Sample size determination via learning-type curves

This paper is concerned with sample size determination methodology for prediction models. We propose combining the individual calculations via a learning-type curve. We suggest two distinct ways of doing so, a deterministic skeleton of a learning curve and a Gaussian process centred upon its deterministic counterpart. We employ several learning algorithms for modelling the primary endpoint and distinct measures for trial efficacy. We find that the performance may vary with the sample size, but borrowing information across sample size universally improves the performance of such calculations. The Gaussian process-based learning curve appears more robust and statistically efficient, while computational efficiency is comparable. We suggest that anchoring against historical evidence when extrapolating sample sizes should be adopted when such data are available. The methods are illustrated on binary and survival endpoints.Comment: 22 pages, 4 figure

Long-term functional outcomes of hearing and speech rehabilitation efficacy among paediatric cochlear implant recipients in Shandong, China.

PURPOSE: To evaluate the auditory performance and speech intelligibility of 100 children with bilateral profound sensorineural hearing loss up to 3 years after cochlear implantation. METHODS: A cohort study was established consisting of 100 children who received cochlear implantation at Shandong Ear Nose and Throat Hospital from 2012 to 2015. Children were examined after 1 month, 1, 2, and 3 years of implantation to assess auditory performance and speech intelligibility using standard tools. The paired Wilcoxon signed-rank test was used to assess whether the scores obtained at different testing points differed significantly. The Mann-Whitney test was utilized to examine the between-group differences (e.g., age at implantation). RESULTS: Three years after implantation, 60% out of 100 children reached the maximal category (7) of categorical auditory performance and 37% achieved the highest category (5) of speech intelligibility rating. Significant improvements were found over time in categorical auditory performance category and speech intelligibility rating (from month 1 to year 1, p < 0.001; from year 1 to year 2, p < 0.001; and from year 2 to year 3, p < 0.001). Larger improvements in auditory outcomes and speech intelligibility were observed in children with a younger age at implantation and those who received speech therapy. CONCLUSIONS: Cochlear implantation appears to make a significant, positive contribution to the development of communication skills of young congenital and prelingually deaf children in China. These improvements continue for up to 3 years after implantation. Positive outcomes appear to be associated with earlier age at implantation and receipt of speech therapy.Implications for rehabilitationBilateral sensorineural hearing loss.Bilateral sensorineural hearing loss in children can cause delay in speech development, poor language skills and potentially disorders in psychological behaviour and social isolation.Cochlear implantation (CI) is an effective strategy that helps children with bilateral sensorineural hearing loss gain the ability to hear and continue to develop language.This study shows that the auditory performance and speech intelligibility of deaf children who speak Mandarin continued to improve up to 3 years of implantation, when follow-up ceased

Trajectories of Haemoglobin and incident stroke risk: a longitudinal cohort study.

BACKGROUND: Studies have demonstrated that high or low haemoglobin increases the risk of stroke. Previous studies, however, performed only a limited number of haemoglobin measurements, while there are dynamic haemoglobin changes over the course of a lifetime. This longitudinal cohort study aimed to classify the long-term trajectory of haemoglobin and examine its association with stroke incidence. METHODS: The cohort consisted of 11,431 participants (6549 men) aged 20 to 50 years whose haemoglobin was repeatedly measured 3-9 times during 2004-2015. A latent class growth mixture model (LCGMM) was used to classify the long-term trajectory of haemoglobin concentrations, and hazard ratios (HRs) and 95% confidence intervals (95% CI) according to the Cox proportional hazard model were used to investigate the association of haemoglobin trajectory types with the risk of stroke. RESULTS: Three distinct trajectory types, high-stable (n = 5395), normal-stable (n = 5310), and decreasing (n = 726), were identified, with stroke incidence rates of 2.7, 1.9 and 3.2 per 1000 person-years, respectively. Compared to the normal-stable group, after adjusting for the baseline covariates, the decreasing group had a 2.94-fold (95% CI 1.22 to 7.06) increased risk of developing stroke. Strong evidence was observed in men, with an HR (95% CI) of 4.12 (1.50, 11.28), but not in women (HR = 1.66, 95% CI 0.34, 8.19). Individuals in the high-stable group had increased values of baseline covariates, but the adjusted HR (95% CI), at 1.23 (0.77, 1.97), was not significant for the study cohort or for men and women separately. CONCLUSIONS: This study revealed that a decreasing haemoglobin trajectory was associated with an increased risk of stroke in men. These findings suggest that long-term decreasing haemoglobin levels might increase the risk of stroke

A comprehensive evaluation on the associations between hearing and vision impairments and risk of all-cause and cause-specific dementia: results from cohort study, meta-analysis and Mendelian randomization study

Background: Epidemiological studies show inconsistent links between hearing/vision impairment and dementia risk. Using multisource data, we investigated how single or combined sensory impairments relate to risks of all-cause and specific types of dementia. Methods: We employed a triangulation approach combining three methodologies. We analyzed 90,893 UK Biobank (UKB) adults to explore single and joint effects of hearing and vision impairments on all-cause and Alzheimer’s disease (AD), vascular dementia (VD) and non-AD non-VD (NAVD). A meta-analysis of prospective studies involving 937,908 participants provided stronger evidence. Finally, we conducted Mendelian randomization (MR) analysis using genome-wide association studies from UKB (361,194 participants) and FinnGen (412,181 participants) to validate relationships between sensory impairments and dementia occurrence. Results: In the UKB cohort study, compared to participants with normal hearing, those in the mild and severe hearing impairment groups had progressively and significantly higher risk of all-cause dementia (mild: HR1.52, 95%CI 1.31–1.77; severe: HR1.80, 95%CI 1.36–2.38), AD (mild: HR1.63, 95%CI 1.30–2.04; severe: HR2.18, 95%CI 1.45–3.27), VD (mild: HR1.68, 95%CI 1.19–2.37; severe: HR1.47, 95%CI 1.22–1.78), and NAVD (mild: HR1.47, 95%CI 1.22–1.78; severe: HR1.98, 95%CI 1.43–2.75). Besides, vision impairment was associated with an increased risk of all-cause dementia (HR1.55, 95%CI 1.18–2.04) and NAVD (HR1.51, 95%CI 1.07–2.13). Furthermore, dual sensory impairment was associated with stepwise increased risks of all-cause and cause-specific dementia than single hearing or vision impairment. In the meta-analysis of 31 prospective cohort studies, risks of all-cause dementia and AD were elevated in participants with single hearing impairment (all-cause dementia: HR1.30, 95%CI 1.21–1.40; AD: HR1.30, 95%CI 1.21–1.40) and dual sensory impairment (all-cause dementia: HR1.63, 95%CI1.14–2.12; AD: HR 2.55, 95%CI 1.19–3.91), while single vision impairment only associated with higher risk of all-cause dementia (HR1.43, 95%CI 1.16–1.71) but not AD. Finally, the MR analysis revealed a significant association between hearing impairment and all-cause dementia (OR1.74, 95%CI 1.01–2.99), AD (OR1.56, 95%CI 1.09–2.23), and NAVD (OR1.14, 1.02–1.26), as well as vision impairment and NAVD (OR1.62, 95%CI 1.13–2.33). Conclusions: Our findings showed significant associations between hearing and vision impairments and increased risks of all-cause and cause-specific dementia. Standardized hearing and vision assessment and intervention should be emphasized in dementia prevention strategies

The PARTNER trial of neoadjuvant olaparib with chemotherapy in triple-negative breast cancer

PARTNER is a prospective, phase II–III, randomized controlled clinical trial that recruited patients with triple-negative breast cancer1, 2, who were germline BRCA1 and BRCA2 wild type3. Here we report the results of the trial. Patients (n = 559) were randomized on a 1:1 basis to receive neoadjuvant carboplatin–paclitaxel with or without 150 mg olaparib twice daily, on days 3 to 14, of each of four cycles (gap schedule olaparib, research arm) followed by three cycles of anthracycline-based chemotherapy before surgery. The primary end point was pathologic complete response (pCR)4, and secondary end points included event-free survival (EFS) and overall survival (OS)5. pCR was achieved in 51% of patients in the research arm and 52% in the control arm (P = 0.753). Estimated EFS at 36 months in the research and control arms was 80% and 79% (log-rank P > 0.9), respectively; OS was 90% and 87.2% (log-rank P = 0.8), respectively. In patients with pCR, estimated EFS at 36 months was 90%, and in those with non-pCR it was 70% (log-rank P < 0.001), and OS was 96% and 83% (log-rank P < 0.001), respectively. Neoadjuvant olaparib did not improve pCR rates, EFS or OS when added to carboplatin–paclitaxel and anthracycline-based chemotherapy in patients with triple-negative breast cancer who were germline BRCA1 and BRCA2 wild type. ClinicalTrials.gov ID: NCT03150576

Sample size determination for prediction models via learning‐type curves

Publication status: PublishedThis article is concerned with sample size determination methodology for prediction models. We propose to combine the individual calculations via learning‐type curves. We suggest two distinct ways of doing so, a deterministic skeleton of a learning curve and a Gaussian process centered upon its deterministic counterpart. We employ several learning algorithms for modeling the primary endpoint and distinct measures for trial efficacy. We find that the performance may vary with the sample size, but borrowing information across sample size universally improves the performance of such calculations. The Gaussian process‐based learning curve appears more robust and statistically efficient, while computational efficiency is comparable. We suggest that anchoring against historical evidence when extrapolating sample sizes should be adopted when such data are available. The methods are illustrated on binary and survival endpoints.</jats:p

Trajectories of Lipids Profile and Incident Cardiovascular Disease Risk: A Longitudinal Cohort Study

Background The association between low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, and triglycerides with cardiovascular disease ( CVD ) has been well studied. No previous studies considered trajectory of these lipids jointly. This study aims to characterize longitudinal trajectories of lipid profile jointly and examine its impact on incident CVD . Methods and Results A total of 9726 participants (6102 men), aged from 20 to 58 years who had lipids repeatedly measured 3 to 9 times, were included in the study. Three distinct trajectories were identified using the multivariate latent class growth mixture model: inverse U‐shape (18.72%; n=1821), progressing (66.03%; n=6422), and U‐shape (15.25%; n=1483). Compared with the U‐shape class, the adjusted hazard ratio and 95% CI were 1.33 (1.05–1.68) and 1.49 (1.14–1.95) for the progressing and inverse U‐shape class, respectively. The area under the curve was calculated using the integral of the model parameters. In the adjusted model, total and incremental area under the curve of lipid profile were significantly associated with CVD risk. Furthermore, the model‐estimated levels and linear slopes of lipids were calculated at each age point according to the latent class growth mixture model model parameters and their first derivatives, respectively. After adjusting for covariates, standardized odds ratio of slope increases gradually from 1.11 (1.02, 1.21) to 1.21 (1.12, 1.31) at 20 to 40 years and then decreased to 1.02 (0.94, 1.11) until 60 years. Conclusions These results indicate that the lipids profile trajectory has a significant impact on CVD risk. Age between 20 and 42 years is a crucial period for incident CVD , which has implications for early lipids intervention. </jats:sec