To explore the optimal cutoff score for initial detection of Alzheimer’s Disease (AD) through the Chinese version of Mini-Mental State Examination (CMMSE) in rural areas in China, we conducted a cross-sectional study within the Linxian General Population Nutritional Follow-up study. 16,488 eligible cohort members participated in the survey and 881 completed the CMMSE. Among 881 participants, the median age (Interquartile range) was 69.00 (10.00), 634 (71.92%) were female, 657 (74.57%) were illiterate, 35 (3.97%) had 6 years of education or higher, and 295 (33.48%) were diagnosed with AD. By reducing the CMMSE criteria for illiterate to 16 points, primary school to 19 points, and middle school or higher to 23 points, the efficiency of Chinese version of Mini-Mental State Examination can be significantly improved for initial detection of AD in rural areas in China, especially in those nutrition deficient areas.

To investigate the issues of the NNT based on the absolute risk reduction (ARR), namely NNT_ARR; and to propose an alternative definition and an estimation procedure based on the restricted mean survival time (RMST), namely NNT_RMST, for RCTs. Three recent clinical trials with survival endpoints, representing different scenarios, were selected to compare the performance of the NNT_ARR and NNT_RMST. For each trial, both versions of NNT were estimated using the reconstructed individual-level data, and the average life gain (ALG) was derived to show the differences between the NNT_ARR and NNT_RMST. Four hypothetical scenarios were constructed to further explore the advantages and disadvantages of each definition of the NNT for survival endpoints. For the illustrative trial examples, the NNT_ARR failed to capture the profile of the treatment effect over time as it is calculated at a specific time point. Sometimes it may even result in misinterpretations of the treatment benefit. In particular, when either the observed event rates are low, the two survival curves cross, or a mixture of survival patterns exist. In contrast, the NNT_RMST based on the average survival (or event-free) time can quantify the treatment effect more accurately and its interpretation is more intuitive and clinically meaningful. The NNT_RMST can be used as an alternative measure for quantifying treatment effect in RCTs, especially so in the case of the ALG, which helps practitioners to better understand the magnitude of the benefit conferred by treatment.

Little is known about the long-term effectiveness of risk-based treat-to-target cholesterol-lowering interventions on cardiovascular risk. Here, we show the emulated effectiveness of guideline-recommended low-density and non-high-density lipoprotein cholesterol-lowering interventions using the absolute risk reduction (ARR) and the restricted mean event-free time-based number needed to treat (NNT). With 5,375 participants, the 29-year risks for cardiovascular disease (CVD), all-cause mortality, and atherosclerotic CVD were 18.6%, 25.6%, and 17.7%, respectively. Long-term treat-to-target interventions showed significant reductions in CVD (ARR −2.3%, 95%CI −3.4% to −0.8%; NNT 115), all-cause mortality (−3.0%, −4.3% to −1.8%; 95), and atherosclerotic CVD (−2.6%, −3.5% to −1.2%; 104). Such effects appear more pronounced in women, smokers, and those with body mass index < 24 kg/m² or higher adherence rates.

The STEP (Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients) trial showed that intensive systolic blood pressure (SBP) control reduced cardiovascular risk. Study investigators conducted an extended follow-up of the STEP trial to determine the longer-term effects of intensive blood pressure (BP) control. In this randomized controlled trial, 8,511 patients with hypertension were randomly assigned to the intensive treatment group, with an SBP target of 110 mm Hg to <130 mm Hg, or the standard treatment group, with an SBP target of 130 mm Hg to <150 mm Hg. After the original trial ended, all surviving patients, either in the standard group or the intensive treatment group previously, received intensive treatment in the extended period, referred to as the delayed intensive treatment group or the sustained intensive treatment group. The primary outcome was a composite of stroke, acute coronary syndrome, acute decompensated heart failure, coronary revascularization, atrial fibrillation, or death resulting from cardiovascular causes. The Fine-Gray subdistribution hazard model was used to estimate the HR between the 2 groups, and g-formula methods were initiated to compare overall primary outcome risks with intensive treatment initiated from randomization and initiated every year after randomization. After a median follow-up of 6.11 years, the mean SBP was 127.9 mm Hg in the sustained intensive treatment group and 129.5 mm Hg in the delayed intensive treatment group. The incidence rate of primary outcome was 1.12% per year in the sustained intensive treatment group, compared with 1.33% per year in the delayed intensive treatment group (HR: 0.82; 95% CI: 0.71-0.96). No difference in safety event rates between the 2 groups was observed except for hypotension, which occurred more frequently in the sustained intensive treatment group. Furthermore, analyses using the parametric g-formula showed that compared with the standard BP treatment, intensive treatment initiating from randomization (0 month) yielded the greatest benefit (relative risk [RR]: 0.83; 95% CI: 0.70-0.96), with an attenuated cardiovascular benefit for later initiation from 12 months (RR: 0.88; 95% CI: 0.76-0.99). Our results suggested that sustained intensive BP control could benefit patients with hypertension compared with delayed intensive treatment in the longer-term follow-up. The earlier intensive treatment is initiated after the hypertension diagnosis, the greater the cardiovascular benefits will be. (Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients [STEP]; NCT03015311).

Patients’ heterogeneity poses a fundamental problem in the rapidly developing field of precision medicine. Based on a prespecified cutoff, biomarker-based designs provide a flexible approach to selecting a subset of biomarker-positive patients who are most likely to benefit from the new therapeutics. However, a natural question is how to determine the biomarker cutoff that distinguishes biomarker-positive patients from the negatives, and then evaluate the efficacy of the new therapeutics in one trial. We propose a phase II basket biomarker cutoff (BBC) design where a biomarker for identifying the sensitive patients is measured on a continuous scale. The proposed BBC design incorporates the biomarker cutoff identification procedure into a basket trial via Bayesian hierarchical modeling. We verify its feasibility and practicability via real trial examples, extensive simulation studies, and sensitivity analyses. The simulation studies show that the BBC design can select biomarker-positive patients accurately and may exhibit competitive improvement in regards to the overall type I error, power, and average sample number.

Late-onset (LO) toxicities often arise in the new era of phase I oncology dose-finding trials with targeted agents or immunotherapies. The current LO toxicities modelling is often formulated in a weighted likelihood framework, where the time-to-event continual reassessment method (TITE-CRM) is commonly used. The TITE-CRM uses the patient exposure time as a weight for the censored observation, while there is large uncertainty on which weight function to be used. As an alternative, the fractional scheme formulates an efficient and robust paradigm to address LO toxicity issues in dose finding. We review the fractional continual reassessment method (fCRM) and compare its operating characteristics with those of the TITE-CRM as well as other competitive designs via extensive simulation studies based on both the fixed and randomly generated scenarios. The fCRM is shown to possess desirable operating characteristics in identifying the maximum tolerated dose (MTD) and deliver competitive performances in comparison with other designs. It provides an alternative efficient and robust paradigm for interpreting and addressing LO toxicities in the new era of phase I dose-finding trials in precision oncology. A real trial example is used to illustrate the practical use of the fCRM design.