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.

This 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.

The MITRE trial protocol: a study to evaluate the microbiome as a biomarker of efficacy and toxicity in cancer patients receiving immune checkpoint inhibitor therapy.

BACKGROUND: The gut microbiome is implicated as a marker of response to immune checkpoint inhibitors (ICI) based on preclinical mouse models and preliminary observations in limited patient series. Furthermore, early studies suggest faecal microbial transfer may have therapeutic potential, converting ICI non-responders into responders. So far, identification of specific responsible bacterial taxa has been inconsistent, which limits future application. The MITRE study will explore and validate a microbiome signature in a larger scale prospective study across several different cancer types. METHODS: Melanoma, renal cancer and non-small cell lung cancer patients who are planned to receive standard immune checkpoint inhibitors are being recruited to the MITRE study. Longitudinal stool samples are collected prior to treatment, then at 6 weeks, 3, 6 and 12 months during treatment, or at disease progression/recurrence (whichever is sooner), as well as after a severe (≥grade 3 CTCAE v5.0) immune-related adverse event. Additionally, whole blood, plasma, buffy coat, RNA and peripheral blood mononuclear cells (PBMCs) is collected at similar time points and will be used for exploratory analyses. Archival tumour tissue, tumour biopsies at progression/relapse, as well as any biopsies from body organs collected after a severe toxicity are collected. The primary outcome measure is the ability of the microbiome signature to predict 1 year progression-free survival (PFS) in patients with advanced disease. Secondary outcomes include microbiome correlations with toxicity and other efficacy end-points. Biosamples will be used to explore immunological and genomic correlates. A sub-study will evaluate both COVID-19 antigen and antibody associations with the microbiome. DISCUSSION: There is an urgent need to identify biomarkers that are predictive of treatment response, resistance and toxicity to immunotherapy. The data generated from this study will both help inform patient selection for these drugs and provide information that may allow therapeutic manipulation of the microbiome to improve future patient outcomes. TRIAL REGISTRATION: NCT04107168 , ClinicalTrials.gov, registered 09/27/2019. Protocol V3.2 (16/04/2021).

Lethal COG6-CDG in neonatal patient with arachnodactyly, joint contractures, and skin manifestations: Founder mutation in the Southeastern European population?

Herein, we report a lethal case of the ultra-rare COG6-congenital disorder of glycosylation (CDG) presenting with skin manifestations (scaling and erosions) and joint contractures in a neonate of Albanian origin. The patient was homozygous for a COG6 pathogenic variant, previously reported in another three individuals of Greek, Bulgarian and Turkish descent. The presence of a founder mutation in the geographical area is possible. The index case emphasizes the need to consider CDGs in neonatal patients with skin manifestations and joint contractures, particularly patients of Southeastern European or West Asian origin.

Bayesian epidemic models for spatially aggregated count data.

Epidemic data often possess certain characteristics, such as the presence of many zeros, the spatial nature of the disease spread mechanism, environmental noise, serial correlation and dependence on time-varying factors. This paper addresses these issues via suitable Bayesian modelling. In doing so, we utilize a general class of stochastic regression models appropriate for spatio-temporal count data with an excess number of zeros. The developed regression framework does incorporate serial correlation and time-varying covariates through an Ornstein-Uhlenbeck process formulation. In addition, we explore the effect of different priors, including default options and variations of mixtures of g-priors. The effect of different distance kernels for the epidemic model component is investigated. We proceed by developing branching process-based methods for testing scenarios for disease control, thus linking traditional epidemiological models with stochastic epidemic processes, useful in policy-focused decision making. The approach is illustrated with an application to a sheep pox dataset from the Evros region, Greece. Copyright © 2017 John Wiley & Sons, Ltd.

Assessing optimal target populations for influenza vaccination programmes: an evidence synthesis and modelling study.

BACKGROUND: Influenza vaccine policies that maximise health benefit through efficient use of limited resources are needed. Generally, influenza vaccination programmes have targeted individuals 65 y and over and those at risk, according to World Health Organization recommendations. We developed methods to synthesise the multiplicity of surveillance datasets in order to evaluate how changing target populations in the seasonal vaccination programme would affect infection rate and mortality. METHODS AND FINDINGS: Using a contemporary evidence-synthesis approach, we use virological, clinical, epidemiological, and behavioural data to develop an age- and risk-stratified transmission model that reproduces the strain-specific behaviour of influenza over 14 seasons in England and Wales, having accounted for the vaccination uptake over this period. We estimate the reduction in infections and deaths achieved by the historical programme compared with no vaccination, and the reduction had different policies been in place over the period. We find that the current programme has averted 0.39 (95% credible interval 0.34-0.45) infections per dose of vaccine and 1.74 (1.16-3.02) deaths per 1,000 doses. Targeting transmitters by extending the current programme to 5-16-y-old children would increase the efficiency of the total programme, resulting in an overall reduction of 0.70 (0.52-0.81) infections per dose and 1.95 (1.28-3.39) deaths per 1,000 doses. In comparison, choosing the next group most at risk (50-64-y-olds) would prevent only 0.43 (0.35-0.52) infections per dose and 1.77 (1.15-3.14) deaths per 1,000 doses. CONCLUSIONS: This study proposes a framework to integrate influenza surveillance data into transmission models. Application to data from England and Wales confirms the role of children as key infection spreaders. The most efficient use of vaccine to reduce overall influenza morbidity and mortality is thus to target children in addition to older adults. Please see later in the article for the Editors' Summary.

Surgical outcomes of gallbladder cancer: the OMEGA retrospective, multicentre, international cohort study.

Background: Gallbladder cancer (GBC) is rare but aggressive. The extent of surgical intervention for different GBC stages is non-uniform, ranging from cholecystectomy alone to extended resections including major hepatectomy, resection of adjacent organs and routine extrahepatic bile duct resection (EBDR). Robust evidence here is lacking, however, and survival benefit poorly defined. This study assesses factors associated with recurrence-free survival (RFS), overall survival (OS) and morbidity and mortality following GBC surgery in high income countries (HIC) and low and middle income countries (LMIC). Methods: The multicentre, retrospective Operative Management of Gallbladder Cancer (OMEGA) cohort study included all patients who underwent GBC resection across 133 centres between 1st January 2010 and 31st December 2020. Regression analyses assessed factors associated with OS, RFS and morbidity. Findings: On multivariable analysis of all 3676 patients, wedge resection and segment IVb/V resection failed to improve RFS (HR 1.04 [0.84-1.29], p = 0.711 and HR 1.18 [0.95-1.46], p = 0.13 respectively) or OS (HR 0.96 [0.79-1.17], p = 0.67 and HR 1.48 [1.16-1.88], p = 0.49 respectively), while major hepatectomy was associated with worse RFS (HR 1.33 [1.02-1.74], p = 0.037) and OS (HR 1.26 [1.03-1.53], p = 0.022). Furthermore, EBDR (OR 2.86 [2.3-3.52], p < 0.0010), resection of additional organs (OR 2.22 [1.62-3.02], p < 0.0010) and major hepatectomy (OR 3.81 [2.55-5.73], p < 0.0010) were all associated with increased morbidity and mortality. Compared to LMIC, patients in HIC were associated with poorer RFS (HR 1.18 [1.02-1.37], p = 0.031) but not OS (HR 1.05 [0.91-1.22], p = 0.48). Adjuvant and neoadjuvant treatments were infrequently used. Interpretation: In this large, multicentre analysis of GBC surgical outcomes, liver resection was not conclusively associated with improved survival, and extended resections were associated with greater morbidity and mortality without oncological benefit. Aggressive upfront resections do not benefit higher stage GBC, and international collaborations are needed to develop evidence-based neoadjuvant and adjuvant treatment strategies to minimise surgical morbidity and prioritise prognostic benefit. Funding: Cambridge Hepatopancreatobiliary Department Research Fund.

Evaluating the effects of second-dose vaccine-delay policies in European countries: A simulation study based on data from Greece.

The results of a simulation-based evaluation of several policies for vaccine rollout are reported, particularly focusing on the effects of delaying the second dose of two-dose vaccines. In the presence of limited vaccine supply, the specific policy choice is a pressing issue for several countries worldwide, and the adopted course of action will affect the extension or easing of non-pharmaceutical interventions in the next months. We employ a suitably generalised, age-structure, stochastic SEIR (Susceptible → Exposed → Infectious → Removed) epidemic model that can accommodate quantitative descriptions of the major effects resulting from distinct vaccination strategies. The different rates of social contacts among distinct age-groups (as well as some other model parameters) are informed by a recent survey conducted in Greece, but the conclusions are much more widely applicable. The results are summarised and evaluated in terms of the total number of deaths and infections as well as life years lost. The optimal strategy is found to be one based on fully vaccinating the elderly/at risk as quickly as possible, while extending the time-interval between the two vaccine doses to 12 weeks for all individuals below 75 years old, in agreement with epidemic theory which suggests targeting a combination of susceptibility and infectivity. This policy, which is similar to the approaches adopted in the UK and in Canada, is found to be effective in reducing deaths and life years lost in the period while vaccination is still being carried out.

A quantitative analysis of the spatial and temporal evolution patterns of the bluetongue virus outbreak in the island of Lesvos, Greece, in 2014.

Bluetongue virus (BTV) causes an infectious disease called bluetongue, a vector-borne viral disease of ruminants, which has major implications and causes severe economic damage due to its effect on livestock. These economic costs are mostly ascribed to the trade restrictions imposed during the epidemic period. In August 2014, an epidemic of bluetongue occurred in the island of Lesvos, Greece. The epidemic was severe and evolved over time, lasting until December 2014. The total cases of infected farms were 490, including a total number of 136,368 small ruminants. In this paper, we describe a bluetongue virus serotype 4 (BTV-4) epidemic and utilize Bayesian epidemic models to capture the spatio-temporal spread of the disease. Our study provides important insights into the drivers of BTV transmission and has implications for designing control strategies. The results showed strong spatial autocorrelations, with BTV being more likely to spread between farms located nearby. The spatial modelling results proposed a certain spatial radius (~12 km) around the onset of a similar epidemic for imposing restrictions on animal movement, which can be sufficient for the control of the disease and limit economic damage.

Contemporary statistical inference for infectious disease models using Stan.

This paper is concerned with the application of recent statistical advances to inference of infectious disease dynamics. We describe the fitting of a class of epidemic models using Hamiltonian Monte Carlo and variational inference as implemented in the freely available Stan software. We apply the two methods to real data from outbreaks as well as routinely collected observations. Our results suggest that both inference methods are computationally feasible in this context, and show a trade-off between statistical efficiency versus computational speed. The latter appears particularly relevant for real-time applications.

A spatial predictive model for malaria resurgence in central Greece integrating entomological, environmental and social data.

Malaria constitutes an important cause of human mortality. After 2009 Greece experienced a resurgence of malaria. Here, we develop a model-based framework that integrates entomological, geographical, social and environmental evidence in order to guide the mosquito control efforts and apply this framework to data from an entomological survey study conducted in Central Greece. Our results indicate that malaria transmission risk in Greece is potentially substantial. In addition, specific districts such as seaside, lakeside and rice field regions appear to represent potential malaria hotspots in Central Greece. We found that appropriate maps depicting the basic reproduction number, R0, are useful tools for informing policy makers on the risk of malaria resurgence and can serve as a guide to inform recommendations regarding control measures.

Evaluating the frequency of asymptomatic Ebola virus infection.

The potential for asymptomatic infection from Ebola viruses has long been questioned. Knowing the proportion of infections that are asymptomatic substantially changes the predictions made by mathematical models and alters the corresponding decisions based upon these models. To assess the degree of asymptomatic infection occurring during an Ebola virus disease (EVD) outbreak, we carried out a serological survey in the Djera district of the Equateur province of the Democratic Republic of the Congo affected by an Ebola outbreak in 2014. We sampled all asymptomatic residents (n = 182) of 48 households where at least one case of EVD was detected. To control for potential background seroprevalence of Ebola antibodies in the population, we also sampled 188 individuals from 92 households in an unaffected area with a similar demographic background. We tested the sera collected for anti-Ebola IgG and IgM antibodies at four different dilutions. We then developed a mixture model to estimate the likely number of asymptomatic patients who developed IgM and IgG responses to Ebola antigens in both groups. While we detected an association between medium to high titres and age, we did not detect any evidence of increased asymptomatic infection in the individuals who resided in the same household as cases.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

Survival extrapolation using the poly-Weibull model.

Recent studies of (cost-) effectiveness in cardiothoracic transplantation have required estimation of mean survival over the lifetime of the recipients. In order to calculate mean survival, the complete survivor curve is required but is often not fully observed, so that survival extrapolation is necessary. After transplantation, the hazard function is bathtub-shaped, reflecting latent competing risks which operate additively in overlapping time periods. The poly-Weibull distribution is a flexible parametric model that may be used to extrapolate survival and has a natural competing risks interpretation. In addition, treatment effects and subgroups can be modelled separately for each component of risk. We describe the model and develop inference procedures using freely available software. The methods are applied to two problems from cardiothoracic transplantation.

Influence of organic selenium supplementation on the accumulation of toxic and essential trace elements involved in the antioxidant system of chicken.

The aim of the study was to investigate the interactions between selenium (Se) and various trace elements, both toxic and essential, involved in the antioxidant system. A total of 128 day-old chicks (Gallus gallus, broilers) were used to investigate the effect of Se yeast supplementation on the accumulation of cadmium (Cd), copper (Cu) iron (Fe) and zinc (Zn). There were four replicates of four dietary treatments: T1 (basal diet with no added Se, analyzed to contain 0.21 mg kg(-1)), T2 (T1 with 0.15 mg kg(-1) Se added), T3 (T1 with 0.3 mg kg(-1) Se) and T4 (T1 with 3.0 mg kg(-1) Se). At week 4 and 6, two chickens per replicate pen were sacrificed for whole blood, breast muscle and liver sampling. Samples were analyzed by ICP-MS. Supplementation with Se-yeast, not only increased Se concentration but also reduced Cd concentration in the tissues. Selenium was negatively correlated with Cd and positively correlated with Zn, Cu and Fe. Cadmium was negatively correlated with Zn and Cu. Zinc was positively correlated with Cu. Iron was negatively correlated with Cu and uncorrelated with Zn and Cd. The balance between Se, Cu, Fe and Zn is important for proper antioxidant defense since they are an integral part of various antioxidant enzymes.

Assessing the benefit of accepting a single lung offer now compared with waiting for a subsequent double lung offer.

BACKGROUND: Comparisons of survival after single lung transplant (SLT) and bilateral lung transplant (BLT) are useful in making policy decisions, but a more relevant comparison for an individual patient is between accepting a single lung when offered and remaining on the waiting list with the potential to subsequently receive a suitable pair of lungs. METHODS: U.K. data from a cohort of 1211 adult, first lung transplant candidates diagnosed with pulmonary fibrosis (PF) or chronic obstructive pulmonary disease (COPD), listed July 1995 to July 2006 and followed up till December 2007, were analyzed. A sequentially stratified proportional hazards model was used to assess mortality after SLT relative to continued waiting for BLT. RESULTS: For patients with PF, SLT was associated with a significant reduction in hazard relative to waiting for BLT (hazard ratio 0.81, 95% confidence interval 0.68-0.97, P=0.021), particularly for older patients with body mass index less than 20 and forced expired volume in 1 sec is less than 1 L. In contrast, our results gave no support for accepting SLT rather than waiting for BLT for patients with COPD (hazard ratio 1.08, 95% confidence interval 0.92-1.29, P=0.35). CONCLUSION: The high pretransplant risk of death for patients with PF, particularly older patients with low body mass index and poor lung function, suggests that they would benefit from taking an SLT if offered. However, there is no benefit of accepting SLT rather than waiting for BLT for patients with COPD; this reflects the low relative hazard in the absence of transplant for these patients.

Microsimulation and clinical outcomes analysis support a lower age threshold for use of biological valves.

OBJECTIVE: To characterise contemporary results of aortic valve replacement in relation to type of prosthesis and subsequent competing hazards. METHODS: 5470 procedures in 5433 consecutive patients with aortic valve replacement ± coronary artery bypass grafting (CABG) were studied. Microsimulation of survival and valve-related outcomes was performed based on meta-analysis and patient data inputs, with separate models for age, gender and CABG. Survival was validated against the UK Heart Valve Registry. RESULTS: Patient survival at 1, 5 and 10 years was 90%, 78% and 57%, respectively. The crossover points at which bioprostheses and mechanical prostheses conferred similar life expectancy (LE) was 59 years for men and women (no significant difference between prosthesis types between the ages of 56 and 69 for men, and 58 an 63 for women). The improvement in event-free LE for mechanical valves was greater at younger ages with a crossover point of 66 years for men and 67 years for women. Long-term survival was independently influenced by age, male gender and concomitant CABG, but not by type of prosthesis. In bioprostheses the most common long-term occurrence was structural deterioration. For men aged 55, 65 and 75 at initial operation it had a lifetime incidence of 50%, 30% and 13%, respectively. The simulation output showed excellent agreement with registry data. CONCLUSION: Bioprostheses can be implanted selectively in patients as young as 56 without significant adverse effects on life expectancy, although event-free life expectancy remains significantly lower with bioprostheses up to age of implant of 63.

Life-years gained by reducing donor heart ischemic times.

BACKGROUND: Transplantation is limited by the number of available donor organs. Donor organ maintenance systems are a recent technological advance. These systems may increase the number of donor organs that can be used and improve outcomes by decreasing donor organ ischemic time (IT). The purpose of this study was to determine the potential life-years gained if IT in the United Kingdom were decreased for cardiac transplantation. METHODS: Proportional hazards regression and extrapolation of survival rates beyond 20 years posttransplantation were used to estimate the effect of decreasing total IT on survival and the life-years gained over the lifetime of UK heart transplantation patients. RESULTS: Median survival posttransplantation was 10.4 years (95% CI 9.9 to 10.9). For each additional hour of donor organ IT, patients had a 25% increased risk of death after heart transplantation in the first year after transplant, with a 5% increase thereafter (P<0.001). On average, a recipient surviving 10 years posttransplantation could potentially gain 0.4 (95% CI 0.1 to 0.7) life-years if IT was reduced to 1 hr. The longer the IT, the greater the potential life-years to gain; for example, a recipient of an organ that would have had an IT of 6 hr without the use of an organ maintenance system might expect to gain 2.9 life-years (95% CI -0.6 to 6.4) if IT was reduced to 1 hr. CONCLUSIONS: Use of cardiac donor organ maintenance systems has the potential to increase posttransplantation survival.

Cost-effectiveness of ventricular assist device use in the United Kingdom: results from the evaluation of ventricular assist device programme in the UK (EVAD-UK).

BACKGROUND: The UK Department of Health funds ventricular assist device (VAD) implantation as a bridge to transplantation (BTT) at three centers. The cost-effectiveness of this program has not been established. METHODS: All 70 VAD implants for BTT and a consecutive cohort of 71 inotrope-dependent transplant candidates, between April 2002 and December 2004, were prospectively monitored for survival, transplantation, quality of life and resource use. Costs and quality-adjusted life-years were estimated for these groups, and for a hypothetical scenario in which VAD patients would die within 30 days in the absence of the program. RESULTS: Mean quality-adjusted life-years for a VAD patient was 3.27 at a lifetime cost of 173,841 pounds (316,078 US dollars). The majority of the cost was attributable to the VAD implant (63,830 pounds, 116,056 US dollars) and the initial hospital stay in the ITU and ward (14,500 pounds, 26,364 US dollars). Inotrope-dependent transplant candidates had mean quality-adjusted life-years of 4.99 at a lifetime cost of 130,905 pounds (238,011 US dollars). The worst clinical scenario resulted in a lifetime cost of 14,400 pounds (26,182 US dollars), based on 1 month in the ICU (mean 15 days). These figures were robust to a range of plausible assumptions. CONCLUSIONS: A lifetime model based on current UK practice demonstrates that BTT VAD patients had significant quality-adjusted life-years, but treatment was expensive when compared with the worst clinical scenario. If device technology improves, costs are reduced, or referral practice changes, results should be re-assessed.