only partially accounting for the methodological biases. To address these challenges, we emulate a target trial through the clone-censor-weight approach.

Results

Overlooking competing risk bias and employing the naïve Kaplan-Meier estimator led to increased in-hospital death probabilities in patients with COVID-19. Specifically, in the treatment effectiveness analysis, the Kaplan-Meier estimator resulted in an in-hospital mortality of 45.6% for treated patients and 59.0% for untreated patients. In contrast, employing an emulated trial framework with the weighted Aalen-Johansen estimator, we observed that in-hospital death probabilities were reduced to 27.9% in the "X"-treated arm and 40.1% in the non-"X"-treated arm. Immortal-time bias led to an underestimated hazard ratio of treatment.

Conclusion

Overlooking competing risks, immortal-time bias, and confounding bias leads to shifted estimates of treatment effects. Applying the naïve Kaplan-Meier method resulted in the most biased results and overestimated probabilities for the primary outcome in analyses of hospital data from COVID-19 patients. This overestimation could mislead clinical decision-making. Both immortal-time bias and confounding bias must be addressed in assessments of treatment effectiveness. The trial emulation framework offers a potential solution to address all three methodological biases.

Cardiovascular events after cancer immunotherapy as oncologic emergencies: Analyses of 610 head and neck cancer patients treated with immune checkpoint inhibitors

BACKGROUND

Cardio-oncology and emergency medicine are closely collaborative, as many cardiac events in cancer patients require evaluation and treatment in the emergency department (ED). Immune checkpoint inhibitors (ICIs) have become a common treatment for patients with head and neck cancer (HNC). However, the immune-related adverse events (irAEs) from ICIs can be clinically significant.

METHODS

We reviewed and analyzed cardiovascular diagnoses among HNC patients who received ICI during the period April 1, 2016-December 31, 2020 in a large tertiary cancer center. Demographics, clinical and cancer-related data were abstracted, and billing databases were queried for cardiovascular disease (CVD)-related diagnosis using International Classification of Disease-version10 (ICD-10) codes. We recorded receipt of care at the ED as one of the outcome variables.

RESULTS

A total of 610 HNC patients with a median follow-up time of 12.3 months (median, interquartile range = 5-30 months) comprised our study cohort. Overall, 25.7% of patients had pre-existing CVD prior to ICI treatment. Of the remaining 453 patients without pre-existing CVD, 31.5% (n = 143) had at least one CVD-related diagnosis after ICI initiation. Tachyarrhythmias (91 new events) was the most frequent CVD-related diagnosis after ICI. The time to diagnosis of myocarditis from initiation of ICI occurred the earliest (median 2.5 months, 1.5-6.8 months), followed by myocardial infarction (3.7, 0.5-9), cardiomyopathy (4.5, 1.6-7.3), and tachyarrhythmias (4.9, 1.2-11.4). Patients with myocarditis and tachyarrhythmias mainly presented to the ED for care.

CONCLUSION

The use of ICI in HNC is still expanding and the spectrum of delayed manifestation of ICI-induced cardiovascular toxicities is yet to be fully defined in HNC survivors.

A review on statistical and machine learning competing risks methods

When modeling competing risks (CR) survival data, several techniques have been proposed in both the statistical and machine learning literature. State-of-the-art methods have extended classical approaches with more flexible assumptions that can improve predictive performance, allow high-dimensional data and missing values, among others. Despite this, modern approaches have not been widely employed in applied settings. This article aims to aid the uptake of such methods by providing a condensed compendium of CR survival methods with a unified notation and interpretation across approaches. We highlight available software and, when possible, demonstrate their usage via reproducible R vignettes. Moreover, we discuss two major concerns that can affect benchmark studies in this context: the choice of performance metrics and reproducibility.

The 10-year follow-up of a community-based cohort of people with diabetes: The incidence of foot ulceration and death

BACKGROUND

Identifying people with diabetes who are likely to experience a foot ulcer is an important part of preventative care. Many cohort studies report predictive models for foot ulcerations and for people with diabetes, but reports of long-term outcomes are scarce.

AIM

We aimed to develop a predictive model for foot ulceration in diabetes using a range of potential risk factors with a follow-up of 10 years after recruitment. A new foot ulceration was the outcome of interest and death was the secondary outcome of interest.

DESIGN

A 10-year follow-up cohort study.

METHODS

1193 people with a diagnosis of diabetes who took part in a study in 2006-2007 were invited to participate in a 10-year follow-up. We developed a prognostic model for the incidence of incident foot ulcerations using a survival analysis, Cox proportional hazards model. We also utilised survival analysis Kaplan-Meier curves, and relevant tests, to assess the association between the predictor variables for foot ulceration and death.

RESULTS

At 10-year follow-up, 41% of the original study population had died and more than 18% had developed a foot ulcer. The predictive factors for foot ulceration were an inability to feel a 10 g monofilament or vibration from a tuning fork, previous foot ulceration and duration of diabetes.

CONCLUSIONS

The prognostic model shows an increased risk of ulceration for those with previous history of foot ulcerations, insensitivity to a 10 g monofilament, a tuning fork and duration of diabetes. The incidence of foot ulceration at 10-year follow-up was 18%; however, the risk of death for this community-based population was far greater than the risk of foot ulceration.

Relapses in Illicit Drug Use Among Probationers: Results in a Risk Group of Public Health Services in Bavaria

Objective: We aimed to identify in this study time trends of relapses in the illicit consumption of narcotics in a special at-risk population of former drug users under a public health perspective. Methods: In a pooled dataset of 14 consecutive calendar years (2006-2019), the use of seven different narcotic substances was studied in 380 persons with a total of 2,928 urine samples which were analyzed using a valid marker system for narcotic residues. Results: During the entire observation period, the relapse rate for cannabinoids and opiates was the highest despite abstinence requirements. It was noticeable that the relapses across all narcotics groups occurred primarily during the first 3 years of the probation period (90%) with a decrease in illegal consumption during the following years of the observation period. Conclusion: Special attention should be paid to probationers at the beginning of the probation period to develop more effective prevention strategies for substance abstinence by all involved actors in public health services.

The effect of discontinuing beta-blockers after different treatment durations following acute myocardial infarction in optimally treated, stable patients without heart failure: a Danish, nationwide cohort study

AIMS

We studied the effect of discontinuing beta-blockers following myocardial infarction in comparison to continuous beta-blocker use in optimally treated, stable patients without heart failure.

METHODS AND RESULTS

Using nationwide registers, we identified first-time myocardial infarction patients treated with beta-blockers following percutaneous coronary intervention or coronary angiography. The analysis was based on landmarks selected as 1, 2, 3, 4, and 5 years after the first redeemed beta-blocker prescription date. The outcomes included all-cause death, cardiovascular death, recurrent myocardial infarction, and a composite outcome of cardiovascular events and procedures. We used logistic regression and reported standardized absolute 5-year risks and risk differences at each landmark year. Among 21 220 first-time myocardial infarction patients, beta-blocker discontinuation was not associated with an increased risk of all-cause death, cardiovascular death, or recurrent myocardial infarction compared with patients continuing beta-blockers (landmark year 5; absolute risk difference [95% confidence interval]), correspondingly; -4.19% [-8.95%; 0.57%], -1.18% [-4.11%; 1.75%], and -0.37% [-4.56%; 3.82%]). Further, beta-blocker discontinuation within 2 years after myocardial infarction was associated with an increased risk of the composite outcome (landmark year 2; absolute risk [95% confidence interval] 19.87% [17.29%; 22.46%]) compared with continued beta-blocker use (landmark year 2; absolute risk [95% confidence interval] 17.10% [16.34%; 17.87%]), which yielded an absolute risk difference [95% confidence interval] at -2.8% [-5.4%; -0.1%], however, there was no risk difference associated with discontinuation hereafter.

CONCLUSION

Discontinuation of beta-blockers 1 year or later after a myocardial infarction without heart failure was not associated with increased serious adverse events.

Statistical approaches to identifying significant differences in predictive performance between machine learning and classical statistical models for survival data

Research that seeks to compare two predictive models requires a thorough statistical approach to draw valid inferences about comparisons between the performance of the two models. Researchers present estimates of model performance with little evidence on whether they reflect true differences in model performance. In this study, we apply two statistical tests, that is, the 5 × 2-fold cv paired t-test, and the combined 5 × 2-fold cv F-test to provide statistical evidence on differences in predictive performance between the Fine-Gray (FG) and random survival forest (RSF) models for competing risks. These models are trained on different scenarios of low-dimensional simulated survival data to determine whether the differences in their predictive performance that exist are indeed significant. Each simulation was repeated one hundred times on ten different seeds. The results indicate that the RSF model is superior in predictive performance in the presence of complex relationships (quadratic and interactions) between the outcome and its predictors. The two statistical tests show that the differences in performance are significant in quadratic simulation but not significant in interaction simulations. The study has also revealed that the FG model is superior in predictive performance in linear simulations and its differences in predictive performance compared to the RSF model are significant. The combined 5 × 2-fold cv F-test has lower type I error rates compared to the 5 × 2-fold cv paired t-test.

Pretransplant survival of patients with end-stage heart failure under competing risks

Heart transplantation is the gold standard of care for end-stage heart failure in the United States. Donor hearts are a scarce resource, however the current allocation policy—proposed in 2016 and implemented in 2018—has not addressed certain disparities. Between 2005 and 2016, the number of active candidates increased 127%, whereas transplant rates decreased 27.8%. Pretransplant mortality rates declined steadily for that period from 14.6 to 9.7, especially for candidates with mechanical circulatory assistive devices (MCSDs). This study reports survival analyses of candidates for heart transplantation list under competing events of transplantation and MCSD implantation. We queried the transplant data for a cohort of adult patients (age ≥ 16) without MCSDs prior to listing for transplantation between 2005 and 2014 (n = 23,373). We used cause-specific and subdistribution hazards models as multivariate regressions for all competing events. Patients listed as low priority for transplantation are less likely to require implantation but less likely to survive after 1,000 days of listing than patients listed at higher priorities. The current policy does not address this disparity as it focuses on stratifying patients with different types of MCSD. Clinical characteristics must be considered in prioritization.

Effect of sutureless securement on hemodialysis catheter-related bloodstream infection

The use of sutureless securement devices during catheterization might reduce the risk of catheter-related bloodstream infection (CRBSI) by suppressing catheter-exit infection and catheter dislodgement. However, the effectiveness of these devices in reducing CRBSI risk when securing hemodialysis catheters has not been explored. This single-center retrospective observational study examined 211 non-tunneled hemodialysis catheters (NTHCs) from 110 hemodialysis inpatients, of which 121 were secured using conventional skin sutures (Suture group) and 90 with GRIP-LOK (GRIP-LOK group). The stabilized inverse probability of treatment (SIPT)-weighting method was used to generate a new population (SIPT-weighted model) without group differences for each of the 12 predictors of CRBSI development (i.e., age, sex, dialysis history, concomitant acute kidney injury or diabetes, concurrent use of immunosuppressant drugs or aspirin, NTHC insertion site, methicillin-resistant Staphylococcus aureus, carriage, bacteremia event within 3 months before catheterization, hemoglobin level, and serum albumin titer). The effect of GRIP-LOK compared with sutures on CRBSI in the SIPT-weighted model was evaluated using univariate SIPT-weighted Cox proportional regression analysis, which showed a significant CRBSI suppression effect of GRIP-LOK compared with sutures (hazard ratio: 0.17 [95% CI 0.04–0.78], p = 0.023).　GRIP-LOK affords a lower risk of CRBSI due to indwelling NTHCs than conventional securement using sutures.

Development and validation of a prognostic model for non-lung cancer death in elderly patients treated with stereotactic body radiotherapy for non-small cell lung cancer

This study sought to develop and validate a prognostic model for non-lung cancer death (NLCD) in elderly patients with non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT). Patients aged ≥65 diagnosed with NSCLC (Tis-4N0M0), tumor diameter ≤5 cm and SBRT between 1998 and 2015 were retrospectively registered from two independent institutions. One institution was used for model development (arm D, 353 patients) and the other for validation (arm V, 401 patients). To identify risk factors for NLCD, multiple regression analysis on age, sex, performance status (PS), body mass index (BMI), Charlson comorbidity index (CCI), tumor diameter, histology and T-stage was performed on arm D. A score calculated using the regression coefficient was assigned to each factor and three risk groups were defined based on total score. Scores of 1.0 (BMI ≤18.4), 1.5 (age ≥ 5), 1.5 (PS ≥2), 2.5 (CCI 1 or 2) and 3 (CCI ≥3) were assigned, and risk groups were designated as low (total ≤ 3), intermediate (3.5 or 4) and high (≥4.5). The cumulative incidences of NLCD at 5 years in the low, intermediate and high-risk groups were 6.8, 23 and 40% in arm D, and 23, 19 and 44% in arm V, respectively. The AUC index at 5 years was 0.705 (arm D) and 0.632 (arm V). The proposed scoring system showed usefulness in predicting a high risk of NLCD in elderly patients treated with SBRT for NSCLC.

Nomograms for predicting cancer-specific survival in patients with primary central nervous system lymphoma: a population-based analysis

Background

This study identified the risk factors for survival in patients with primary central nervous system lymphoma (PCNSL). Nomograms were developed and validated to predict individualized overall survival (OS) and cancer-specific survival (CSS) in this particular cohort.

Methods

Patients diagnosed with PCNSL between 1975 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database for this study. The Cox regression model, the Fine and Grey's model, and the backward method were applied to determine the risk factors for OS and CSS. Nomograms were established accordingly. Internal and external validation was performed in an Asian population to examine the accuracy of the nomograms.

Results

A total of 5,900 patients with PCNSL were identified from the SEER database. A further 163 patients with PCNSL from the Beijing Tiantan Hospital between 2004 and 2018 were included. Age at diagnosis, tumor site, pathological subtype, surgery, chemotherapy, coexisting malignancies, and HIV infection were independent risk factors of CSS. In addition to the risk factors of CSS, gender, marital status, and radiation were also independent factors of OS. Nomograms were developed to estimate the 1-, 3-, and 5-year OS and CSS. The discrimination and calibration of the nomograms performed well. The C-indexes of the nomograms for OS and CSS prediction were 0.728 [95% confidence interval (CI): 0.703-0.753] and 0.726 (95% CI: 0.696-0.756), respectively. In addition, compared with previously published OS nomograms, the newly established nomograms displayed superior prediction for OS.

Conclusions

Nomograms predicting the 1-, 3- and 5-year OS and CSS of patients with PCNSL were established in this study. The validated nomograms showed relatively good performance and may be used clinically to evaluate patients' individualized risk and prognosis with PCNSL. Free software for individualized survival prediction is provided at http://www.pcnsl-survivalprediction.cn.

Prior Resection of the Primary Tumor Prolongs Survival After Peptide Receptor Radionuclide Therapy of Advanced Neuroendocrine Neoplasms

OBJECTIVE

The aim of the study was to compare impact on survival after resection of primary tumors (PTs) after peptide receptor radionuclide therapy (PRRT).

BACKGROUND

PRRT is a highly effective therapeutic option to treat locally advanced or metastatic neuroendocrine neoplasms (NENs).

METHODS

We retrospectively analyzed the data of 889 patients with advanced NEN (G1-G3, stage IV) treated with at least 1 cycle of PRRT. In 486 of 889 patients (55%, group 1), PT had been removed before PRRT. Group 2 constituted 403 patients (45%) with no prior PT resection. Progression-free survival (PFS) and overall survival (OS) was determined by 68Ga SSTR-PET/CT in all patients applying RECIST and EORTC.

RESULTS

Most patients had their PT in pancreas (n = 335; 38%) and small intestine (n = 284; 32%). Both groups received a mean of 4 cycles of PRRT (P = 0.835) with a mean cumulative administered radioactivity of 21.6 ± 11.7 versus 22.2 ± 11.2 GBq (P = 0.407). Median OS in group 1 was 134.0 months [confidence interval (CI): 118-147], whereas OS in group 2 was 67.0 months (CI: 60-80; hazard ratio 2.79); P < 0.001. Likewise, the median progression-free survival after first PRRT was longer in group 1 with 18.0 (CI: 15-20) months as compared to group 2 with 14.0 (CI: 15-18; hazard ratio 1.21) months; P = 0.012.

CONCLUSIONS

A previous resection of the PT before PRRT provides a significant survival benefit in patients with NENs stage IV.

Effect of long-term beta-blocker treatment following myocardial infarction among stable, optimally treated patients without heart failure in the reperfusion era: a Danish, nationwide cohort study

AIMS

We aimed to investigate the long-term cardio-protective effect associated with beta-blocker (BB) treatment in stable, optimally treated myocardial infarction (MI) patients without heart failure (HF).

METHODS AND RESULTS

Using nationwide registries, we included patients with first-time MI undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI) during admission and treated with both acetyl-salicylic acid and statins post-discharge between 2003 and 2018. Patients with prior history of MI, prior BB use, or any alternative indication or contraindication for BB treatment were excluded. Follow-up began 3 months following discharge in patients alive, free of cardiovascular (CV) events or procedures. Primary outcomes were CV death, recurrent MI, and a composite outcome of CV events. We used adjusted logistic regression and reported standardized absolute risks and differences (ARD) 3 years after MI. Overall, 30 177 stable, optimally treated MI patients were included (58% acute PCI, 26% sub-acute PCI, 16% CAG without intervention). At baseline, 82% of patients were on BB treatment (median age 61 years, 75% male) and 18% were not (median age 62 years, 68% male). BB treatment was associated with a similar risk of CV death, recurrent MI, and the composite outcome of CV events compared with no BB treatment [ARD (95% confidence intervals)] correspondingly; 0.1% (-0.3% to 0.5%), 0.2% (-0.7% to 1.2%), and 1.2% (-0.2% to 2.7%).

CONCLUSIONS

In this nationwide cohort study of stable, optimally treated MI patients without HF, we found no long-term effect of BB treatment on CV prognosis following the patients from 3 months to 3 years after MI admission.

Early Posttransplant Blood Transfusion and Risk for Worse Graft Outcomes

Introduction

Blood transfusion is a risk factor for allosensitization. Nevertheless, blood transfusion posttransplant remains a common practice. We evaluated the effect of posttransplant blood transfusion on graft outcomes.

Methods

We included nonsensitized, first-time, kidney-alone recipients transplanted between 1 July 2015 and 31 December 2017. Patients were grouped based on receiving blood transfusion in the first 30 days posttransplant. The primary end point was a composite outcome of biopsy-proven acute rejection, death of any cause, or graft failure in the first year posttransplant. Secondary outcomes included the individual components of the primary outcome and the cumulative incidence of de novo donor-specific antibodies (DSAs).

Results

Two hundred seventy-three patients were included. One hundred twenty-seven (47%) received blood transfusion. Patients in the transfusion group were more likely to be older, have had a deceased donor, and have received induction with basiliximab. There was no difference between groups in the composite primary outcome (adjusted hazard ratio = [HR] 1.34; 95% confidence interval [CI], 0.83–2.17; P = 0.23). The cumulative incidence of de novo DSAs during the first year posttransplant was similar between groups (12.8% transfusion vs. 10.9% no transfusion, P = 0.48).

Conclusion

Early transfusion of blood products in kidney transplant recipients receiving induction with lymphocyte depletion was not associated with an increased hazard of experiencing acute rejection, death from any cause, or graft loss.

All-cause and cause-specific mortality in microscopic colitis: a Danish nationwide matched cohort study

BACKGROUND

The long-term natural history of microscopic colitis remains uncertain.

AIM

To describe the mortality in a large unselected cohort of patients with microscopic colitis.

METHODS

All Danish patients above 18 years with an incident diagnosis of microscopic colitis from 2001 to 2018 were identified from nationwide registries and compared to age- and sex-matched controls (variable 1:10 ratio). Patients were categorised according to subtypes: lymphocytic colitis and collagenous colitis. The relative risk of death by any cause was analysed with Cox regression models estimating both crude and comorbidity-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs). Cause-specific death was evaluated with cumulative incidence functions. An E-value was calculated to address the impact of unmeasured confounding.

RESULTS

The final cohort consisted of 14 024 patients with microscopic colitis. The mean follow-up was 5.8 (standard deviation SD, 2.9) years and the mean age at diagnosis was 61.1 (SD 13.9) years, 70% were women and 41% were diagnosed with lymphocytic colitis. The main results showed a 25% increased risk of all-cause death in patients with microscopic colitis; however, the relative risk was attenuated to 9% when adjusting for comorbidities (95% CI, 1.05-1.14). The E-value indicates that unmeasured confounding could explain the residual observed increased all-cause mortality. Mortality was significantly increased in patients with both lymphocytic colitis (HR 1.15; 95% CI, 1.08-1.23) and collagenous colitis (HR 1.06; 95% CI, 1.01-1.12) in fully adjusted analyses. The absolute difference in death between patients with microscopic colitis and matches was 0.9% at 1 year, 2.8% at 5 years, 5.0% at 10 years and 3.0% at 15 years. Cumulative incidence functions showed that patients with microscopic colitis were more likely to die due to smoking-related diseases including ischemic heart and lung diseases, but had a significant decreased risk of death due to colorectal cancers (P < 0.0001).

CONCLUSION

In an unselected large nationwide cohort of patients with microscopic colitis, the risk of death was significantly increased compared to the background population. However, the increased mortality seemed to be associated to a high burden of comorbidities and unmeasured life-style factors including smoking and not microscopic colitis per se.

Patient characteristics and outcomes after ruxolitinib discontinuation in patients with myelofibrosis

Background: This retrospective analysis evaluates morbidities, outcomes and associated risk factors in patients with myelofibrosis (MF) after ruxolitinib discontinuation, using Truven Health Analytics MarketScan (TR), Optum integrated virtual electronic health records and claims databases (OP), and Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database (SM).Methods: A total of 290 patients with MF between 2006 and 2015 (using ICD-9 and ICD-O-3 codes), who were treated with and discontinued ruxolitinib were identified. Only patients with ≥90 days of medical history prior to index diagnosis (TR + OP) and Part A, B, and D enrollment at the time of index diagnosis (SM) were included. Morbidities were assessed during the 30-day period each following ruxolitinib initiation, prior to and post ruxolitinib discontinuation. Cumulative incidence of cytopenias and efficacy outcomes were evaluated from baseline.Results: Median age of patients was 68 years, with equal proportion of either gender. Median time to ruxolitinib discontinuation was 284 days and median follow-up after discontinuation was 70.9 days. The majority of patients were diagnosed with anemia and >30% of the patients received RBC transfusions during 30-day period prior to and the 30-day period post ruxolitinib discontinuation. After ruxolitinib discontinuation, half of the patients developed cytopenias. The median treatment progression-free survival, and overall survival after ruxolitinib discontinuation were 6.0 (4.4, 8.3) months and 11.1 (8.4, 14.5) months, respectively. Age at ruxolitinib discontinuation (HR [95% CI] = 2.071 [1.320, 3.248]), Charlson Comorbidity Index score (HR [95% CI] = 1.172 [1.093, 1.257]) and gender (HR [95% CI] = 1.620 [1.108, 2.369]) increased the risk of treatment progression (start of the subsequent treatment regimen) or death.Conclusion: Results from this large, retrospective, US population-based outcome analysis of MF patients show an increase in morbidity burden and identifies the risk factors of survival outcomes among real-world patients who have discontinued ruxolitinib.

Generic escitalopram initiation and substitution among Medicare beneficiaries: A new user cohort study

OBJECTIVES

To examine patterns of generic escitalopram initiation and substitution among Medicare beneficiaries.

METHODS

This retrospective new user cohort used a 5% random sample of 2013-2015 Medicare administrative claims data. Fee-for-service Medicare beneficiaries continuously enrolled in Parts A, B, and D during a 6-month washout period prior to their initial generic or brand oral escitalopram prescriptions were included (n = 12,351). The primary outcomes were generic escitalopram treatment initiation, and among brand escitalopram initiators, generic substitution within 12 months. Patient demographics, health service utilization, and prescription level factors were measured and assessed.

RESULTS

Among all escitalopram initiators, about 88.2% Medicare beneficiaries initiated generic escitalopram. Beneficiaries who were younger age, male, residing in non-Northeast regions or urban area, in the Part D plan deductible benefit phase, and filling prescriptions at community/retail pharmacies were more likely to initiate generic treatment. Among brand escitalopram initiators (n = 1,464), about 20.7% switched to generic escitalopram, 31.2% switched to another alternative antidepressant, 25.1% discontinued treatment, and 8.7% were lost to follow up or passed away within 12 months after brand initiation. Factors associated with generic escitalopram substitution included region (Midwest vs. Northeast, adjusted hazard ratio (HR) = 1.46, 95% CI = 1.04-2.05), pre-index hospitalization (HR = 1.31; 95% CI = 1.16-1.48) and lower escitalopram average daily dosage (HR = 0.97; 95% CI = 0.95-0.99).

CONCLUSIONS

In 2013-2015, almost 90% Medicare beneficiaries initiated generic escitalopram treatment. Among brand escitalopram initiators, about 1 in 5 patients switched to generic escitalopram within 1 year, as compared to 1 in 4 or 1 in 3 who discontinued current or switched to alternative treatment, respectively. Medicare beneficiary's geographic region was independently associated with generic escitalopram initiation and substitution. Findings from this study not only provide up-to-date evidence in generic escitalopram use patterns among Medicare population, but also can guide educational and practice interventions to further increase generic escitalopram use.

Ignoring competing events in the analysis of survival data may lead to biased results: a nonmathematical illustration of competing risk analysis

OBJECTIVE

Competing events are often ignored in epidemiological studies. Conventional methods for the analysis of survival data assume independent or noninformative censoring, which is violated when subjects that experience a competing event are censored. Because many survival studies do not apply competing risk analysis, we explain and illustrate in a nonmathematical way how to analyze and interpret survival data in the presence of competing events.

STUDY DESIGN AND SETTING

Using data from the Longitudinal Aging Study Amsterdam, both marginal analyses (Kaplan-Meier method and Cox proportional-hazards regression) and competing risk analyses (cumulative incidence function [CIF], cause-specific and subdistribution hazard regression) were performed. We analyzed the association between sex and depressive symptoms, in which death before the onset of depression was a competing event.

RESULTS

The Kaplan-Meier method overestimated the cumulative incidence of depressive symptoms. Instead, the CIF should be used. As the subdistribution hazard model has a one-to-one relation with the CIF, it is recommended for prediction research, whereas the cause-specific hazard model is recommended for etiologic research.

CONCLUSION

When competing risks are present, the type of research question guides the choice of the analytical model to be used. In any case, results should be presented for all event types.

Methods of competing risks flexible parametric modeling for estimation of the risk of the first disease among HIV infected men

Background

Patients infected with the Human Immunodeficiency Virus (HIV) are susceptible to many diseases. In these patients, the occurrence of one disease alters the chance of contracting another. Under such circumstances, methods for competing risks are required. Recently, competing risks analyses in the scope of flexible parametric models have risen to address this requirement. These lesser-known analyses have considerable advantages over conventional methods.

Methods

Using data from Multi Centre AIDS Cohort Study (MACS), this paper reviews and applies methods of competing risks flexible parametric models to analyze the risk of the first disease (AIDS or non-AIDS) among HIV-infected patients. We compared two alternative subdistribution hazard flexible parametric models (SDH_FPM1 and SDH_FPM2) with the Fine & Gray model. To make a complete inference, we performed cause-specific hazard flexible parametric models for each event separately as well.

Results

Both SDH_FPM1 and SDH_FPM2 provided consistent results regarding the magnitude of coefficients and risk estimations compared with estimations obtained from the Fine & Gray model, However, competing risks flexible parametric models provided more efficient and smoother estimations for the baseline risks of the first disease. We found that age at HIV diagnosis indirectly affected the risk of AIDS as the first event by increasing the number of patients who experience a non-AIDS disease prior to AIDS among > 40 years. Other significant covariates had direct effects on the risks of AIDS and non-AIDS.

Discussion

The choice of an appropriate model depends on the research goals and computational challenges. The SDH_FPM1 models each event separately and requires calculating censoring weights which is time-consuming. In contrast, SDH_FPM2 models all events simultaneously and is more appropriate for large datasets, however, when the focus is on one particular event SDH_FPM1 is more preferable.

Performance of FRAX in Predicting Fractures in US Postmenopausal Women with Varied Race and Genetic Profiles

BACKGROUND

Whether the Fracture Risk Assessment Tool (FRAX) performed differently in estimating the 10-year fracture probability in women of different genetic profiling and race remained unclear.

METHODS

The genomic data in the Women's Health Initiative (WHI) study was analyzed (n = 23,981). The genetic risk score (GRS) was calculated from 14 fracture-associated single nucleotide polymorphisms (SNPs) for each participant. FRAX without bone mineral density (BMD) was used to estimate fracture probability.

RESULTS

FRAX significantly overestimated the risk of major osteoporotic fracture (MOF) in the WHI study. The most significant overestimation was observed in women with low GRS (predicted/observed ratio (POR): 1.61, 95% CI: 1.45-1.79) specifically Asian women (POR: 3.5, 95% CI 2.48-4.81) and in African American women (POR: 2.59, 95% CI: 2.33-2.87). Compared to the low GRS group, the 10-year probability of MOF adjusted for the FRAX score was 21% and 30% higher in the median GRS group and high GRS group, respectively. Asian, African American, and Hispanic women respectively had a 78%, 76%, and 56% lower hazard than Caucasian women after the FRAX score was adjusted. The results were similar for hip fractures.

CONCLUSIONS

Our study suggested the FRAX performance varies significantly by both genetic profile and race in postmenopausal women.

Prospects and challenges for clinical decision support in the era of big data

Recently, there has been burgeoning interest in developing more effective and robust clinical decision support systems (CDSSs) for oncology. This has been primarily driven by the demands for more personalized and precise medical practice in oncology in the era of so-called Big Data (BD); an era that promises to harness the power of large-scale data flow to revolutionize cancer treatment. This interest in BD analytics has created new opportunities as well as new unmet challenges. These include: routine aggregation and standardization of clinical data; patient privacy; transformation of current analytical approaches to handle such noisy and heterogeneous data; and expanded use of advanced statistical learning methods based on confluence of modern statistical methods and machine learning algorithms. In this review, we present the current status of CDSSs in oncology, the prospects and current challenges of BD analytics, and the promising role of integrated modern statistics and machine learning algorithms in predicting complex clinical endpoints, individualizing treatment rules, and optimizing dynamic personalized treatment regimens. We discuss issues pertaining to these topics and present application examples from an aggregate of experiences. We also discuss the role of human factors in improving the utilization and acceptance of such enhanced CDSSs and how to mitigate possible sources of human error to achieve optimal performance and wider acceptance.

Canadian chronic myeloid leukemia outcomes post-transplant in the tyrosine kinase inhibitor era

The majority of patients with TKI failure respond to HCT. However, the relapse risk remains high. This study has evaluated transplant outcomes in 223 CML patients with TKI failure due to resistance (n = 132) or intolerance (n = 29), as well as those that were TKI naïve/responding with advanced disease (n = 35) or with chronic phase (CP, n = 27). We studied outcomes according to post-transplant BCR-ABL transcript level within 3 months. With respect to transplant outcomes according to the post-transplant BCR/ABLtranscript level within 3 months, the group failing to achieve a 1.3 log reduction (n = 14, 12.4%) showed the highest relapse rate of 78.6% at 5 years, compared to 26.2% and 24.1% in the groups achieving 1.3-4.0 log reduction (n = 45, 39.8%), and ≥4.1 log reduction (n = 54, 47.8%) respectively (p < 0.001). Multivariate analysis confirmed that the group failing to achieve a 1.3 log reduction had a 2.3-fold higher risk of death and 6.6 times higher risk of relapse. Poor overall survival after HCT was associated with advanced disease at diagnosis, but not disease status prior to HCT. Of 61 patients who relapsed after HCT, 47 were treated with post-transplant TKI therapy; those receiving TKI after loss of MR2 or MMR showed higher rates of response and survival compared to those receiving TKI after hematologic relapse (p < 0.001). QPCR log reduction level within 3 months post transplantation is prognostic in this population.

Natural history of neurological abnormalities in cerebrotendinous xanthomatosis

OBJECTIVES

Cerebrotendinous xanthomatosis (CTX) is a rare inherited neurodegenerative disorder in bile acid synthesis. The natural history of neurological abnormalities in CTX is not well understood. The object of this study was to determine neurological progression in CTX.

METHODS

A literature search on PubMed for "cerebrotendinous xanthomatosis" yielded 91 publications that reported cases of CTX patients. Two independent reviewers abstracted information about the presence and age of onset of neurological abnormalities in published CTX cases. For each neurological abnormality, we estimated the probability of its onset at any given age using cumulative incidence function analysis. We also present our own case series, in which five CTX patients were evaluated.

RESULTS

The literature search yielded 194 CTX cases (ages ranging from newborn to 67 years old). The most common neurological abnormalities were corticospinal tract abnormalities including weakness, hyperreflexia, spasticity, Babinski sign (59.8%), ataxia (58.8%), cognitive decline (46.4%), and gait difficulty (38.1%); 68 (35.0%) had baseline cognitive problems. Cumulative incidence function analysis revealed that ataxia, gait difficulties, and corticospinal tract abnormalities developed throughout life, while cognitive decline tended to develop later in life. Of the less common neurological abnormalities, seizures, psychiatric changes and speech changes developed throughout life, while parkinsonism and sensory changes tended to develop later in life. Our case series corroborated this temporal pattern of neurological abnormalities.

CONCLUSION

We provide estimates for the neurological progression of CTX, categorizing neurological abnormalities according to time and probability of development. Our approach may be applicable to other rare disorders.

The Combination of Beta Blockers and Renin-Angiotensin System Blockers Improves Survival in Incident Hemodialysis Patients: A Propensity-Matched Study

INTRODUCTION

Although several studies suggest that the prognosis of hypertensive dialysis patients can be improved by using antihypertensive drug therapy, it is unknown whether the prescription of a particular class or combination of antihypertensive drugs is beneficial during hemodialysis.

METHODS

We performed a propensity score matching study to compare the effectiveness of various classes of antihypertensive drugs on cardiovascular (CV) mortality in 2518 incident hemodialysis patients in Spain. The patients had initially received antihypertensive therapy with a renin-angiotensin system (RAS) blocker (728 patients), a ß-blocker (679 patients), antihypertensive drugs other than a RAS blocker or a ß-blocker (787 patients), or the combination of a ß-blocker and a RAS inhibitor (324 patients). These patients were followed for a maximum of 5 years (median: 2.21 yr; range: 1.04-3.34 yr).

RESULTS

After adjustment for baseline CV risk covariates, no significant differences were observed in the risk of CV mortality between patients taking a RAS blocker and patients treated with ß-blocker-based antihypertensive therapy. The combination of a RAS blocker with a ß-blocker was associated with better CV survival than either agent alone (RAS blocker: hazard ratio [HR]: 1.68; 95% confidence interval [CI] 1.05-2.69; ß-blocker: HR: 1.59; 95% CI: 1.01-2.50; antihypertensive medication other than a RAS blocker or ß-blocker: HR: 1.67; 95% CI: 1.08-2.58).

DISCUSSION

Our data suggested that the combination of a RAS blocker and a ß-blocker could improve survival in hemodialysis patients. Further prospective randomized controlled trials are necessary to confirm the beneficial effects of this combination of antihypertensive drugs in patients undergoing hemodialysis.

Flexible parametric modelling of the cause-specific cumulative incidence function

Competing risks arise with time-to-event data when individuals are at risk of more than one type of event and the occurrence of one event precludes the occurrence of all other events. A useful measure with competing risks is the cause-specific cumulative incidence function (CIF), which gives the probability of experiencing a particular event as a function of follow-up time, accounting for the fact that some individuals may have a competing event. When modelling the cause-specific CIF, the most common model is a semi-parametric proportional subhazards model. In this paper, we propose the use of flexible parametric survival models to directly model the cause-specific CIF where the effect of follow-up time is modelled using restricted cubic splines. The models provide smooth estimates of the cause-specific CIF with the important advantage that the approach is easily extended to model time-dependent effects. The models can be fitted using standard survival analysis tools by a combination of data expansion and introducing time-dependent weights. Various link functions are available that allow modelling on different scales and have proportional subhazards, proportional odds and relative absolute risks as particular cases. We conduct a simulation study to evaluate how well the spline functions approximate subhazard functions with complex shapes. The methods are illustrated using data from the European Blood and Marrow Transplantation Registry showing excellent agreement between parametric estimates of the cause-specific CIF and those obtained from a semi-parametric model. We also fit models relaxing the proportional subhazards assumption using alternative link functions and/or including time-dependent effects. Copyright © 2016 John Wiley & Sons, Ltd.

Application of the Multiplicative-Additive Model in the Bone Marrow Transplantation Survival Data Including Competing Risks

BACKGROUND

Cox proportional hazard model is a popular choice in modeling the survival data, but sometimes proportionality assumption is not satisfied. One of the tools for handling the non-proportional effects is the multiplicative-additive model named "Cox-Aalen model". Recently these flexible regression models developed for competing risks setting. The aim of this paper is showing the application of the multiplicative-additive model in competing risks setting on real bone marrow transplantation (BMT) data when the proportionality assumption is violated.

METHODS

The data was from a retrospective study on class III thalassemia patients who undergo hematopoietic stem cell transplantation (HSCT) in BMT ward of Shariatei Hospital, Tehran, Iran. The neutrophil engraftment time as the early outcome of HSCT on37 patients who received mesenchymal stem cell infusion (MSC group) compared with 50 patients who did not. We fit the standard proportional models and flexible Cox-Aalen model in the sub distribution hazards.

RESULTS

By day 30 after transplantation, the cumulative incidence of neutrophil recovery was 97% (95%CI: 89%-100%) and 76%(95%CI: 64%-88%) in MSC and control group, respectively. Based on the Cox-Aalen model for cumulative incidence function, the MSC infusion had a significant delay effect on neutrophil engraftment (P=.044). In patients who did not neutrophil recovery immediately after HSCT, those who received MSC had faster recovery.

CONCLUSION

Cox-Aalen model provides more accurate statistical description for time-varying covariate effects. There is a positive effect of MSCs on the neutrophil recovery, however further study on the advantages and disadvantages of MSCs are needed.

Weighted comparison of two cumulative incidence functions with R-CIFsmry package

In this paper we propose a class of flexible weight functions for use in comparison of two cumulative incidence functions. The proposed weights allow the users to focus their comparison on an early or a late time period post treatment or to treat all time points with equal emphasis. These weight functions can be used to compare two cumulative incidence functions via their risk difference, their relative risk, or their odds ratio. The proposed method has been implemented in the R-CIFsmry package which is readily available for download and is easy to use as illustrated in the example.

BCR/ABL level at 6 months identifies good risk CML subgroup after failing early molecular response at 3 months following imatinib therapy for CML in chronic phase

It is unclear if patients with CML treated with imatinib who fail to achieve BCR/ABL transcript levels <10%(IS) at 3 months i.e. an early molecular response (EMR) have a better prognosis if they achieve a response by 6 months. We reviewed 320 patients with chronic myeloid leukemia (CML) in chronic phase receiving Imatinib therapy with 3 and 6 month BCR/ABL transcript levels available, and divided them into four groups. Group I (achieved an EMR at 3 months), Group II (did not achieve an EMR at 3 months, but achieved a transcript level of <1% at 6 months), Group III (did not achieve an EMR at 3 months, then at 6 months achieved a level between 1% and 10%) and Group IV (failed to achieve a response at 3 and 6 months). Compared to Group I, Group IV showed significantly worse freedom from treatment failure (FTF; 93.1% vs 69.0%, P < 0.001), progression free survival (97.7% vs 77.3%, P < 0.001) and overall survival (98.3% vs 78.9%, P < 0.001). While, group III showed inferior PFS (98.3% vs 90.4%, P = 0.013) and OS (97.7% vs 90.4%, P = 0.037), but no difference in FTF (93.1% vs 92.0%, P = 0.520). There were no significant differences between Groups I and II. A BCR/ABL transcript level at 6 months can identify a "good-risk" subgroup among patients who fail to achieve an EMR on Imatinib therapy for CML.

Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases

BACKGROUND

Competing risks arise when the subject is exposed to more than one cause of failure. Data consists of the time that the subject failed and an indicator of which risk caused the subject to fail.

METHODS

With three approaches consisting of Fine and Gray, binomial, and pseudo-value, all of which are directly based on cumulative incidence function, cardiovascular disease data of the Isfahan Cohort Study were analyzed. Validity of proportionality assumption for these approaches is the basis for selecting appropriate models. Such as for the Fine and Gray model, establishing proportionality assumption is necessary. In the binomial approach, a parametric, non-parametric, or semi-parametric model was offered according to validity of assumption. However, pseudo-value approaches do not need to establish proportionality.

RESULTS

Following fitting the models to data, slight differences in parameters and variances estimates were seen among models. This showed that semi-parametric multiplicative model and the two models based on pseudo-value approach could be used for fitting this kind of data.

CONCLUSION

We would recommend considering the use of competing risk models instead of normal survival methods when subjects are exposed to more than one cause of failure.

A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions

Competing risks endpoints are frequently encountered in hematopoietic stem cell transplantation where patients are exposed to relapse and treatment-related mortality. Both cause-specific hazards and direct models for the cumulative incidence functions have been used for analyzing such competing risks endpoints. For both approaches, the popular models are of a proportional hazards type. Such models have been used for studying prognostic factors in acute and chronic leukemias. We argue that a complete understanding of the event dynamics requires that both hazards and cumulative incidence be analyzed side by side, and that this is generally the most rigorous scientific approach to analyzing competing risks data. That is, understanding the effects of covariates on cause-specific hazards and cumulative incidence functions go hand in hand. A case study illustrates our proposal.

Different competing risks models applied to data from the Australian Orthopaedic Association National Joint Replacement Registry

PURPOSE

Here we describe some available statistical models and illustrate their use for analysis of arthroplasty registry data in the presence of the competing risk of death, when the influence of covariates on the revision rate may be different to the influence on the probability (that is, risk) of the occurrence of revision.

PATIENTS AND METHODS

Records of 12,525 patients aged 75-84 years who had received hemiarthroplasty for fractured neck of femur were obtained from the Australian Orthopaedic Association National Joint Replacement Registry. The covariates whose effects we investigated were: age, sex, type of prosthesis, and type of fixation (cementless or cemented). Extensions of competing risk regression models were implemented, allowing the effects of some covariates to vary with time.

RESULTS

The revision rate was significantly higher for patients with unipolar than bipolar prostheses (HR = 1.38, 95% CI: 1.01-1.89) or with monoblock than bipolar prostheses (HR = 1.45, 95% CI: 1.08-1.94). It was significantly higher for the younger age group (75-79 years) than for the older one (80-84 years) (HR = 1.28, 95% CI: 1.05-1.56) and higher for males than for females (HR = 1.37, 95% CI: 1.09-1.71). The probability of revision, after correction for the competing risk of death, was only significantly higher for unipolar prostheses than for bipolar prostheses, and higher for the younger age group. The effect of fixation type varied with time; initially, there was a higher probability of revision for cementless prostheses than for cemented prostheses, which disappeared after approximately 1.5 years.

INTERPRETATION

When accounting for the competing risk of death, the covariates type of prosthesis and sex influenced the rate of revision differently to the probability of revision. We advocate the use of appropriate analysis tools in the presence of competing risks and when covariates have time-dependent effects.

NCI First International Workshop on the Biology, Prevention, and Treatment of Relapse after Allogeneic Hematopoietic Stem Cell Transplantation: report from the Committee on the Epidemiology and Natural History of Relapse following Allogeneic Cell Transplantation

Allogeneic hematopoietic stem cell transplantation (alloHSCT) is increasingly being used for treatment of hematologic malignancies, and the immunologic graft-versus-tumor effect (GVT) provides its therapeutic effectiveness. Disease relapse remains a cause of treatment failure in a significant proportion of patients undergoing alloHSCT without improvements over the last 2-3 decades. We summarize here current data and outline future research regarding the epidemiology, risk factors, and outcomes of relapse after alloHSCT. Although some factors (eg, disease status at alloHSCT or graft-versus-host disease [GVHD] effects) are common, other disease-specific factors may be unique. The impact of reduced-intensity regimens on relapse and survival still need to be assessed using contemporary supportive care and comparable patient populations. The outcome of patients relapsing after an alloHSCT generally remains poor even though interventions including donor leukocyte infusions can benefit some patients. Trials examining targeted therapies along with improved safety of alloHSCT may result in improved outcomes, yet selection bias necessitates prospective assessment to gauge the real contribution of any new therapies. Ongoing chronic GVHD (cGVHD) or other residual post-alloHSCT morbidities may limit the applicability of new therapies. Developing strategies to promptly identify patients as alloHSCT candidates, while malignancy is in a more treatable stage, could decrease relapses rates after alloHSCT. Better understanding and monitoring of minimal residual disease posttransplant could lead to novel preemptive treatments of relapse. Analyses of larger cohorts through multicenter collaborations or registries remain essential to probe questions not amenable to single center or prospective studies. Studies need to provide data with detail on disease status, prior treatments, biologic markers, and posttransplant events. Stringent statistical methods to study relapse remain an important area of research. The opportunities for improvement in prevention and management of post-alloHSCT relapse are apparent, but clinical discipline in their careful study remains important.