Measure Of Concordance Research Articles

Efficient and Accurate Evaluation Methods for Concordance Measures via Functional Tensor Characterizations of Copulas

There is now an increasingly large number of proposed concordance measures available to capture, measure and quantify different notions of dependence in stochastic processes. However, evaluation of concordance measures to quantify such types of dependence for different copula models can be challenging. In this work, we propose a class of new methods that involves a highly accurate and computationally efficient procedure to evaluate concordance measures for a given copula, applicable even when sampling from the copula is not easily achieved. In addition, this then allows us to reconstruct maps of concordance measures locally in all regions of the state space for any range of copula parameters. We believe this technique will be a valuable tool for practitioners to understand better the behaviour of copula models and associated concordance measures expressed in terms of these copula models.

Localization value of subclinical seizures on scalp video-EEG in epilepsy presurgical evaluation.

To evaluate the localization value and prognostic significance of subclinical seizures (SCSs) on scalp video-electroencephalography monitoring (VEEG) in comparison to clinical seizures (CSs) in patients who had epilepsy surgery. We included 123 consecutive patients who had SCSs and CSs during scalp-VEEG evaluation. All patients had subsequent epilepsy surgery and at least 1-year follow-up. Concordance between SCSs and CSs was summarized into five categories: complete, partial, overlapping, no concordance, or indeterminate. Using the same scheme, we analyzed the relationship between resection and SCS/CS localizations. The concordance measures, along with demographic, electroclinical, and other presurgical evaluation data, were evaluated for their associations with postoperative seizure outcome. Sixty-nine patients (56.1%) had seizure-free outcome at 1-year follow-up. In 68 patients (55.3%), the localizations of SCSs and CSs were completely concordant. Multivariate logistic analysis showed that complete SCS/CS concordance was independently associated with seizure-free outcome at 1-year (P=.020) and 2-year follow-up (P=.040). In the temporal lobe epilepsy (TLE) seizure-free group, SCS localization was completelycontained within the resection in 44.4% andCS localization was completelycontained within the resection in41.7%; in the extratemporal lobe epilepsy (ETLE) seizure-free group, SCS localization was completelycontained within the resection in 54.5%and CS localization was completely contained within the resection in57.6%. Complete concordance between CS and SCS localization is a positive prognostic factor for 1-year and 2-year postoperative seizure-free outcome. Localization value of SCSs on scalp VEEG is similar to that of CSs for TLE and ETLE. Although SCSs cannot replace CSs, localization information from SCSs should not be ignored.

Gene expression based survival prediction for cancer patients-A topic modeling approach.

Cancer is one of the leading cause of death, worldwide. Many believe that genomic data will enable us to better predict the survival time of these patients, which will lead to better, more personalized treatment options and patient care. As standard survival prediction models have a hard time coping with the high-dimensionality of such gene expression data, many projects use some dimensionality reduction techniques to overcome this hurdle. We introduce a novel methodology, inspired by topic modeling from the natural language domain, to derive expressive features from the high-dimensional gene expression data. There, a document is represented as a mixture over a relatively small number of topics, where each topic corresponds to a distribution over the words; here, to accommodate the heterogeneity of a patient’s cancer, we represent each patient (≈ document) as a mixture over cancer-topics, where each cancer-topic is a mixture over gene expression values (≈ words). This required some extensions to the standard LDA model—e.g., to accommodate the real-valued expression values—leading to our novel discretized Latent Dirichlet Allocation (dLDA) procedure. After using this dLDA to learn these cancer-topics, we can then express each patient as a distribution over a small number of cancer-topics, then use this low-dimensional “distribution vector” as input to a learning algorithm—here, we ran the recent survival prediction algorithm, MTLR, on this representation of the cancer dataset. We initially focus on the METABRIC dataset, which describes each of n = 1,981 breast cancer patients using the r = 49,576 gene expression values, from microarrays. Our results show that our approach (dLDA followed by MTLR) provides survival estimates that are more accurate than standard models, in terms of the standard Concordance measure. We then validate this “dLDA+MTLR” approach by running it on the n = 883 Pan-kidney (KIPAN) dataset, over r = 15,529 gene expression values—here using the mRNAseq modality—and find that it again achieves excellent results. In both cases, we also show that the resulting model is calibrated, using the recent “D-calibrated” measure. These successes, in two different cancer types and expression modalities, demonstrates the generality, and the effectiveness, of this approach. The dLDA+MTLR source code is available at https://github.com/nitsanluke/GE-LDA-Survival.

Distinct Montages of Slow Oscillatory Transcranial Direct Current Stimulation (so-tDCS) Constitute Different Mechanisms during Quiet Wakefulness.

Slow oscillatory- (so-) tDCS has been applied in many sleep studies aimed to modulate brain rhythms of slow wave sleep and memory consolidation. Yet, so-tDCS may also modify coupled oscillatory networks. Efficacy of weak electric brain stimulation is however variable and dependent upon the brain state at the time of stimulation (subject and/or task-related) as well as on stimulation parameters (e.g., electrode placement and applied current. Anodal so-tDCS was applied during wakefulness with eyes-closed to examine efficacy when deviating from the dominant brain rhythm. Additionally, montages of different electrodes size and applied current strength were used. During a period of quiet wakefulness bilateral frontolateral stimulation (F3, F4; return electrodes at ipsilateral mastoids) was applied to two groups: ‘Group small’ (n = 16, f:8; small electrodes: 0.50 cm2; maximal current per electrode pair: 0.26 mA) and ‘Group Large’ (n = 16, f:8; 35 cm2; 0.35 mA). Anodal so-tDCS (0.75 Hz) was applied in five blocks of 5 min epochs with 1 min stimulation-free epochs between the blocks. A finger sequence tapping task (FSTT) was used to induce comparable cortical activity across sessions and subject groups. So-tDCS resulted in a suppression of alpha power over the parietal cortex. Interestingly, in Group Small alpha suppression occurred over the standard band (8–12 Hz), whereas for Group Large power of individual alpha frequency was suppressed. Group Small also revealed a decrease in FSTT performance at retest after stimulation. It is essential to include concordant measures of behavioral and brain activity to help understand variability and poor reproducibility in oscillatory-tDCS studies.

Quantifying Donor Effects on Transplant Outcomes Using Kidney Pairs from Deceased Donors.

In kidney transplantation, the relative contribution of donor versus other factors on clinical outcomes is unknown. We sought to quantify overall donor effects on transplant outcomes for kidney donations from deceased donors. For paired donations from deceased donors resulting in transplants to different recipients, the magnitude of donor effects can be quantified by examining the excess of concordant outcomes within kidney pairs beyond chance concordance. Using data from the Organ Procurement and Transplantation Network between the years 2013 and 2017, we examined concordance measures for delayed graft function, death-censored 1-year graft failure, and death-censored 3-year graft failure. The concordance measures were excess relative risk, excess absolute risk, and the fixation index (where zero is no concordance and one is perfect concordance). We further examined concordance in strata of kidneys with similar values of the Kidney Donor Profile Index, a common metric of organ quality. If the transplant of the kidney mate resulted in delayed graft function, risk for delayed graft function was 19% higher (95% confidence interval [95% CI], 18% to 20%), or 1.76-fold higher (95% CI, 1.73- to 1.80-fold), than baseline. If a kidney graft failed within 1 year, then the kidney mate's risk of failure was 6% higher (95% CI, 4% to 9%), or 2.85-fold higher (95% CI, 2.25- to 3.48-fold), than baseline. For 3-year graft failure, the excess absolute risk was 7% (95% CI, 4% to 10%) but excess relative risk was smaller, 1.91-fold (95% CI, 1.56- to 2.28-fold). Fixation indices were 0.25 for delayed graft function (95% CI, 0.24 to 0.27), 0.07 for 1-year graft failure (95% CI, 0.04 to 0.09), and 0.07 for 3-year graft failure (95% CI, 0.04 to 0.10). Results were similar in strata of kidneys with a similar Kidney Donor Profile Index. Overall results indicated that the donor constitution has small or moderate effect on post-transplant clinical outcomes.

Can the American College of Surgeons Risk Calculator Predict 30-Day Complications After Cervical Spine Surgery?

This was a retrospective cohort study. The objective of this study was to assess the American College of Surgeons (ACS) Risk Calculator's ability to accurately predict complications after cervical spine surgery. Surgical risk calculators exist in many fields and may assist in the identification of patients at increased risk for complications and readmissions. Risk calculators may allow for improved outcomes, an enhanced informed consent process, and management of modifiable risk factors. The American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Risk Calculator was developed from a cohort of over 1.4 million patients, using 2805 unique Current Procedural Terminology (CPT) codes. The risk calculator uses 21 patient predictors (eg, age, American Society of Anesthesiologists class, body mass index, hypertension) and the planned procedure (CPT code) to predict the chance that patients will have any of 12 different outcomes (eg, death, any complication, serious complication, reoperation) within 30 days following surgery. The purpose of this study is to determine if the ACS NISQIP risk calculator can predict 30-day complications after cervical fusion. A retrospective chart review was performed on patients that underwent primary cervical fusions between January 2009 and 2015 at a single institution, utilizing cervical fusion CPT codes. Patients without 30 days of postoperative follow-up were excluded. Descriptive statistics were calculated for the overall sample, anterior versus posterior fusion, and single versus multilevel fusion. Logistic regression models were fit with actual complication occurrence as the dependent variable in each model and ACS estimated risk as the independent variable. The c-statistic was used as the measure of concordance for each model. Receiver operating characteristic curves were plotted to visually depict the predictive ability of the estimated risks. Acceptable concordance was set at c>0.80. All analyses were conducted using SAS, v9.4. A total of 404 patients met the inclusion criteria for this study. Age, body mass index, sex, and a number of levels of fusion were gathered as input data the ACS NSQIP Risk Calculator. Results of Risk Calculator were compared with observed complication rates. Descriptive statistics of the Risk Calculator risk estimates showed a significant prediction of "any complication" and "discharge to skilled nursing facility" among the cohort. Because there were no deaths or urinary tract infections, no models were fit for these outcomes. The ACS Risk Calculator accurately predicted complications in the categories of "any complication" (P<0.0001) and "discharge to the skilled nursing facility" (P<0.001) for our cohort. We conclude that the ACS Risk Calculator was unable to accurately predict specific complications on a more granular basis for the patients of this study. Although the ACS risk calculator may be useful in the field of general surgery and in the development of new institutional strategies for risk mitigation, our findings demonstrate that it does not necessarily provide accurate information for patients undergoing cervical spinal surgery.

Agreement between molecular subtyping and surrogate subtype classification: a contemporary population-based study of ER-positive/HER2-negative primary breast cancer

PurposeOestrogen receptor-positive (ER+) and human epidermal receptor 2-negative (HER2–) breast cancers are classified as Luminal A or B based on gene expression, but immunohistochemical markers are used for surrogate subtyping. The aims of this study were to examine the agreement between molecular subtyping (MS) and surrogate subtyping and to identify subgroups consisting mainly of Luminal A or B tumours.MethodsThe cohort consisted of 2063 patients diagnosed between 2013–2017, with primary ER+/HER2– breast cancer, analysed by RNA sequencing. Surrogate subtyping was performed according to three algorithms (St. Gallen 2013, Maisonneuve and our proposed Grade-based classification). Agreement (%) and kappa statistics (κ) were used as concordance measures and ROC analysis for luminal distinction. Ki67, progesterone receptor (PR) and histological grade (HG) were further investigated as surrogate markers.ResultsThe agreement rates between the MS and St. Gallen 2013, Maisonneuve and Grade-based classifications were 62% (κ = 0.30), 66% (κ = 0.35) and 70% (κ = 0.41), respectively. PR did not contribute to distinguishing Luminal A from B tumours (auROC = 0.56). By classifying HG1-2 tumours as Luminal A-like and HG3 as Luminal B-like, agreement with MS was 80% (κ = 0.46). Moreover, by combining HG and Ki67 status, a large subgroup of patients (51% of the cohort) having > 90% Luminal A tumours could be identified.ConclusionsAgreement between MS and surrogate classifications was generally poor. However, a post hoc analysis showed that a combination of HG and Ki67 could identify patients very likely to have Luminal A tumours according to MS.

An instrument for quality assurance in work capacity evaluation: development, evaluation, and inter-rater reliability

BackgroundEmployees insured in pension insurance, who are incapable of working due to ill health, are entitled to a disability pension. To assess whether an individual meets the medical requirements to be considered as disabled, a work capacity evaluation is conducted. However, there are no official guidelines on how to perform an external quality assurance for this evaluation process. Furthermore, the quality of medical reports in the field of insurance medicine can vary substantially, and systematic evaluations are scarce. Reliability studies using peer review have repeatedly shown insufficient ability to distinguish between high, moderate and low quality. Considering literature recommendations, we developed an instrument to examine the quality of medical experts’ reports.MethodsThe peer review manual developed contains six quality domains (formal structure, clarity, transparency, completeness, medical-scientific principles, and efficiency) comprising 22 items. In addition, a superordinate criterion (survey confirmability) rank the overall quality and usefulness of a report. This criterion evaluates problems of inner logic and reasoning. Development of the manual was assisted by experienced physicians in a pre-test. We examined the observable variance in peer judgements and reliability as the most important outcome criteria. To evaluate inter-rater reliability, 20 anonymous experts’ reports detailing the work capacity evaluation were reviewed by 19 trained raters (peers). Percentage agreement and Kendall’s W, a reliability measure of concordance between two or more peers, were calculated. A total of 325 reviews were conducted.ResultsAgreement of peer judgements with respect to the superordinate criterion ranged from 29.2 to 87.5%. Kendall’s W for the quality domain items varied greatly, ranging from 0.09 to 0.88. With respect to the superordinate criterion, Kendall’s W was 0.39, which indicates fair agreement. The results of the percentage agreement revealed systemic peer preferences for certain deficit scale categories.ConclusionThe superordinate criterion was not sufficiently reliable. However, in comparison to other reliability studies, this criterion showed an equivalent reliability value. This report aims to encourage further efforts to improve evaluation instruments. To reduce disagreement between peer judgments, we propose the revision of the peer review instrument and the development and implementation of a standardized rater training to improve reliability.

Review and evaluation of the concordance measures for assessing discrimination in the logistic regression methods

Concordance statistic (C-statistic), which is equivalent to the area under a receiver operating characteristic curve (AUC), is frequently used to quantify the discriminatory power (the ability of the model to distinguish low and high risk patient) of a risk prediction model developed in the logistic regression framework. Several methods for estimating concordance statistics including both non-parametric and parametric have been proposed in the literature. Despite the several proposals of the C-statistic, it is still unclear to the practical users which approaches should be applied in practice. This paper reviewed and evaluated some commonly used C-statistics by illustrating them using two datasets with different prognostic abilities and an extensive simulation study and compared their results to make some practical recommendations. Several simulation scenarios were considered by varying the sample size, prevalence of the binary outcome, and distribution of prognostic index (or log-odds) derived from the model, to mimic the scenarios in practice. The results revealed that both non-parametric and Kernel-smoothing based methods showed comparable results in most simulation scenarios but performed better than the parametric approach particularly for small sample situation and skewed distribution of the prognostic index. Based on the findings of the study, some practical recommendations are discussed.

Duration of military service is associated with decision quality in Veterans considering total knee replacement: case series.

PurposeDue to the nature of military service, the patient–physician relationship in Veterans is unlike that seen in civilian life. The structure of the military is hypothesized to result in barriers to open patient–physician communication and patient participation in elective care decision-making. Decision quality is a measure of concordance between a chosen treatment and the aspects of medical care that matter most to an informed patient; high decision quality is synonymous with patient-centered care. While past research has examined how age and other demographic factors affect decision quality in Veterans, duration of military service, rank at discharge, and years since discharge have not been studied.Patients and methodsWe enrolled 25 Veterans with knee osteoarthritis at a VA hospital. Enrollees completed a survey with demographic, military service, and decision-making preference questions and the Hip-Knee Decision Quality Instrument (HK-DQI), which measures patients’ knowledge about their disease process, concordance of their treatment decision, and the considered elements in their decision-making process.ResultsThe HK-DQI knowledge score had a significant, positive correlation with duration of military service (R2=0.36, p=0.004). Rank at discharge and years since discharge did not show a significant correlation with decision quality (p=0.500 and p=0.317, respectively). The concordance score did not show a statistically significant correlation with rank, duration of service, and years since discharge (p=0.640, p=0.486 and p=0.795, respectively). Additionally, decision process score was not significantly associated with rank, duration of military service, and years since discharge (p=0.380, p=0.885, and p=0.474, respectively).ConclusionDecision quality in Veterans considering treatment for knee osteoarthritis appears to be correlated positively with duration of military service. These findings may present an opportunity for identification of Veterans at most risk of low decision quality and customization of shared decision-making methods for Veterans by characteristics of military service.

Potential use of transrenal DNA for non-invasive monitoring and prognosis of colorectal cancer

Background: Anti-EGFR mAb are recommended treatment for metastatic colorectal cancer (mCRC). Accurate mutation profiling and disease monitoring are challenging. The current study investigates the potential use of transrenal DNA as a biomarker for disease management.Methods: Agreement between archival tissue specimens and transrenal DNA extracted from 200 post-treated mCRC patients was determined. Total DNA concentrations were measured and mutations within the KRAS and EGFR genes were profiled for each specimen. To ascertain therapy resistance; patients were serially monitored monthly.Results: Concordance measurement with matched tissues at baseline was remarkably high (92%) for EGFR and KRAS mutations. Sensitivity and specificity were 98.4% and 89.1% respectively. Newly detectable mutations for a subgroup of patients with initial wildtype characteristics were evident after 4 months of anti-EGFR mAb therapy. Survival analysis using adjusted estimates showed that patients detected by transrenal DNA for key mutations or had higher mutant DNA content had poorer outcome.Conclusion: Transrenal DNA offers new options to follow clinical treatment in mCRC. It demonstrates the ability to capture newly acquired mutations that has strong associative links to therapy resistance. Patients with these mutations fared poorly for survival outcomes and indicated possible prognostic value for transrenal DNA detection.

Missed psychosocial risk factors during routine preoperative evaluations are associated with increased complications after elective cancer surgery

BackgroundCertain behavioral traits and inadequate social support are known risk factors for complications after cancer surgery. Despite their importance, it is unclear whether conventional patient preoperative evaluation captures them. This study was conducted to assess concordance between documentation and patient survey of selected risk factors and to determine whether failure to document affected postoperative outcomes. MethodsAdult patients at a tertiary academic medical center were surveyed before abdominal cancer surgery to assess 6 psychosocial risk factors. Risk factors were also assessed by retrospective chart review and compared with survey results through concordance measures. Thirty-day postoperative complications were abstracted by chart review. Rates of major complications for those with and without clinically missed risk factors were compared. ResultsComparisons between chart review and screening survey revealed poor-to-moderate positive agreement (0%–47%) for 5 risk factors and strong negative agreement (82%–99%) among all risk factors. Kappa analysis demonstrated poor-to-fair agreement among 5 risk factors (κ = 0.112–0.423). The overall complication rate was 36%. The complication rate for patients with at least 1 clinically missed risk factor was 49% vs 24% in those without (P = .021), with a similar effect replicated for each individual risk factor. ConclusionThis study shows a high level of discordance between formal screening and routine clinician documentation in a preoperative setting for psychosocial risk factors. There is a significant association between missing these risk factors and worse postoperative outcomes. Future work should examine whether structured screening of psychosocial risk factors may improve preoperative risk stratification through proactive interventions.

COMPATIBILITY AND ATTAINABILITY OF MATRICES OF CORRELATION-BASED MEASURES OF CONCORDANCE

AbstractMeasures of concordance have been widely used in insurance and risk management to summarize nonlinear dependence among risks modeled by random variables, which Pearson’s correlation coefficient cannot capture. However, popular measures of concordance, such as Spearman’s rho and Blomqvist’s beta, appear as classical correlations of transformed random variables. We characterize a whole class of such concordance measures arising from correlations of transformed random variables, which includes Spearman’s rho, Blomqvist’s beta and van der Waerden’s coefficient as special cases. Compatibility and attainability of square matrices with entries given by such measures are studied—that is, whether a given square matrix of such measures of concordance can be realized for some random vector and how such a random vector can be constructed. Compatibility and attainability of block matrices and hierarchical matrices are also studied due to their practical importance in insurance and risk management. In particular, a subclass of attainable block Spearman’s rho matrices is proposed to compensate for the drawback that Spearman’s rho matrices are in general not attainable for dimensions larger than three. Another result concerns a novel analytical form of the Cholesky factor of block matrices which allows one, for example, to construct random vectors with given block matrices of van der Waerden’s coefficient.

Improving Peptide-Spectrum Matching by Fragmentation Prediction Using Hidden Markov Models.

Tandem mass spectrometry has become the method of choice for high-throughput, quantitative analysis in proteomics. Peptide spectrum matching algorithms score the concordance between the experimental and the theoretical spectra of candidate peptides by evaluating the number (or proportion) of theoretically possible fragment ions observed in the experimental spectra without any discrimination. However, the assumption that each theoretical fragment is just as likely to be observed is inaccurate. On the contrary, MS2 spectra often have few dominant fragments. Using millions of MS/MS spectra we show that there is high reproducibility across different fragmentation spectra given the precursor peptide and charge state, implying that there is a pattern to fragmentation. To capture this pattern we propose a novel prediction algorithm based on hidden Markov models with an efficient training process. We investigated the performance of our interpolated-HMM model, trained on millions of MS2 spectra, and found that our model picks up meaningful patterns in peptide fragmentation. Second, looking at the variability of the prediction performance by varying the train/test data split, we observed that our model performs well independent of the specific peptides that are present in the training data. Furthermore, we propose that the real value of this model is as a preprocessing step in the peptide identification process. The model can discern fragment ions that are unlikely to be intense for a given candidate peptide rather than using the actual predicted intensities. As such, probabilistic measures of concordance between experimental and theoretical spectra will leverage better statistics.

A flexible and robust method for assessing conditional association and conditional concordance.

When analyzing bivariate outcome data, it is often of scientific interest to measure and estimate the association between the bivariate outcomes. In the presence of influential covariates for one or both of the outcomes, conditional association measures can quantify the strength of association without the disturbance of the marginal covariate effects, to provide cleaner and less-confounded insights into the bivariate association. In this work, we propose estimation and inferential procedures for assessing the conditional Kendall's tau coefficient given the covariates, by adopting the quantile regression and quantile copula framework to handle marginal covariate effects. The proposed method can flexibly accommodate right censoring and be readily applied to bivariate survival data. It also facilitates an estimator of the conditional concordance measure, namely, a conditional index, where the unconditional index is commonly used to assess the predictive capacity for survival outcomes. The proposed method is flexible and robust and can be easily implemented using standard software. The method performed satisfactorily in extensive simulation studies with and without censoring. Application of our methods to two real-life data examples demonstrates their desirable practical utility.

Exact Confidence Limits on Some New Measures of Concordance and Discordance in Binary Outcomes

Using a measure of agreement that does not distinguish the "positive" outcome from the "negative" outcome can be sometimes misleading in assessing resemblance. To alleviate this concern, some new indices, including the "positive" and "negative" conditional synchrony measures (CSM) (or the conditional discordant measures [CDM]), as well as their related measures, have been recently proposed elsewhere. We show that one can easily derive exact confidence limits for these new indices. Using Monte Carlo simulation, we find that the asymptotic interval estimator derived from the score test and these exact interval estimators can all perform well in a variety of situations, while the asymptotic interval estimator based on Wald's statistic can lose accuracy. We use the data taken from a cross-sectional validation study assessing the diagnostic performance of the Whooley questions for major depression disorder (MDD) among older adults to illustrate the use of these interval estimators developed here.

Lifetime Occurrence of Brain Metastases Arising from Lung, Breast, and Skin Cancers in the Elderly: A SEER-Medicare Study.

The Surveillance, Epidemiology, and End Results (SEER) Program recently released data on brain metastases (BM) diagnosed during primary cancer staging workup ("synchronous" BM, or SBM); this study examines the incidence of SBM compared with that of lifetime BM (LBM) identified using Medicare claims for patients diagnosed with lung cancer, breast cancer, or melanoma. Incidence proportions (IP) and age-adjusted rates for each of SEER SBM and Medicare LBM are presented along with measures of concordance between the two sources of data, where Medicare LBM were defined by several combinations of diagnosis and putative diagnostic imaging procedure codes. The SBM IP in lung, breast, and melanoma cancers were 9.6%, 0.3%, and 1.1%, respectively; the corresponding LBM IP were 13.5%, 1.8%, and 3.6%. The greatest SBM IP among patients with lung cancer was 13.4% for non-small cell lung cancer, and among patients with breast cancer was 0.7% for triple-negative breast cancer. The greatest LBM IP among lung cancers was 23.1% in small-cell lung cancer, and among breast cancers was 4.2% for cases of the triple negative subtype. Using a large dataset that is representative of the elderly population in the United States, these analyses estimate synchronous and lifetime incidence of BM in lung cancers, breast cancers, and melanomas. These and other population-based estimates may be used to guide development of BM screening policy and evaluation of real-world data sources.

Correlation and concordance measures between clinical, endoscopic and histological scores activity in Crohn’s disease under treatment

Aim: Our aim was to evaluate the correlation and concordance measures between clinical, endoscopic and histologic remission in Crohn’s disease (CD) under treatment.Method: Twenty-four patients with CD under treatment were included in a prospective consecutive cross-sectional study from January to September 2018. Clinical activity was assessed by Crohn’s Disease Activity Index (CDAI). All of the patients were submitted an ileocolonoscopy with biopsy and classified by Simple Endoscopic Score (SES-CD). Histologic activity was assessed by Global Histologic Activity Score (GHAS) modified. Remission was considered with CDAI <150; SES-CD ≤2 and GHAS ≤4.Results: Clinical remission was established in 53%, however, only 50% had mucosal healing (MH) and 70% had inflammatory histologic activity. Correlation between endoscopic and histological measures was strong and positive (σ = 0.73, p < .0003). The concordance remission agreement between SES-CD and GHAS was weak with (κ) = 0.3 (IC 95%: −0.09; 0.69). The greatest disparity arose when clinical activity (CDAI) was compared with histological measures (σ = 0.20, p = .45), (κ) = 0.26 (IC = −0.03; 0.56).Conclusion: The score SES-CD correlates well with histological score GHAS in CD under treatment, however, there is low concordance between both mainly in patients with anti-TNFs treatment. CDAI score had low correlation and concordance with histological score GHAS. In this sample, patients under treatment and without symptoms had low MH and histologic healing.

PERFORMANCE INDICATORS FOR ENERGY EFFICIENCY RETROFITTING IN MULTIFAMILY RESIDENTIAL BUILDINGS

ABSTRACT The energy performance of an existing building is the amount of energy consumed to meet various needs associated with the standardized use of a building and is reflected in one or more indicators known as Building Energy Performance Indicators (EnPIs). These indicators are distributed amongst six main factors influencing energy consumption: climate, building envelope, building services and energy systems, building operation and maintenance, occupants' activities and behaviour, and indoor environmental quality. Any improvement made to either the existing structure or the physical and operational upgrade of a building system that enhances energy performance is considered an energy efficiency retrofit. The main goal of this research is to support the implementation of multifamily residential building energy retrofits through expert knowledge consensus on EnPIs for energy efficiency retrofit planning. The research methodology consists of a comprehensive literature review which has identified 35 EnPIs for assessing performance of existing residential buildings, followed by a ranking questionnaire survey of experts in the built-environment to arrive at a priority listing of indicators based on mean rank. This was followed by concordance analysis and measure of standard deviation. A total of 280 experts were contacted globally for the survey, and 106 completed responses were received resulting in a 37.85% response rate. The respondents were divided into two groups for analysis: academician/researchers and industry practitioners. The primary outcome of the research is a priority listing of EnPIs based on the quantitative data from the knowledge-base of experts from these two groups. It is the outcome of their perceptions of retrofitting factors and corresponding indicators. A retrofit strategy consists of five phases for retrofitting planning in which the second phase comprises an energy audit and performance assessment and diagnostics. This research substantiates the performance assessment process through the identification of EnPIs.

Effectiveness of a decision aid for promoting colorectal cancer screening in Spain: a randomized trial

BackgroundColorectal cancer (CRC) screening has shown to reduce incidence and mortality rates, and therefore is widely recommended for people above 50 years-old. However, despite the implementation of population-based screening programs in several countries, uptake rates are still low. Decision aids (DAs) may help patients to make informed decisions about CRC screening.MethodsWe performed a randomized controlled trial to assess the effectiveness of a DA developed to promote CRC screening, with patients from two primary care centers in Spain who never had underwent CRC screening. Contrary to center B (n = 24), Center A (n = 83) attended patients from an area where the population-based screening program was not implemented at that moment. Outcome measures were decisional conflict, knowledge of the disease and available screening options, intention to uptake the test, and concordance between patients’ goals/concerns and intention.ResultsIn center A, there were significant differences favoring the DA in decisional conflict (p < 0.001) and knowledge (p < 0.001). The absolute differences favoring DA group in intention to undergo fecal occult blood test (10.5%) and colonoscopy (13.7%) were significant only before correction for attenuation. In center B the differences were significant only for knowledge (p < 0.001). Patients’ goals and concerns regarding the screening did not significantly predict their intention, and therefore we could not calculate a measure of concordance between the two constructs.ConclusionsA DA improved the decisional process of participants who had never been invited to participate in the Spanish public CRC screening program, replicating previous results in this field. Future research is needed to identify subgroups that could benefit more from these interventions.Trial registrationInternational Standard Registered Clinical/social Study Number: ISRCTN98108615 (Retrospectively registered on 27 December 2018).