Statistical approach to quality assessment in liver transplantation.

PURPOSE: This study investigated the utility of retrospective two one-sided cumulative sum (CUSUM) charts combined with multivariable regression analysis in liver transplantation for transplant center benchmarking. METHODS: One thousand seven hundred and forty-nine consecutive adult primary liver transplants (January 1, 1983 to December 31, 2012) were analyzed retrospectively with two one-sided CUSUM chart analysis of 90-day mortality. RESULTS: Three eras and two subseries in latest era 3 were identified due to graphically delineated relevant shifts in mean 90-day mortality. Delineation of eras 1, 2, and 3 coincided with relevant changes in allocation policies. CUSUM analysis detected a resurgence of higher mean 90-day mortality in era 3 after results had improved continuously over 25 years. In era 3, two subseries were identified with improving mean 90-day mortality rates from 15.4% in subseries 1 to 8.9% in the following subseries 2. The quantitative influence of independent risk factors on 90-day mortality differed markedly between all identified eras and subseries as assessed with multivariable regression analysis deployed on era-specific subcohorts. CONCLUSION: The assessed methodology is able to identify meaningful center-specific eras and subseries of liver transplantation with striking alterations of the significance and weight of outcome drivers for post-transplant 90-day mortality over time. This warrants the introduction of prospective risk-adjusted two one-sided CUSUM chart analysis into quality management in liver transplantation in Germany with the goal to obtain alarm signals as early as possible.

Independent Pre-Transplant Recipient Cancer Risk Factors after Kidney Transplantation and the Utility of G-Chart Analysis for Clinical Process Control.

BACKGROUND: The aim of this study is to identify independent pre-transplant cancer risk factors after kidney transplantation and to assess the utility of G-chart analysis for clinical process control. This may contribute to the improvement of cancer surveillance processes in individual transplant centers. PATIENTS AND METHODS: 1655 patients after kidney transplantation at our institution with a total of 9,425 person-years of follow-up were compared retrospectively to the general German population using site-specific standardized-incidence-ratios (SIRs) of observed malignancies. Risk-adjusted multivariable Cox regression was used to identify independent pre-transplant cancer risk factors. G-chart analysis was applied to determine relevant differences in the frequency of cancer occurrences. RESULTS: Cancer incidence rates were almost three times higher as compared to the matched general population (SIR = 2.75; 95%-CI: 2.33-3.21). Significantly increased SIRs were observed for renal cell carcinoma (SIR = 22.46), post-transplant lymphoproliferative disorder (SIR = 8.36), prostate cancer (SIR = 2.22), bladder cancer (SIR = 3.24), thyroid cancer (SIR = 10.13) and melanoma (SIR = 3.08). Independent pre-transplant risk factors for cancer-free survival were age <52.3 years (p = 0.007, Hazard ratio (HR): 0.82), age >62.6 years (p = 0.001, HR: 1.29), polycystic kidney disease other than autosomal dominant polycystic kidney disease (ADPKD) (p = 0.001, HR: 0.68), high body mass index in kg/m2 (p<0.001, HR: 1.04), ADPKD (p = 0.008, HR: 1.26) and diabetic nephropathy (p = 0.004, HR = 1.51). G-chart analysis identified relevant changes in the detection rates of cancer during aftercare with no significant relation to identified risk factors for cancer-free survival (p<0.05). CONCLUSIONS: Risk-adapted cancer surveillance combined with prospective G-chart analysis likely improves cancer surveillance schemes by adapting processes to identified risk factors and by using G-chart alarm signals to trigger Kaizen events and audits for root-cause analysis of relevant detection rate changes. Further, comparative G-chart analysis would enable benchmarking of cancer surveillance processes between centers.

The new liver allocation score for transplantation is validated and improved transplant survival benefit in Germany but not in the United Kingdom.

Prognostic models for the prediction of 90-day mortality after transplantation with pretransplant donor and recipient variables are needed to calculate transplant benefit. Transplants in adult recipients in Germany (Hannover, n = 770; Kiel, n = 234) and the United Kingdom (Birmingham, n = 829) were used for prognostic model design and validation in separate training and validation cohorts. The survival benefit of transplantation was estimated by subtracting the observed posttransplant 90-day mortality from the expected 90-day mortality without transplantation determined by the Model for End-Stage Liver Disease (MELD) score. A prognostic model called the liver allocation score (LivAS) was derived using a randomized sample from Hannover using pretransplant donor and recipient variables. This model could be validated in the German training and validation cohorts (area under the receiver operating characteristic curve [AUROC] > 0.70) but not in the English cohort (AUROC, 0.58). Although 90-day mortality rates after transplantation were 13.7% in Hannover, 12.1% in Kiel, and 8.3% in Birmingham, the calculated 90-day survival benefits of transplantation were 6.8% in Hannover, 7.8% in Kiel, and 2.8% in Birmingham. Deployment of the LivAS for limiting allocation to donor and recipient combinations with likely 90-day survival as indicated by pretransplant LivAS values below the cutoff value would have increased the survival benefit to 12.9% in the German cohorts, whereas this would have decreased the benefit in England to 1.3%. The English and German cohorts revealed significant differences in 21 of 28 pretransplant variables. In conclusion, the LivAS could be validated in Germany and may improve German allocation policies leading to greater survival benefits, whereas validation failed in England due to profound differences in the selection criteria for liver transplantation. This study suggests the need for national prognostic models. Even though the German centers had higher rates of 90-day mortality, estimated survival benefits were greater. Liver Transplantation 22 743-756 2016 AASLD.

Prognostic limitations of the Eurotransplant-Donor Risk Index in liver transplantation.

BACKGROUND: Liver transplantation is the only life-saving therapeutic option for end-stage liver disease. Progressive donor organ shortage and declining donor organ quality justify the evaluation of the leverage of the Donor-Risk-Index, which was recently adjusted to the Eurotransplant community's requirements (ET-DRI). We analysed the prognostic value of the ET-DRI for the prediction of outcome after liver transplantation in our center within the Eurotransplant community. RESULTS: 291 consecutive adult liver transplants were analysed in a single centre study with ongoing data collection. Determination of the area under the receiver operating characteristic curve (AUROC) was performed to calculate the sensitivity, specificity, and overall correctness of the Eurotransplant-Donor-Risk-Index (ET-DRI) for the prediction of 3-month and 1-year mortality, as well as 3-month and 1-year graft survival. Cut-off values were determined with the best Youden-index. The ET-DRI is unable to predict 3-month mortality (AUROC: 0.477) and 3-month graft survival (AUROC: 0.524) with acceptable sensitivity, specificity and overall correctness (54% and 56.3%, respectively). Logistic regression confirmed this finding (p = 0.573 and p = 0.163, respectively). Determined cut-off values of the ET-DRI for these predictions had no significant influence on long-term patient and graft survival (p = 0.230 and p = 0.083, respectively; Kaplan-Meier analysis with Log-Rank test). CONCLUSIONS: The ET-DRI should not be used for donor organ allocation policies without further evaluation, e.g. in combination with relevant recipient variables. Robust and objective prognostic scores for donor organ allocation purposes are desperately needed to balance equity and utility in donor organ allocation.