ICG-Fluorescence Imaging for Margin Assessment During Minimally Invasive Colorectal Liver Metastasis Resection.

Importance: Unintended tumor-positive resection margins occur frequently during minimally invasive surgery for colorectal liver metastases and potentially negatively influence oncologic outcomes. Objective: To assess whether indocyanine green (ICG)-fluorescence-guided surgery is associated with achieving a higher radical resection rate in minimally invasive colorectal liver metastasis surgery and to assess the accuracy of ICG fluorescence for predicting the resection margin status. Design, Setting, and Participants: The MIMIC (Minimally Invasive, Indocyanine-Guided Metastasectomy in Patients With Colorectal Liver Metastases) trial was designed as a prospective single-arm multicenter cohort study in 8 Dutch liver surgery centers. Patients were scheduled to undergo minimally invasive (laparoscopic or robot-assisted) resections of colorectal liver metastases between September 1, 2018, and June 30, 2021. Exposures: All patients received a single intravenous bolus of 10 mg of ICG 24 hours prior to surgery. During surgery, ICG-fluorescence imaging was used as an adjunct to ultrasonography and regular laparoscopy to guide and assess the resection margin in real time. The ICG-fluorescence imaging was performed during and after liver parenchymal transection to enable real-time assessment of the tumor margin. Absence of ICG fluorescence was favorable both during transection and in the tumor bed directly after resection. Main Outcomes and Measures: The primary outcome measure was the radical (R0) resection rate, defined by the percentage of colorectal liver metastases resected with at least a 1 mm distance between the tumor and resection plane. Secondary outcomes were the accuracy of ICG fluorescence in detecting margin-positive (R1; <1 mm margin) resections and the change in surgical management. Results: In total, 225 patients were enrolled, of whom 201 (116 [57.7%] male; median age, 65 [IQR, 57-72] years) with 316 histologically proven colorectal liver metastases were included in the final analysis. The overall R0 resection rate was 92.4%. Re-resection of ICG-fluorescent tissue in the resection cavity was associated with a 5.0% increase in the R0 percentage (from 87.4% to 92.4%; P < .001). The sensitivity and specificity for real-time resection margin assessment were 60% and 90%, respectively (area under the receiver operating characteristic curve, 0.751; 95% CI, 0.668-0.833), with a positive predictive value of 54% and a negative predictive value of 92%. After training and proctoring of the first procedures, participating centers that were new to the technique had a comparable false-positive rate for predicting R1 resections during the first 10 procedures (odds ratio, 1.36; 95% CI, 0.44-4.24). The ICG-fluorescence imaging was associated with changes in intraoperative surgical management in 56 (27.9%) of the patients. Conclusions and Relevance: In this multicenter prospective cohort study, ICG-fluorescence imaging was associated with an increased rate of tumor margin-negative resection and changes in surgical management in more than one-quarter of the patients. The absence of ICG fluorescence during liver parenchymal transection predicted an R0 resection with 92% accuracy. These results suggest that use of ICG fluorescence may provide real-time feedback of the tumor margin and a higher rate of complete oncologic resection.

Deep learning based tumor-stroma ratio scoring in colon cancer correlates with microscopic assessment.

Background: The amount of stroma within the primary tumor is a prognostic parameter for colon cancer patients. This phenomenon can be assessed using the tumor-stroma ratio (TSR), which classifies tumors in stroma-low (≤50% stroma) and stroma-high (>50% stroma). Although the reproducibility for TSR determination is good, improvement might be expected from automation. The aim of this study was to investigate whether the scoring of the TSR in a semi- and fully automated method using deep learning algorithms is feasible. Methods: A series of 75 colon cancer slides were selected from a trial series of the UNITED study. For the standard determination of the TSR, 3 observers scored the histological slides. Next, the slides were digitized, color normalized, and the stroma percentages were scored using semi- and fully automated deep learning algorithms. Correlations were determined using intraclass correlation coefficients (ICCs) and Spearman rank correlations. Results: 37 (49%) cases were classified as stroma-low and 38 (51%) as stroma-high by visual estimation. A high level of concordance between the 3 observers was reached, with ICCs of 0.91, 0.89, and 0.94 (all P < .001). Between visual and semi-automated assessment the ICC was 0.78 (95% CI 0.23-0.91, P-value 0.005), with a Spearman correlation of 0.88 (P < .001). Spearman correlation coefficients above 0.70 (N=3) were observed for visual estimation versus the fully automated scoring procedures. Conclusion: Good correlations were observed between standard visual TSR determination and semi- and fully automated TSR scores. At this point, visual examination has the highest observer agreement, but semi-automated scoring could be helpful to support pathologists.

General tests of the Markov property in multi-state models.

Multi-state models for event history analysis most commonly assume the process is Markov. This article considers tests of the Markov assumption that are applicable to general multi-state models. Two approaches using existing methodology are considered; a simple method based on including time of entry into each state as a covariate in Cox models for the transition intensities and a method involving detecting a shared frailty through a stratified Commenges-Andersen test. In addition, using the principle that under a Markov process the future rate of transitions of the process at times $t > s$ should not be influenced by the state occupied at time $s$, a new class of general tests is developed by considering summaries from families of log-rank statistics where patients are grouped by the state occupied at varying initial time $s$. An extended form of the test applicable to models that are Markov conditional on observed covariates is also derived. The null distribution of the proposed test statistics are approximated by using wild bootstrap sampling. The approaches are compared in simulation and applied to a dataset on sleeping behavior. The most powerful test depends on the particular departure from a Markov process, although the Cox-based method maintained good power in a wide range of scenarios. The proposed class of log-rank statistic based tests are most useful in situations where the non-Markov behavior does not persist, or is not uniform in nature across patient time.

Inaccurate Risk Assessment by the ACS NSQIP Risk Calculator in Aortic Surgery.

OBJECTIVES: The aim of this retrospective study was to assess the predictive performance of the American College of Surgeons (ACS) risk calculator for aortic aneurysm repair for the patient population of a Dutch tertiary referral hospital. METHODS: This retrospective study included all patients who underwent elective endovascular or open aortic aneurysm repair at our institution between the years 2013 and 2019. Preoperative patient demographics and postoperative complication data were collected, and individual risk assessments were generated using five different current procedural terminology (CPT) codes. Receiver operating characteristic (ROC) curves, calibration plots, Brier scores, and Index of Prediction Accuracy (IPA) values were generated to evaluate the predictive performance of the ACS risk calculator in terms of discrimination and calibration. RESULTS: Two hundred thirty-four patients who underwent elective endovascular or open aortic aneurysm repair were identified. Only five out of thirteen risk predictions were found to be sufficiently discriminative. Furthermore, the ACS risk calculator showed a structurally insufficient calibration. Most Brier scores were close to 0; however, comparison to a null model though IPA-scores showed the predictions generated by the ACS risk calculator to be inaccurate. Overall, the ACS risk calculator showed a consistent underestimation of the risk of complications. CONCLUSIONS: The ACS risk calculator proved to be inaccurate within the framework of endovascular and open aortic aneurysm repair in our medical center. To minimize the effects of patient selection and cultural differences, multicenter collaboration is necessary to assess the performance of the ACS risk calculator in aortic surgery.

Combined Assessment of the Tumor-Stroma Ratio and Tumor Immune Cell Infiltrate for Immune Checkpoint Inhibitor Therapy Response Prediction in Colon Cancer.

The best current biomarker strategies for predicting response to immune checkpoint inhibitor (ICI) therapy fail to account for interpatient variability in response rates. The histologic tumor-stroma ratio (TSR) quantifies intratumoral stromal content and was recently found to be predictive of response to neoadjuvant therapy in multiple cancer types. In the current work, we predicted the likelihood of ICI therapy responsivity of 335 therapy-naive colon adenocarcinoma tumors from The Cancer Genome Atlas, using bioinformatics approaches. The TSR was scored on diagnostic tissue slides, and tumor-infiltrating immune cells (TIICs) were inferred from transcriptomic data. Tumors with high stromal content demonstrated increased T regulatory cell infiltration (p = 0.014) but failed to predict ICI therapy response. Consequently, we devised a hybrid tumor microenvironment classification of four stromal categories, based on histological stromal content and transcriptomic-deconvoluted immune cell infiltration, which was associated with previously established transcriptomic and genomic biomarkers for ICI therapy response. By integrating these biomarkers, stroma-low/immune-high tumors were predicted to be most responsive to ICI therapy. The framework described here provides evidence for expansion of current histological TIIC quantification to include the TSR as a novel, easy-to-use biomarker for the prediction of ICI therapy response.

Resection of the Portal-Superior Mesenteric Vein in Pancreatic Cancer: Pathological Assessment and Recurrence Patterns.

OBJECTIVES: The portal vein (PV)-superior mesenteric vein (SMV) margin is the most affected margin in pancreatic cancer. This study investigates the association between venous resection, tumor invasion in the resected PV-SMV, recurrence patterns, and overall survival (OS). METHODS: This multicenter cohort study included patients who underwent pancreatoduodenectomy for pancreatic cancer (2010-2017). In addition, a systematic literature search was performed. RESULTS: In total, 531 patients were included, of which 149 (28%) underwent venous resection of whom 53% had tumor invasion in the resected PV-SMV. Patients with venous resection had a significant higher rate of R1 margins (69% vs 37%) and had more often multiple R1 margins (43% vs 16%). Patient with venous resection had a significant shorter time to locoregional recurrence and a shorter OS (15 vs 19 months). At multivariable analyses, venous resection and tumor invasion in the resected PV-SMV were not predictive for time to recurrence and OS. The literature overview showed that pathological assessment of the resected PV-SMV is not adequately standardized. CONCLUSIONS: Only half of patients with venous resection had pathology confirmed tumor invasion in the resected PV-SMV, and both are not independently associated with time to recurrence and OS. The pathological assessment of the resected PV-SMV needs to be standardized.

A hybrid landmark Aalen-Johansen estimator for transition probabilities in partially non-Markov multi-state models.

Multi-state models are increasingly being used to model complex epidemiological and clinical outcomes over time. It is common to assume that the models are Markov, but the assumption can often be unrealistic. The Markov assumption is seldomly checked and violations can lead to biased estimation of many parameters of interest. This is a well known problem for the standard Aalen-Johansen estimator of transition probabilities and several alternative estimators, not relying on the Markov assumption, have been suggested. A particularly simple approach known as landmarking have resulted in the Landmark-Aalen-Johansen estimator. Since landmarking is a stratification method a disadvantage of landmarking is data reduction, leading to a loss of power. This is problematic for "less traveled" transitions, and undesirable when such transitions indeed exhibit Markov behaviour. Introducing the concept of partially non-Markov multi-state models, we suggest a hybrid landmark Aalen-Johansen estimator for transition probabilities. We also show how non-Markov transitions can be identified using a testing procedure. The proposed estimator is a compromise between regular Aalen-Johansen and landmark estimation, using transition specific landmarking, and can drastically improve statistical power. We show that the proposed estimator is consistent, but that the traditional variance estimator can underestimate the variance of both the hybrid and landmark estimator. Bootstrapping is therefore recommended. The methods are compared in a simulation study and in a real data application using registry data to model individual transitions for a birth cohort of 184 951 Norwegian men between states of sick leave, disability, education, work and unemployment.

Competing risks in quality and safety research: a framework to guide choice of analysis and improve reporting.

When comparing hospitals on their readmission rates as currently done in the Hospital Readmission and Reduction Program (HRRP) in the USA, should we include the competing risk of mortality after discharge, which precludes the readmission, in the analysis? Not including competing risks in current HRRP metrics was raised recently as a limitation with possible unintended consequences, as financial penalties for higher readmission rates are more severe than for higher mortality rates. Incorrectly including or ignoring competing risks can both induce bias. In this paper, we present a framework to clarify situations when competing risks should be taken into account and when they should not. We argue that the research question and the perspective from which it is asked determine whether the competing risk is also of interest and should be included in the analysis, or if only the event of interest should be considered. This information is often not explicitly reported but is needed to interpret whether the results are valid. Using the examples of readmissions and cancer, we show how different research questions fit different perspectives from which these are asked (patient, system, regulatory/insurance). Slightly changing the research question or perspective may thus change the analysis. Even though some may argue that any introduced bias is likely to be small, in the context of the HRRP, even small changes may mean that a hospital will face (higher) financial penalties. The impact of getting it wrong matters.

Risk assessment in aortic aneurysm repair by medical specialists versus the American College of Surgeons National Surgical Quality Improvement Program risk calculator outcomes.

OBJECTIVE: The aim of this online clinical vignette-based survey study was to compare risk assessments by vascular surgeons, anaesthesiologists and interventional radiologists involved in treating patients with aortic aneurysms in the Netherlands with the NSQIP risk calculator outcomes. METHODS: Participants, recruited using purposive sampling, provided their estimation of the likelihood of postoperative complications and events following aortic surgery in five fictional cases. These cases were subsequently scored using the NSQIP calculator. The risk assessments were statistically analysed using the ANOVA and student t-test. RESULTS: All participating specialists i.e. twelve vascular surgeons, ten interventional radiologists and ten anaesthesiologists completed the survey. In the vast majority of outcomes and vignettes, no significant differences were found between various specialists, whereas significant differences were found between the NSQIP risk calculator outcomes and the combined risk assessments of the specialists. Overall, specialist risk assessments differ from the NSQIP, but neither particularly higher nor lower compared to the risk calculator. CONCLUSIONS: Risk assessment by vascular surgeons, anaesthesiologists and interventional radiologists differs significantly with NSQIP risk calculator outcomes, within the framework of both endovascular and open aortic aneurysm repair. Based on these results, implementing the NSQIP risk calculator in preoperative workup could be of added value in both patient planning as well as adequately informing patients for obtaining consent.

Assessment of assumptions of statistical analysis methods in randomised clinical trials: the what and how.

When analysing and presenting results of randomised clinical trials, trialists rarely report if or how underlying statistical assumptions were validated. To avoid data-driven biased trial results, it should be common practice to prospectively describe the assessments of underlying assumptions. In existing literature, there is no consensus on how trialists should assess and report underlying assumptions for the analyses of randomised clinical trials. With this study, we developed suggestions on how to test and validate underlying assumptions behind logistic regression, linear regression, and Cox regression when analysing results of randomised clinical trials.Two investigators compiled an initial draftbased on a review of the literature. Experienced statisticians and trialists from eight different research centres and trial units then participated in a anonymised consensus process, where we reached agreement on the suggestions presented in this paper.This paper provides detailed suggestions on 1) which underlying statistical assumptions behind logistic regression, multiple linear regression and Cox regression each should be assessed; 2) how these underlying assumptions may be assessed; and 3) what to do if these assumptions are violated.We believe that the validity of randomised clinical trial results will increase if our recommendations for assessing and dealing with violations of the underlying statistical assumptions are followed.

Unravelling sexual care in chronically ill patients: the perspective of GP practice nurses; Health Service Research.

BACKGROUND: Assessment of sexual health is important in chronically ill patients, as many experience sexual dysfunction (SD). The general practice nurse (GPN) can play a crucial part in addressing SD. OBJECTIVE: The aim of this cross-sectional study was to examine to which extent GPNs discuss SD with chronically ill patients and what barriers may refrained them from discussing SD. Furthermore, we examined which factors had an association with a higher frequency of discussing SD. METHODS: A cross-sectional survey using a 48-item questionnaire was send to 637 GPNs across the Netherlands. RESULTS: In total, 407 GPNs returned the questionnaire (response rate 63.9%) of which 337 completed the survey. Two hundred and twenty-one responding GPNs (65.6%) found it important to discuss SD. More than half of the GPNS (n = 179, 53.3%) never discussed SD during a first consultation, 60 GPNs (18%) never discussed SD during follow-up consultations. The three most important barriers for discussing SD were insufficient training (54.7%), 'reasons related to language and ethnicity' (47.5%) and 'reasons related to culture and religion' (45.8%). More than half of the GPNs thought that they had not enough knowledge to discuss SD (n = 176, 54.8%). A protocol on addressing SD would significantly increase discussing during SD. CONCLUSIONS: This study indicates that GPNs do not discuss SD with chronically ill patients routinely. Insufficient knowledge, training and reasons related to cultural diversity were identified as most important reasons for this practice pattern. Implementation of training in combination with guidelines on SD in the general practice could improve on the discussing of sexual health with chronic patients.

Landmark estimation of transition probabilities in non-Markov multi-state models with covariates.

In non-Markov multi-state models, the traditional Aalen-Johansen (AJ) estimator for state transition probabilities is generally not valid. An alternative, suggested by Putter and Spitioni, is to analyse a subsample of the full data, consisting of the individuals present in a specific state at a given landmark time-point. The AJ estimator of occupation probabilities is then applied to the landmark subsample. Exploiting the result by Datta and Satten, that the AJ estimator is consistent for state occupation probabilities even in non-Markov models given that censoring is independent of state occupancy and times of transition between states, the landmark Aalen-Johansen (LMAJ) estimator provides consistent estimates of transition probabilities. So far, this approach has only been studied for non-parametric estimation without covariates. In this paper, we show how semi-parametric regression models and inverse probability weights can be used in combination with the LMAJ estimator to perform covariate adjusted analyses. The methods are illustrated by a simulation study and an application to population-wide registry data on work, education and health-related absence in Norway. Results using the traditional AJ estimator and the LMAJ estimator are compared, and show large differences in estimated transition probabilities for highly non-Markov multi-state models.

Outcome of Liver Transplant Patients With High Urgent Priority: Are We Doing the Right Thing?

BACKGROUND: About 15% of liver transplantations (LTs) in Eurotransplant are currently performed in patients with a high-urgency (HU) status. Patients who have acute liver failure (ALF) or require an acute retransplantation can apply for this status. This study aims to evaluate the efficacy of this prioritization. METHODS: Patients who were listed for LT with HU status from January 1, 2007, up to December 31, 2015, were included. Waiting list and posttransplantation outcomes were evaluated and compared with a reference group of patients with laboratory Model for End-Stage Liver Disease (MELD) score (labMELD) scores ≥40 (MELD 40+). RESULTS: In the study period, 2299 HU patients were listed for LT. Ten days after listing, 72% of all HU patients were transplanted and 14% of patients deceased. Patients with HU status for primary ALF showed better patient survival at 3 years (69%) when compared with patients in the MELD 40+ group (57%). HU patients with labMELD ≥45 and patients with HU status for acute retransplantation and labMELD ≥35 have significantly inferior survival at 3-year follow-up of 46% and 42%, respectively. CONCLUSIONS: Current prioritization for patients with ALF is highly effective in preventing mortality on the waiting list. Although patients with HU status for ALF have good outcomes, survival is significantly inferior for patients with a high MELD score or for retransplantations. With the current scarcity of livers in mind, we should discuss whether potential recipients for a second or even third retransplantation should still receive absolute priority, with HU status, over other recipients with an expected, substantially better prognosis after transplantation.

Individual dynamic predictions using landmarking and joint modelling: Validation of estimators and robustness assessment.

After the diagnosis of a disease, one major objective is to predict cumulative probabilities of events such as clinical relapse or death from the individual information collected up to a prediction time, usually including biomarker repeated measurements. Several competing estimators have been proposed, mainly from two approaches: joint modelling and landmarking. These approaches differ by the information used, the model assumptions and the complexity of the computational procedures. This paper aims to review the two approaches, precisely define the derived estimators of dynamic predictions and compare their performances notably in case of misspecification. The ultimate goal is to provide key elements for the use of individual dynamic predictions in clinical practice. Prediction of two competing causes of prostate cancer progression from the history of prostate-specific antigen is used as a motivated example. We formally define the quantity to estimate and its estimators, propose techniques to assess the uncertainty around predictions and validate them. We then conduct an in-depth simulation study compare the estimators in terms of prediction error, discriminatory power, efficiency and robustness to model assumptions. We show that prediction tools should be handled with care, in particular by properly specifying models and estimators.

Non-parametric estimation of transition probabilities in non-Markov multi-state models: The landmark Aalen-Johansen estimator.

The topic non-parametric estimation of transition probabilities in non-Markov multi-state models has seen a remarkable surge of activity recently. Two recent papers have used the idea of subsampling in this context. The first paper, by de Uña Álvarez and Meira-Machado, uses a procedure based on (differences between) Kaplan-Meier estimators derived from a subset of the data consisting of all subjects observed to be in the given state at the given time. The second, by Titman, derived estimators of transition probabilities that are consistent in general non-Markov multi-state models. Here, we show that the same idea of subsampling, used in both these papers, combined with the Aalen-Johansen estimate of the state occupation probabilities derived from that subset, can also be used to obtain a relatively simple and intuitive procedure which we term landmark Aalen-Johansen. We show that the landmark Aalen-Johansen estimator yields a consistent estimator of the transition probabilities in general non-Markov multi-state models under the same conditions as needed for consistency of the Aalen-Johansen estimator of the state occupation probabilities. Simulation studies show that the landmark Aalen-Johansen estimator has good small sample properties and is slightly more efficient than the other estimators.

E-Healthcare for Celiac Disease-A Multicenter Randomized Controlled Trial.

OBJECTIVE: To evaluate the (cost-)effectiveness of online consultations in follow-up of patients with celiac disease (CD). STUDY DESIGN: Multicenter randomized, controlled trial involving 304 patients aged ≤25 years with CD for ≥1 year, randomized to an online (n = 156) or outpatient consultation (n = 148). An online consultation included questionnaires for symptom and growth measurement. Antitransglutaminase-type-2 antibodies were determined using a point-of-care (POC) test. Controls had a traditional consultation with antitransglutaminase-type-2 antibodies testing in laboratories. Both groups completed questionnaires concerning CD-specific health-related quality of life (HRQOL), gluten-free diet adherence, and patient satisfaction. Six months later, participants repeated HRQOL and patient satisfaction questionnaires and the POC test. The primary outcome was anti-transglutaminase-type-2 antibodies after 6 months, and the secondary outcomes were health problems, dietary adherence, HRQOL, patient satisfaction, and costs. RESULTS: The performance of the POC test was inferior to laboratory testing (2/156 positive POC tests vs 13/148 positive laboratory tests; P = .003). Health problems were detected significantly more frequently using online consultation. The detection of growth problems and dietary transgressions was similar. HRQOL (from 1 [good] to 5 [poor]) improved after online consultation (from 3.25 to 3.16 [P = .013] vs controls from 3.10 to 3.23; P = .810). Patient satisfaction (from 1 [low] to 10 [high]) was 7.6 (online) vs 8.0 (controls; P = .001); 58% wished to continue online consultations. Mean costs per participant during the studied period were €202 less for the online group (P < .001). CONCLUSIONS: The primary outcome could not be tested because the POC test was unreliable. Nevertheless, our results indicate that online consultations for children and young adults with CD are cost saving, increase CD-specific HRQOL, and are satisfactory for the majority. TRIAL REGISTRATION: Trialregister.nl: NTR3688.

Assessment of dietary compliance in celiac children using a standardized dietary interview.

BACKGROUND & AIMS: Compliance to a gluten free diet (GFD) in celiac disease (CD) is ideally assessed by dietary interviews, albeit time-consuming. Short dietary questionnaires have been developed for adults but not for children. Primary aim was to compare GFD compliance in celiac children, measured by a short dietary questionnaire against a dietary interview. Secondary aims were correlation between both questionnaires and celiac antibodies and identifying variables predicting noncompliance. METHODS: Between 2012 and 2014, participants in the E-health CoelKids study, completed a short dietary questionnaire and standardized dietary interview together with measurement of anti-tissue transglutaminase antibodies (TG2A). Results of the questionnaires were assigned under similar categories. Factors possibly influencing dietary compliance were recorded. Where appropriate, Pearson's Chi-square test for trend, unpaired t-test, Cohen's kappa and one-way ANOVA were used. RESULTS: 151 of 165 participating patients were studied, 66% were female. Mean age was 11.3 years (2-26, SD 5.4), mean age at CD diagnosis was 4.9 years (1-23, SD 4.0). The short questionnaire and dietary interview correlated poorly, detecting problems in dietary adherence in 14% and 52% of the patients, respectively (Cohen's kappa 0.034). Only the short questionnaire correlated with TG2A (p = 0.003). Only older age was associated with noncompliance, the mean age of completely nonadherent, adherent but committing errors, and strictly adherent patients were 15.5, 11.5 and 10.1 years, respectively (p < 0.001). CONCLUSIONS: Compared to the dietary interview, short dietary questionnaires and TG2A serology failed to detect dietary transgressions in CD children, wherein adolescents were shown to be at highest risk.

Comparison of Patients' and Doctors' Reports on Health-related Quality of Life in Celiac Disease.

OBJECTIVE: To investigate whether implementation of a celiac disease (CD)-specific health-related quality of life (HRQOL) questionnaire would add value to CD follow-up visits; we compared patients' self-reported CD-specific HRQOL with the physician's report provided during a regular CD follow-up visit in children and young adults. METHODS: A cross-sectional study in the control group of a study on self-management in CD (CoelKids). Eligible patients had CD for ≥1 year and were 25 years or younger. They completed a CD-specific HRQOL questionnaire (CDDUX) after their regular follow-up visit. Their physicians were unaware of the present study's objectives or self-reported HRQOL. PRIMARY OUTCOME: agreement between physician-reported and self-reported HRQOL. SECONDARY OUTCOMES: patient variables predicting a discrepancy between reports, or a lower HRQOL. RESULTS: Physician-reported HRQOL was available in 70 of 78 enrolled patients. The self-reported and physician-reported HRQOL were concordant in 30 of 70 (K = 0.093), 6 of them had a poor self-reported HRQOL. Reports were discrepant in 40 of 70; all 40 self-reported a poor HRQOL. Discrepancies occurred more frequently in patients with a disease duration <9 years (32/40 with discrepant reports were diagnosed <9 years ago vs 17/30 with no discrepancy, P<0.001) and in females (35/40 with discrepant reports were girls versus 16 of 30 with no discrepancy, P = 0.001). Both factors were predictors of a poorer HRQOL. CONCLUSIONS: During regular CD follow-up visits, physicians did not report a poor HRQOL in 40 of 46 children and young adults with a poor self-reported HRQOL. This is consistent with previous studies examining other chronic diseases and supports the implementation of self-reported CD-specific HRQOL measurements in CD follow-up visits.

Improved Risk Assessment by Integrating Molecular and Clinicopathological Factors in Early-stage Endometrial Cancer-Combined Analysis of the PORTEC Cohorts.

PURPOSE: Recommendations for adjuvant treatment for women with early-stage endometrial carcinoma are based on clinicopathologic features. Comprehensive genomic characterization defined four subgroups: p53-mutant, microsatellite instability (MSI), POLE-mutant, and no specific molecular profile (NSMP). We aimed to confirm the prognostic capacity of these subgroups in large randomized trial populations, investigate potential other prognostic classifiers, and integrate these into an integrated molecular risk assessment guiding adjuvant therapy. EXPERIMENTAL DESIGN: Analysis of MSI, hotspot mutations in 14 genes including POLE, protein expression of p53, ARID1a, ß-catenin, L1CAM, PTEN, ER, and PR was undertaken on 947 available early-stage endometrioid endometrial carcinomas from the PORTEC-1 and -2 trials, mostly high-intermediate risk (n = 614). Prognostic value was determined using univariable and multivariable Cox proportional hazard models. AUCs of different risk stratification models were compared. RESULTS: Molecular analyses were feasible in >96% of the patients and confirmed the four molecular subgroups: p53-mutant (9%), MSI (26%), POLE-mutant (6%), and NSMP (59%). Integration of prognostic molecular alterations with established clinicopathologic factors resulted in a stronger model with improved risk prognostication. Approximately 15% of high-intermediate risk patients had unfavorable features (substantial lymphovascular space invasion, p53-mutant, and/or >10% L1CAM), 50% favorable features (POLE-mutant, NSMP being microsatellite stable, and CTNNB1 wild-type), and 35% intermediate features (MSI or CTNNB1-mutant). CONCLUSIONS: Integrating clinicopathologic and molecular factors improves the risk assessment of patients with early-stage endometrial carcinoma. Assessment of this integrated risk profile is feasible in daily practice, and holds promise to reduce both overtreatment and undertreatment. Clin Cancer Res; 22(16); 4215-24. ©2016 AACR.

Years of life lost due to lower extremity injury in association with dementia, and care need: a 6-year follow-up population-based study using a multi-state approach among German elderly.

BACKGROUND: Dementia and care need are challenging aging populations worldwide. Lower extremity injury (LEI) in the elderly makes matters worse. Using a multi-state approach, we express the effect of LEI on dementia, care need, and mortality in terms of remaining life expectancy at age 75 (rLE) and years of life lost (YLL). METHODS: A population-based random sample of beneficiaries aged 75-95 years was drawn from the largest public health insurer in Germany in 2004 and followed until 2010 (N 62,103; Mean Age ± SD 81.5 ± 4.8 years; Female 71.2%). We defined a five-state model (Healthy, Dementia, Care, Dementia & Care, Dead), and calculated transition-specific hazard ratios of LEI using Cox regression. The transition probabilities as well as the YLL due to LEI were estimated. RESULTS: LEI significantly increased the risk for each transition, with a maximum risk for the transition from Healthy to Care (HR: 1.70, 95% CI: 1.63-1.77) and a minimum risk for the transition from Care to Dead (HR: 1.16, 95% CI: 1.10-1.22). If the elderly had LEI-history, their age-specific mortality was generally higher and their probabilities of transient states peaked at younger ages. At age 75, initially dementia-free and care-independent elderly experiencing LEI lost about 2 years of life, of which more than 90% were life years free of dementia or care need. Dementia patients lost about one and a half year, more than 60% were free of long-term care need. CONCLUSIONS: LEI not only casts a large health burden on care need, but is also associated with cognitive decline and shortened rLE. LEI plus dementia extend the relative life time in need of care, despite generally shortening rLE. Using the composite measure YLL may help to better convey these results to the elderly, families, and health professionals. This may strengthen preventive measures as well as improve timely and rehabilitative treatment of LEI, not only in cognitive and physically intact elderly.