Time-Dependent ROC Curve Analysis for Assessing the Capability of Radiation-Induced CD8 T-Lymphocyte Apoptosis to Predict Late Toxicities after Adjuvant Radiotherapy of Breast Cancer Patients.

Late fibrosis can occur in breast cancer patients treated with curative-intent radiotherapy. Predicting this toxicity is of clinical interest in order to adapt the irradiation dose delivered. Radiation-induced CD8 T-lymphocyte apoptosis (RILA) had been proven to be associated with less grade ≥2 late radiation-induced toxicities in patients with miscellaneous cancers. Tobacco smoking status and adjuvant hormonotherapy were also identified as potential factors related to late-breast-fibrosis-free survival. This article evaluates the predictive performance of the RILA using a ROC curve analysis that takes into account the dynamic nature of fibrosis occurrence. This time-dependent ROC curve approach is also applied to evaluate the ability of the RILA combined with the other previously identified factors. Our analysis includes a Monte Carlo cross-validation procedure and the calculation of an expected cost of misclassification, which provides more importance to patients who have no risk of late fibrosis in order to be able to treat them with the maximal irradiation dose. Performance evaluation was assessed at 12, 24, 36 and 50 months. At 36 months, our results were comparable to those obtained in a previous study, thus underlying the predictive power of the RILA. Based on specificity and cost, RILA alone seemed to be the most performant, while its association with the other factors had better negative predictive value results.

Flexible modeling of longitudinal health-related quality of life data accounting for informative dropout in a cancer clinical trial.

PURPOSE: A joint modeling approach is recommended for analysis of longitudinal health-related quality of life (HRQoL) data in the presence of potentially informative dropouts. However, the linear mixed model modeling the longitudinal HRQoL outcome in a joint model often assumes a linear trajectory over time, an oversimplification that can lead to incorrect results. Our aim was to demonstrate that a more flexible model gives more reliable and complete results without complicating their interpretation. METHODS: Five dimensions of HRQoL in patients with esophageal cancer from the randomized clinical trial PRODIGE 5/ACCORD 17 were analyzed. Joint models assuming linear or spline-based HRQoL trajectories were applied and compared in terms of interpretation of results, graphical representation, and goodness of fit. RESULTS: Spline-based models allowed arm-by-time interaction effects to be highlighted and led to a more precise and consistent representation of the HRQoL over time; this was supported by the martingale residuals and the Akaike information criterion. CONCLUSION: Linear relationships between continuous outcomes (such as HRQoL scores) and time are usually the default choice. However, the functional form turns out to be important by affecting both the validity of the model and the statistical significance. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov, number NCT00861094.

Residual Viremia Is Linked to a Specific Immune Activation Profile in HIV-1-Infected Adults Under Efficient Antiretroviral Therapy.

Chronic immune activation persists in persons living with HIV-1 even though they are aviremic under antiretroviral therapy, and fuels comorbidities. In previous studies, we have revealed that virologic responders present distinct profiles of immune activation, and that one of these profiles is related to microbial translocation. In the present work, we tested in 140 HIV-1-infected adults under efficient treatment for a mean duration of eight years whether low-level viremia might be another cause of immune activation. We observed that the frequency of viremia between 1 and 20 HIV-1 RNA copies/mL (39.5 ± 24.7% versus 21.1 ± 22.5%, p = 0.033) and transient viremia above 20 HIV-1 RNA copies/mL (15.1 ± 16.9% versus 3.3 ± 7.2%, p = 0.005) over the 2 last years was higher in patients with one profile of immune activation, Profile E, than in the other patients. Profile E, which is different from the profile related to microbial translocation with frequent CD38+ CD8+ T cells, is characterized by a high level of CD4+ T cell (cell surface expression of CD38), monocyte (plasma concentration of soluble CD14), and endothelium (plasma concentration of soluble Endothelial Protein C Receptor) activation, whereas the other profiles presented low CD4:CD8 ratio, elevated proportions of central memory CD8+ T cells or HLA-DR+ CD4+ T cells, respectively. Our data reinforce the hypothesis that various etiological factors shape the form of the immune activation in virologic responders, resulting in specific profiles. Given the type of immune activation of Profile E, a potential causal link between low-level viremia and atherosclerosis should be investigated.

Identification of distinct immune activation profiles in adult humans.

Latent infectious agents, microbial translocation, some metabolites and immune cell subpopulations, as well as senescence modulate the level and quality of activation of our immune system. Here, we tested whether various in vivo immune activation profiles may be distinguished in a general population. We measured 43 markers of immune activation by 8-color flow cytometry and ELISA in 150 adults, and performed a double hierarchical clustering of biomarkers and volunteers. We identified five different immune activation profiles. Profile 1 had a high proportion of naïve T cells. By contrast, Profiles 2 and 3 had an elevated percentage of terminally differentiated and of senescent CD4+ T cells and CD8+ T cells, respectively. The fourth profile was characterized by NK cell activation, and the last profile, Profile 5, by a high proportion of monocytes. In search for etiologic factors that could determine these profiles, we observed a high frequency of naïve Treg cells in Profile 1, contrasting with a tendency to a low percentage of Treg cells in Profiles 2 and 3. Moreover, Profile 5 tended to have a high level of 16s ribosomal DNA, a direct marker of microbial translocation. These data are compatible with a model in which specific causes, as the frequency of Treg or the level of microbial translocation, shape specific profiles of immune activation. It will be of interest to analyze whether some of these profiles drive preferentially some morbidities known to be fueled by immune activation, as insulin resistance, atherothrombosis or liver steatosis.

Should we use liver grafts repeatedly refused by other transplant teams?

BACKGROUND & AIMS: In France, liver grafts that have been refused at least 5 times can be "rescued" and allocated to a centre which chooses a recipient from its own waiting list, outside the patient-based allocation framework. We explored whether these "rescued" grafts were associated with worse graft/patient survival, as well as assessing their effect on survival benefit. METHODS: Among 7,895 candidates, 5,218 were transplanted between 2009 and 2014 (336 centre-allocated). We compared recipient/graft survival between patient allocation and centre allocation, considering a selection bias and the distribution of centre-allocation recipients among the transplant teams. We used a propensity score approach and a weighted Cox model using the inverse probability of treatment weighting method. We also explored the survival benefit associated with centre-allocation grafts. RESULTS: There was a significantly higher risk of graft loss/death in the centre allocation group compared to the patient allocation group (hazard ratio 1.13; 95% CI 1.05-1.22). However, this difference was no longer significant for teams that performed more than 7% of the centre-allocation transplantations. Moreover, receiving a centre-allocation graft, compared to remaining on the waiting list and possibly later receiving a patient-allocation graft, did not convey a poorer survival benefit (hazard ratio 0.80; 95% CI 0.60-1.08). CONCLUSIONS: In centres which transplanted most of the centre-allocation grafts, using grafts repeatedly refused for top-listed candidates was not detrimental. Given the organ shortage, our findings should encourage policy makers to restrict centre-allocation grafts to targeted centres. LAY SUMMARY: "Centre allocation" (CA) made it possible to save 6 out of 100 available liver grafts that had been refused at least 5 times for use in the top-listed candidates on the national waiting list. In this series, the largest on this topic, we showed that, in centres which transplanted most of the CA grafts, using grafts repeatedly refused for top-listed candidates did not appear to be detrimental. In the context of organ shortage, our results, which could be of interest for any country using this CA strategy, should encourage policy makers to reassess some aspects of graft allocation by restricting CA grafts to targeted centres, fostering the "best" matching between grafts and candidates on the waiting list.

Matching Graft Quality to Recipient's Disease Severity Based on the Survival Benefit in Liver Transplantation.

Persistent shortage and heterogeneous quality of liver grafts encourages the optimization of donor-recipient matching in liver transplantation (LT). We explored whether or not there was a survival benefit (SB) of LT according to the quality of grafts assessed by the Donor Quality Index (DQI) and recipients' disease severity, using the Model for End-Stage Liver Disease (MELD) in 8387 French patients wait-listed between 2009 and 2014. SB associated with LT was estimated using the sequential stratification method in different categories of MELD and DQI. For each transplantation, a stratum was created that matched one transplanted patient with all eligible control candidates. Strata were thereafter combined, and a stratified Cox model, adjusted for covariates, was fitted in order to estimate hazard ratios that qualified the SB according to each MELD and DQI sub-group. A significant SB was observed for all MELD and DQI sub-groups, with the exception of high MELD patients transplanted with "high-risk" grafts. More specifically, in decompensated-cirrhosis patients, "high-risk" grafts did not appear to be detrimental in medium MELD patients. Interestingly, in hepatocellular-carcinoma (HCC) patients, a significant SB was found for all MELD-DQI combinations. For MELD exceptions no SB was found. In terms of SB, "low-risk" grafts appeared appropriate for most severe patients (MELD > 30). Conversely, low/medium MELD and HCC patients presented an SB while allocated "high-risk" grafts. Thus, SB based matching rules for LT candidates might improve the survival of the LT population as a whole.

Liver Transplantation with "Hors Tour" Allocated Versus Standard MELD Allocated Grafts: Single-Center Audit and Impact on the Liver Pool in France.

BACKGROUND: The French transplant governing system defined "Rescue" (the so-called "Hors Tour") livers as those livers which were declined for the five top-listed patients. This study compares the outcomes following liver transplantation (LT) in patients who received a donor liver through a rescue allocation (RA) procedure or according to MELD score priority (standard allocation, SA) and evaluates the impact on the graft pool of a proactive policy to accept RA grafts. METHODS: Data from all consecutive patients who underwent LT with SA or RA grafts from 2011 to 2015 were compared in terms of short- and long-term outcomes. RESULTS: The 249 elective first LTs were performed with 64 (25.7%) RA and 185 (74.3%) SA grafts. RA grafts were obtained from older donors and were associated with a longer cold ischemia time. Recipients of RA livers were older and had lower MELD scores. The rates of delayed graft function, primary nonfunction, retransplantation, complications, and mortality were similar between the RA and SA groups. At 1 and 3 and 5 years, graft and patient survival rates were similar between the groups. These results were maintained after matching on recipient characteristics. Our proactive policy to accept RA grafts increased the liver pool for elective first transplantation by 25%. CONCLUSIONS: RA livers can be safely transplanted into selected recipients and significantly expand the liver pool.

Microbial Translocation Is Linked to a Specific Immune Activation Profile in HIV-1-Infected Adults With Suppressed Viremia.

Persistent immune activation in virologically suppressed HIV-1 patients, which may be the consequence of various factors including microbial translocation, is a major cause of comorbidities. We have previously shown that different profiles of immune activation may be distinguished in virological responders. Here, we tested the hypothesis that a particular profile might be the consequence of microbial translocation. To this aim, we measured 64 soluble and cell surface markers of inflammation and CD4+ and CD8+ T-cell, B cell, monocyte, NK cell, and endothelial activation in 140 adults under efficient antiretroviral therapy, and classified patients and markers using a double hierarchical clustering analysis. We also measured the plasma levels of the microbial translocation markers bacterial DNA, lipopolysaccharide binding protein (LBP), intestinal-fatty acid binding protein, and soluble CD14. We identified five different immune activation profiles. Patients with an immune activation profile characterized by a high percentage of CD38+CD8+ T-cells and a high level of the endothelial activation marker soluble Thrombomodulin, presented with higher LBP mean (± SEM) concentrations (33.3 ± 1.7 vs. 28.7 ± 0.9 µg/mL, p = 0.025) than patients with other profiles. Our data are consistent with the hypothesis that the immune activation profiles we described are the result of different etiological factors. We propose a model, where particular causes of immune activation, as microbial translocation, drive particular immune activation profiles responsible for particular comorbidities.

External validation and recalibration of the Brock model to predict probability of cancer in pulmonary nodules using NLST data.

INTRODUCTION: We performed an external validation of the Brock model using the National Lung Screening Trial (NLST) data set, following strict guidelines set forth by the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis statement. We report how external validation results can be interpreted and highlight the role of recalibration and model updating. MATERIALS AND METHODS: We assessed model discrimination and calibration using the NLST data set. Adhering to the inclusion/exclusion criteria reported by McWilliams et al, we identified 7879 non-calcified nodules discovered at the baseline low-dose CT screen with 2 years of follow-up. We characterised differences between Pan-Canadian Early Detection of Lung Cancer Study and NLST cohorts. We calculated the slope on the prognostic index and the intercept coefficient by fitting the original Brock model to NLST. We also assessed the impact of model recalibration and the addition of new covariates such as body mass index, smoking status, pack-years and asbestos. RESULTS: While the area under the curve (AUC) of the model was good, 0.905 (95% CI 0.882 to 0.928), a histogram plot showed that the model poorly differentiated between benign and malignant cases. The calibration plot showed that the model overestimated the probability of cancer. In recalibrating the model, the coefficients for emphysema, spiculation and nodule count were updated. The updated model had an improved calibration and achieved an optimism-corrected AUC of 0.912 (95% CI 0.891 to 0.932). Only pack-year history was found to be significant (p<0.01) among the new covariates evaluated. CONCLUSION: While the Brock model achieved a high AUC when validated on the NLST data set, the model benefited from updating and recalibration. Nevertheless, covariates used in the model appear to be insufficient to adequately discriminate malignant cases.

Using Sequential Decision Making to Improve Lung Cancer Screening Performance.

Globally, lung cancer is responsible for nearly one in five cancer deaths. The National Lung Screening Trial (NLST) demonstrated the efficacy of low-dose computed tomography (LDCT) to identify early-stage disease, setting the basis for widespread implementation of lung cancer screening programs. However, the specificity of LDCT lung cancer screening is suboptimal, with a significant false positive rate. Representing this imaging-based screening process as a sequential decision making problem, we combined multiple machine learning-based methods to learn a partially-observable Markov decision process that simultaneously optimizes lung cancer detection while enhancing test specificity. Using NLST data, we trained a dynamic Bayesian network as an observational model and used inverse reinforcement learning to discover a rewards function based on experts' decisions. Our resultant predictive model decreased the false positive rate while maintaining a high true positive rate at a level comparable to human experts. Our model also detected a number of lung cancers earlier.

Author Correction: A Donor Quality Index for liver transplantation: development, internal and external validation.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

A Donor Quality Index for liver transplantation: development, internal and external validation.

Organ shortage leads to using non-optimal liver grafts. Thus, to determine the graft quality, the Donor Risk Index and the Eurotransplant Donor Risk Index have been proposed. In a previous study we showed that neither could be validated on the French database. Our aim was then dedicated to propose an adaptive Donor Quality Index (DQI) using data from 3961 liver transplantation (LT) performed in France between 2009 and 2013, with an external validation based on 1048 French LT performed in 2014. Using Cox models and three different methods of selection, we developed a new score and defined groups at risk. Model performance was assessed by means of three measures of discrimination corrected by the optimism using a bootstrap procedure. An external validation was also performed in order to evaluate its calibration and discrimination. Five donor covariates were retained: age, cause of death, intensive care unit stay, lowest MDRD creatinine clearance, and liver type. Three groups at risk could be discriminated. The performances of the model were satisfactory after internal validation. Calibration and discrimination were preserved in the external validation dataset. The DQI exhibited good properties and is potentially adaptive as an aid for better guiding decision making for LT.

External validation of the Donor Risk Index and the Eurotransplant Donor Risk Index on the French liver transplantation registry.

BACKGROUND & AIMS: A major limitation to liver transplantation is organ shortage leading to the use of non-optimal liver grafts. The Donor Risk Index has been validated and recommended to select donors/organs. The Eurotransplant Donor Risk Index was derived from the Donor Risk Index. The objective of our study was to perform an external validation of both Donor Risk Index and Eurotransplant-Donor Risk Index against the French liver transplantation Cristal registry according to recommendations of the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis. METHODS: Liver transplantations performed in France between 2009 and 2013 were used to perform the validation study for the Donor Risk Index and the Eurotransplant-Donor Risk Index respectively. We applied on the French data the models used to construct the Donor Risk Index and the Eurotransplant-Donor Risk Index respectively. RESULTS: Neither the Donor Risk Index nor the Eurotransplant-Donor Risk Index were validated against this dataset. Discrimination and calibration of these scores were not preserved according to our data. Important donor and candidates differences between our dataset and the Organ Procurement and Transplantation Network or the Eurotransplant datasets may explain why the Donor Risk Index and the Eurotransplant-Donor Risk Index appeared unadapted to the French transplant registry. CONCLUSION: Neither of these risk indexes were suitable to optimize the French liver allocation system. Thus, our next step will be to propose a general adaptive model for a Donor Risk Index.

Impact of acute-on-chronic liver failure on 90-day mortality following a first liver transplantation.

BACKGROUND: Acute-on-chronic liver failure (ACLF) is associated with a significant short-term mortality rate (23%-74%), depending on the number of organ failures. Some patients present with ACLF at the time of liver transplantation (LT). The aim of this study was to assess whether ACLF was also a prognostic factor after LT and, if applicable, to construct a score that could predict 90-day mortality. METHODS: Three hundred and fifty cirrhotic patients, who underwent LT between January 2008 and December 2013, were enrolled. We used ACLF grades according to EASL-CLIF consortium criteria to categorize the cirrhotic patients. A propensity score was applied with an Inverse Probability Treatment Weighting in a Cox model. A predictive score of early mortality after LT was generated. RESULTS: One hundred and forty patients (40%) met the criteria for ACLF. The overall mortality rate at 90 days post-transplant was 10.6% (37/350 patients). ACLF at the time of LT (HR: 5.78 [3.42-9.77], P<.001) was an independent predictor of 90-day mortality. Infection occurring during the month before LT, high recipient age and male recipient, the reason for LT and a female donor were also independent risk factors for early mortality. Using these factors, we have proposed a model to predict 90-day mortality after LT. CONCLUSIONS: LT is feasible in cirrhotic patients with ACLF. However, we have shown that ACLF is a significant and independent predictor of 90-day mortality. We propose a score that can identify candidate cirrhotic patients in whom LT might be associated with futile LT.

Follow-Up of Alcohol Consumption After Liver Transplantation: Interest of an Addiction Team?

BACKGROUND: Alcohol relapses after liver transplantation (LT) constitute a critical issue. Because there is no widely accepted definition of LT, its prevalence varies from 7 to 95% across studies. Only a severe relapse, the frequency of which is estimated to be 11 to 26%, decreases life expectancy after 5 years of LT and requires specific care. To improve the early identification of alcohol consumption among transplanted patients, liver transplant teams may be helped by input from an addiction team. Nevertheless, added benefit of involvement by addiction specialists in treating posttransplant patients has not been demonstrated. Thus, the aim of this study was to compare the evaluation of the alcohol consumption after LT performed routinely during the transplant consultation or obtained from a specific addiction consultation. METHODS: This was a prospective single-site study. Patients were seen consecutively by their hepatologist and by an addiction specialist, and they completed the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C). Thus, the patient's alcohol status was assessed using 3 different sources of information: the hepatologist's interview, the AUDIT-C score, and the addiction specialist visit. RESULTS: One hundred forty-one patients were consecutively evaluated. Alcohol consumption was identified by the hepatologist in 31 patients (21.9%), in 52 (36.8%) using the AUDIT-C questionnaire, and in 58 (41.1%) by the addiction specialist. The 31 patients concerned reported an average of 6.5 alcohol units/wk to the transplant physician, a number which was significantly greater (p = 0.001) by 8.6 units/wk when they were interviewed by the addiction specialist. CONCLUSIONS: This study highlights the clinical utility of a systematic addiction consultation among liver transplant patients, irrespective of the reason for transplantation.