Search

The major cause of death after allogeneic Hematopoietic Stem Cell Transplantation (HSCT) for acute myeloid leukemia (AML) is disease relapse. We investigated the expression of Inhibitory Receptors (IR; PD-1/CTLA-4/TIM-3/LAG-3/2B4/KLRG1/GITR) on T cells infiltrating the bone marrow (BM) of 32 AML patients relapsing (median 251 days) or maintaining complete remission (CR; median 1 year) after HSCT. A higher proportion of early-differentiated Memory Stem (T SCM ) and Central Memory BM-T cells express multiple IR in relapsing patients than in CR patients. Exhausted BM-T cells at relapse display a restricted TCR repertoire, impaired effector functions and leukemia-reactive specificities. In 57 patients, early detection of severely exhausted (PD-1 + Eomes + T-bet − ) BM-T SCM predicts relapse. Accordingly, leukemia-specific T cells in patients prone to relapse display exhaustion markers, absent in patients maintaining long-term CR. These results highlight a wide, though reversible, immunological dysfunction in the BM of AML patients relapsing after HSCT and suggest new therapeutic opportunities for the disease.

BACKGROUND: The D-Health Trial aims to determine whether monthly high-dose vitamin D supplementation can reduce the mortality rate and prevent cancer. We did not have adequate statistical power for subgroup analyses, so could not justify the high cost of collecting blood samples at baseline. To enable future exploratory analyses stratified by baseline vitamin D status, we developed models to predict baseline serum 25 hydroxy vitamin D [25(OH)D] concentration. METHODS: We used data and serum 25(OH)D concentrations from participants who gave a blood sample during the trial for compliance monitoring and were randomised to placebo. Data were partitioned into training (80%) and validation (20%) datasets. Deseasonalised serum 25(OH)D concentrations were dichotomised using cut-points of 50, 60 and 75 nmol/L. We fitted boosted regression tree models, based on 13 predictors, and evaluated model performance using the validation data. RESULTS: The training and validation datasets had 1788 (10.5% <50 nmol/L, 23.1% <60 nmol, 48.8 <75 nmol/L) and 447 (11.9% <50 nmol/L, 25.7% <60 nmol/L, and 49.2% <75 nmol/L) samples, respectively. Ambient UV radiation and total intake of vitamin D were the strongest predictors of 'low' serum 25(OH)D concentration. The area under the receiver operating characteristic curves were 0.71, 0.70, and 0.66 for cut-points of <50, <60 and <75 nmol/L respectively. CONCLUSIONS: We exploited compliance monitoring data to develop models to predict serum 25(OH)D concentration for D-Health participants at baseline. This approach may prove useful in other trial settings where there is an obstacle to exhaustive data collection.

BACKGROUND: Falls cause considerable morbidity and mortality in older people. It is unclear how vitamin D supplementation affects falls risk, particularly when taken at high doses. We sought to determine whether monthly high-dose vitamin D supplementation reduces risk and incidence of falls. METHODS: We used data from the randomized, double-blind, placebo-controlled D-Health Trial conducted in Australia. Between February 2014 and May 2015, 21 315 participants aged 60-84 years were randomized (1:1) to monthly doses of either 60 000 IU of colecalciferol or placebo for a maximum of 5 years. People who reported a history of osteomalacia, sarcoidosis, hyperparathyroidism, hypercalcaemia or kidney stones or who were taking >500 IU/day supplementary vitamin D were ineligible. Each year, we collected blood samples from ~450 randomly sampled participants from each trial arm and measured 25-hydroxyvitamin D [25(OH)D]. Falls, a prespecified tertiary outcome, were ascertained using annual surveys and, for a subset of participants, 3-month falls diaries. The primary outcome for this analysis was any fall in the month before completing an annual survey. As part of our process to maintain blinding, we used random samples of participants (surveys, n = 16 000; diaries, n = 2400), with equal numbers per group. Participants with no outcome data were excluded. Following an intention-to-treat approach, we analysed outcomes using logistic, ordinal and negative binomial regression. Registration: Australian New Zealand Clinical Trials Registry (ACTRN12613000743763); registered 4 July 2013. RESULTS: Mean treatment duration was 4.3 years (standard deviation [SD] = 1.4 years). Mean serum 25(OH)D concentrations during the trial were 114.8 (SD 30.3) nmol/L and 77.5 (SD 25.2) nmol/L in the vitamin D and placebo groups, respectively. Survey and diary analytic sets included 15 416 and 2200 participants, respectively; approximately half were randomized to vitamin D (surveys: 50.1%; diaries: 50.4%).

BACKGROUND: Many observational studies have reported an association between vitamin D and non-skeletal health outcomes. The D-Health Trial was launched to determine if supplementing the older population with high monthly doses of Vitamin D can prevent cancer and premature mortality. The intervention is ongoing but here we provide a detailed statistical analysis plan for the primary and secondary outcomes of the D-Health Trial. METHODS/DESIGN: The D-Health Trial is a double-blind, randomized, placebo-controlled trial. Between February 2014 and May 2015, 21,315 people were randomized in a 1:1 ratio to receive monthly doses of either 60,000 IU of cholecalciferol (vitamin D3) or placebo for five years. The primary outcome is all-cause mortality and the secondary outcomes are total cancer incidence and colorectal cancer incidence. These will be ascertained via linkage to death and cancer registries. The primary analysis for each outcome will follow an intention-to-treat approach; we will use flexible parametric survival models to investigate the association between supplementation and time to an event. We describe in detail sophisticated secondary analyses that consider non-compliance and contamination due to off-study supplementation. CONCLUSIONS: Publication of this statistical analysis plan in advance of the intervention's completion, and adherence to it, will avoid data-driven analyses of the primary and secondary outcomes and ensure robust reporting of outcomes. CLINICAL TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry: ACTRN12613000743763. Registered on 4 July 2013.