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 McWilliamset 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.

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.

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.

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.

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. 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. 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). 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. “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.