Kernel hazard estimation for visualisation of the effect of a continuous covariates on time‐to‐event endpoints

OBJECTIVEAdult spinal deformity (ASD) surgery has a high rate of major complications (MCs). Public information about adverse outcomes is currently limited to registry average estimates. The object of this study was to assess the incidence of adverse events after ASD surgery, and to develop and validate a prognostic tool for the time-to-event risk of MC, hospital readmission (RA), and unplanned reoperation (RO).METHODSTwo models per outcome, created with a random survival forest algorithm, were trained in an 80% random split and tested in the remaining 20%. Two independent prospective multicenter ASD databases, originating from the European continent and the United States, were queried, merged, and analyzed. ASD patients surgically treated by 57 surgeons at 23 sites in 5 countries in the period from 2008 to 2016 were included in the analysis.RESULTSThe final sample consisted of 1612 ASD patients: mean (standard deviation) age 56.7 (17.4) years, 76.6% women, 10.4 (4.3) fused vertebral levels, 55.1% of patients with pelvic fixation, 2047.9 observation-years. Kaplan-Meier estimates showed that 12.1% of patients had at least one MC at 10 days after surgery; 21.5%, at 90 days; and 36%, at 2 years. Discrimination, measured as the concordance statistic, was up to 71.7% (95% CI 68%–75%) in the development sample for the postoperative complications model. Surgical invasiveness, age, magnitude of deformity, and frailty were the strongest predictors of MCs. Individual cumulative risk estimates at 2 years ranged from 3.9% to 74.1% for MCs, from 3.17% to 44.2% for RAs, and from 2.67% to 51.9% for ROs.CONCLUSIONSThe creation of accurate prognostic models for the occurrence and timing of MCs, RAs, and ROs following ASD surgery is possible. The presented variability in patient risk profiles alongside the discrimination and calibration of the models highlights the potential benefits of obtaining time-to-event risk estimates for patients and clinicians.

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Faculty Opinions recommendation of Outcome of antibiotic prophylaxis discontinuation in patients with persistent vesicoureteral reflux initially presenting with febrile urinary tract infection: time to event analysis.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.5927960.5923058 ◽

2010 ◽

Author(s):

Serdar Tekgul ◽

Hasan Serkan Doðan

Keyword(s):

Urinary Tract Infection ◽

Urinary Tract ◽

Tract Infection ◽

Antibiotic Prophylaxis ◽

Vesicoureteral Reflux ◽

Event Analysis ◽

Time To Event ◽

Febrile Urinary Tract Infection ◽

Infection Time

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Functional modeling of recurrent events on time‐to‐event processes

Biometrical Journal ◽

10.1002/bimj.202000374 ◽

2021 ◽

Author(s):

Marta Spreafico ◽

Francesca Ieva

Keyword(s):

Recurrent Events ◽

Functional Modeling ◽

Time To Event

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Study design synopsis: Survive the race – Time‐to‐event analysis

Equine Veterinary Journal ◽

10.1111/evj.13466 ◽

2021 ◽

Author(s):

Johann Detilleux

Keyword(s):

Study Design ◽

Event Analysis ◽

Time To Event ◽

Race Time

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Sampling strategies to evaluate the prognostic value of a new biomarker on a time-to-event end-point

BMC Medical Research Methodology ◽

10.1186/s12874-021-01283-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Francesca Graziano ◽

Maria Grazia Valsecchi ◽

Paola Rebora

Keyword(s):

Survival Data ◽

Prognostic Value ◽

Cox Model ◽

Lymphoblastic Leukemia ◽

Fixed Ratio ◽

Case Control ◽

Time To Event ◽

Full Cohort ◽

Number Of Patients ◽

Nested Case Control

Abstract Background The availability of large epidemiological or clinical data storing biological samples allow to study the prognostic value of novel biomarkers, but efficient designs are needed to select a subsample on which to measure them, for parsimony and economical reasons. Two-phase stratified sampling is a flexible approach to perform such sub-sampling, but literature on stratification variables to be used in the sampling and power evaluation is lacking especially for survival data. Methods We compared the performance of different sampling designs to assess the prognostic value of a new biomarker on a time-to-event endpoint, applying a Cox model weighted by the inverse of the empirical inclusion probability. Results Our simulation results suggest that case-control stratified (or post stratified) by a surrogate variable of the marker can yield higher performances than simple random, probability proportional to size, and case-control sampling. In the presence of high censoring rate, results showed an advantage of nested case-control and counter-matching designs in term of design effect, although the use of a fixed ratio between cases and controls might be disadvantageous. On real data on childhood acute lymphoblastic leukemia, we found that optimal sampling using pilot data is greatly efficient. Conclusions Our study suggests that, in our sample, case-control stratified by surrogate and nested case-control yield estimates and power comparable to estimates obtained in the full cohort while strongly decreasing the number of patients required. We recommend to plan the sample size and using sampling designs for exploration of novel biomarker in clinical cohort data.

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