Clinical Risk Estimation Research Articles

Clinical risk stratification: Development and validation of the DAAE score, a tool for estimating patient risk of transition to secondary progressive multiple sclerosis

BackgroundBecause secondary progressive multiple sclerosis (SPMS) is associated with worse prognosis, early predictive tools are needed. We aimed to use systematic literature review and advanced methods to create and validate a clinical tool for estimating individual patient risk of transition to SPMS over five years. MethodsData from the Jacobs Multiple Sclerosis Center (JMSC) and the Multiple Sclerosis Center Amsterdam (MSCA) was collected between 1994 and 2022. Participants were relapsing-remitting adult patients at initial evaluation. We created the tool in four stages: (1) identification of candidate predictors from systematic literature review, (2) ordinal cutoff determination, (3) feature selection, (4) feature weighting. ResultsPatients in the development/internal-validation/external-validation datasets respectively (n = 787/n = 522/n = 877) had a median age of 44.1/42.4/36.6 and disease duration of 7.7/6.2/4.4 years. From these, 12.6 %/10.2 %/15.4 % converted to SPMS (median=4.9/5.2/5.0 years). The DAAE Score was named from included predictors: Disease duration, Age at disease onset, Age, EDSS. It ranges from 0 to 12 points, with risk groups of very-low=0–2, low=3–7, medium=8–9, and high≥10. Risk of transition to SPMS increased proportionally across these groups in development (2.7 %/7.4 %/18.8 %/40.2 %), internal-validation (2.9 %/6.8 %/26.8 %/36.5 %), and external-validation (7.5 %/9.6 %/22.4 %/37.5 %). ConclusionThe DAAE Score estimates individual patient risk of transition to SPMS consistently across datasets internationally using clinically-accessible data. With further validation, this tool could be used for clinical risk estimation.

Artificial intelligence-based image analysis in clinical testing: lessons from cervical cancer screening.

Novel screening and diagnostic tests based on artificial intelligence (AI) image recognition algorithms are proliferating. Some initial reports claim outstanding accuracy followed by disappointing lack of confirmation, including our own early work on cervical screening. This is a presentation of lessons learned, organized as a conceptual step-by-step approach to bridge the gap between the creation of an AI algorithm and clinical efficacy. The first fundamental principle is specifying rigorously what the algorithm is designed to identify and what the test is intended to measure (eg, screening, diagnostic, or prognostic). Second, designing the AI algorithm to minimize the most clinically important errors. For example, many equivocal cervical images cannot yet be labeled because the borderline between cases and controls is blurred. To avoid a misclassified case-control dichotomy, we have isolated the equivocal cases and formally included an intermediate, indeterminate class (severity order of classes: case>indeterminate>control). The third principle is evaluating AI algorithms like any other test, using clinical epidemiologic criteria. Repeatability of the algorithm at the borderline, for indeterminate images, has proven extremely informative. Distinguishing between internal and external validation is also essential. Linking the AI algorithm results to clinical risk estimation is the fourth principle. Absolute risk (not relative) is the critical metric for translating a test result into clinical use. Finally, generating risk-based guidelines for clinical use that match local resources and priorities is the last principle in our approach. We are particularly interested in applications to lower-resource settings to address health disparities. We note that similar principles apply to other domains of AI-based image analysis for medical diagnostic testing.

Comparing predictive performance of pulmonary embolism risk stratification tools for acute clinical deterioration.

Existing pulmonary embolism (PE) risk scores were developed to predict death within weeks, but not more proximate adverse events. We determined the ability of 3 PE risk stratification tools (simplified pulmonary embolism severity index [sPESI], 2019 European Society of Cardiology guidelines [ESC], and PE short-term clinical outcomes risk estimation [PE-SCORE]) to predict 5-day clinical deterioration after emergency department (ED) diagnosis of PE. We analyzed data from six EDs on ED patients with confirmed PE. Clinical deterioration was defined as death, respiratory failure, cardiac arrest, new dysrhythmia, sustained hypotension requiring vasopressors or volume resuscitation, or escalated intervention within 5 days of PE diagnosis. We determined sensitivity and specificity of sPESI, ESC, and PE-SCORE for predicting clinical deterioration. Of 1569 patients, 24.5% had clinical deterioration within 5 days. sPESI, ESC, and PE-SCORE classifications were low-risk in 558 (35.6%), 167 (10.6%), and 309 (19.6%), respectively. Sensitivities of sPESI, ESC, and PE-SCORE for clinical deterioration were 81.8 (78, 85.7), 98.7 (97.6, 99.8), and 96.1 (94.2, 98), respectively. Specificities of sPESI, ESC, and PE-SCORE for clinical deterioration were 41.2 (38.4, 44), 13.7 (11.7, 15.6), and 24.8 (22.4, 27.3). Areas under the curve were 61.5 (59.1, 63.9), 56.2 (55.1, 57.3), and 60.5 (58.9, 62.0). Negative predictive values were 87.5 (84.7, 90.2), 97 (94.4, 99.6), and 95.1 (92.7, 97.5). ESC and PE-SCORE were better than sPESI for detecting clinical deterioration within 5 days after PE diagnosis.

Contrast computed tomography-based radiomics is correlation with COG risk stratification of neuroblastoma.

Although a risk stratification strategy for neuroblastoma (NB) has been proposed, precise and convenient clinical risk estimation remains challenging. This study aimed to investigate the correlation of contrast computed tomography (CT)-based radiomics with NB risk stratification. Patients with NB (n = 289) from two centers (244 and 45 patients in the training/testing and external validation cohorts, respectively) were divided into nonhigh- and high-risk groups. A total of 1648 radiomics features were extracted from the arterial phase, and the radiomics signature was constructed using rad scores, whereas the clinical model was established based on clinical factors. Further, a combined nomogram was developed based on the clinical factors and radiomics signatures. Finally, receiver operating characteristic curve and decision curve analyses (DCA) were used to assess the performance of the established models. Seventeen radiomics features were used to construct the radiomics signature. A significant difference was observed in the rad score between the two groups in the training (0.540 vs. 0.704, P < 0.001) and testing (0.563 vs. 0.969, P < 0.001) cohorts. The nomogram showed a higher area under the curve (AUC) in the training (AUC = 0.87), testing (AUC = 0.83), and external validation (AUC = 0.84) cohorts than other models. The Hosmer-Lemeshow test and calibration curves indicated that the nomogram fit perfectly. DCA demonstrated that the clinical-radiomics nomogram was more beneficial. Contrast CT-based radiomics shows correlation with COG risk stratification of NB. Radiomics features combined with clinical factors showed the best performance, which may improve the management of patients with NB.

Whole-exome sequencing: Clinical characterization of pediatric and adult Italian patients affected by different forms of hereditary cardiovascular diseases.

Hereditary cardiovascular diseases comprise several different entities. In this study, we focused on cardiomyopathies (i.e., hypertrophic, dilated, arrhythmogenic, and left ventricular non-compaction), channelopathies (i.e., Brugada syndrome and long QT syndrome), and aortopathies and pulmonary arterial hypertension (i.e., thoracic/abdominal aortic aneurysm and pulmonary arterial hypertension), and genetically characterized 200 Italian patients affected by these diseases. We employed whole-exome sequencing (WES), focused on four in silico gene panels, and the MLPA method for hypertrophic and arrhythmogenic right ventricular cardiomyopathy cases. Cardiomyopathies affected 87.5% of analyzed patients, channelopathies 7%, and aortopathies and pulmonary arterial hypertension 5.5%. The molecular diagnosis was confirmed for 21.5% of cases with a higher detection rate in familial forms (34%) than sporadic ones (14%). We highlighted the importance of family segregation to better understand the pathogenic role of the identified variants and their involvement in the clinical phenotype. Negative results could be ascribed to the high genetic and clinical heterogeneity of hereditary cardiovascular diseases; clinical follow-up and revaluation of WES data will be essential. This study highlights the importance of a multi-step approach (WES and MLPA) to characterize hereditary cardiovascular diseases, provides crucial information for clinical management and recurrence risk estimation, and lays the foundation for future personalized therapies.

Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE).

Develop and validate a prognostic model for clinical deterioration or death within days of pulmonary embolism (PE) diagnosis using point-of-care criteria. We used prospective registry data from six emergency departments. The primary composite outcome was death or deterioration (respiratory failure, cardiac arrest, new dysrhythmia, sustained hypotension, and rescue reperfusion intervention) within 5 days. Candidate predictors included laboratory and imaging right ventricle (RV) assessments. The prognostic model was developed from 935 PE patients. Univariable analysis of 138 candidate variables was followed by penalized and standard logistic regression on 26 retained variables, and then tested with a validation database (N = 801). Logistic regression yielded a nine-variable model, then simplified to a nine-point tool (PE-SCORE): one point each for abnormal RV by echocardiography, abnormal RV by computed tomography, systolic blood pressure < 100 mmHg, dysrhythmia, suspected/confirmed systemic infection, syncope, medico-social admission reason, abnormal heart rate, and two points for creatinine greater than 2.0 mg/dL. In the development database, 22.4% had the primary outcome. Prognostic accuracy of logistic regression model versus PE-SCORE model: 0.83 (0.80, 0.86) vs. 0.78 (0.75, 0.82) using area under the curve (AUC) and 0.61 (0.57, 0.64) vs. 0.50 (0.39, 0.60) using precision-recall curve (AUCpr). In the validation database, 26.6% had the primary outcome. PE-SCORE had AUC 0.77 (0.73, 0.81) and AUCpr 0.63 (0.43, 0.81). As points increased, outcome proportions increased: a score of zero had 2% outcome, whereas scores of six and above had ≥ 69.6% outcomes. In the validation dataset, PE-SCORE zero had 8% outcome [no deaths], whereas all patients with PE-SCORE of six and above had the primary outcome. PE-SCORE model identifies PE patients at low- and high-risk for deterioration and may help guide decisions about early outpatient management versus need for hospital-based monitoring.

267 Development and Validation of a Prognostic Tool: Pulmonary Embolism Short-Term Clinical Outcomes Risk Estimation

Develop and validate a prognostic prediction model for clinical deterioration or death within days of pulmonary embolism (PE) diagnosis using point-of-care criteria. We used data from the PE Short-term Clinical Outcomes Registry populated by emergency departments in six states. The primary composite outcome was death, cardiac arrest, respiratory failure, dysrhythmia, sustained hypotension treated with fluid boluses or adrenergic agents, or reperfusion intervention within 5 days after PE. Candidate predictors were demographics, vital signs, comorbidities, and immediate right ventricle (RV) assessments (biomarkers and imaging). The prediction rule was developed from 935 PE patients using univariate analyses of 107 candidate variables followed by penalized and standard logistic regression on retained variables and tested on a validation database (N = 801). Logistic regression yielded a nine-variable model, then simplified to a nine-point tool (PE-SCORE): one point each for abnormal RV by echocardiography, abnormal RV by computed tomography, systolic blood pressure < 100 mmHg, dysrhythmia, suspected sepsis, syncope, medico-social reason for admission, abnormal heart rate [< 50 or > 100 bpm], and two points for renal disease. In the development database, 22.4% had the primary outcome. Predictive accuracy of logistic regression versus PE-SCORE models: 0.83 vs. 0.78 using area under receiver operating curve (AUC) and 0.61 vs. 0.50 using precision recall curve (AUCpr). In the validation database, 26.6% had the primary outcome. PE-SCORE had AUC 0.77 and AUCpr 0.63. As points increased, outcome proportions increased: a score of zero had 2% outcome, whereas scores of six and above had > 69.6% outcomes. In the validation dataset, scores of six and above had 100% outcomes. PE-SCORE model identifies PE patients at low and high-risk for clinical deterioration and may guide decisions about early outpatient management versus need for hospital-based monitoring and considerations for escalated PE interventions.

Could VEGF-D level have a role in clinical risk scoring, estimation of thrombus burden, and treatment in acute pulmonary thromboembolism?

Pulmonary embolism (PE) is usually a complication of deep vein thrombosis and is an important cause of mortality and morbidity. Vascular endothelial growth factor D (VEGF-D) is a secretory protein that plays a role in the remodelling of blood vessels and the lymphatic system. This study aimed to determine the relationship between VEGF-D level and clinical risk scoring in patients with PE. The study included 117 patients admitted for PE that were divided into four groups: high-risk patients (n=35), high-intermediate-risk patients (n=30), low-intermediate-risk patients (n=24), and low-risk patients (n=28). Plasma VEGF-D was measured from peripheral venous blood samples (5mL) using a commercial enzyme-linked immunosorbent assay (ELISA) kit. Pulmonary Artery Obstruction Index (PAOI) was calculated from CT angiography imaging. There was no significant difference in troponin-I and NT-proBNP levels between the high-intermediate-risk and high-risk PE patients (P=.134, .146). VEGF-D and PAOI levels were found to be statistically significantly higher in high-risk patients compared with high-intermediate-risk patients (P=.016, .001). VEGF-D level was moderately correlated with mean pulmonary artery pressure and PAOI (r=.481, P=.01; r=.404, P=.01). In ROC curve analysis, a cut-off of 370.1pg/mL for VEGF-D had 91.4% sensitivity and 67% specificity in the differentiation of high-intermediate-risk and high-risk PE patients. This study showed that plasma VEGF-D level was more reliable than troponin-I and NT-proBNP in clinical risk scoring and demonstrating thrombus burden. VEGF-D can be used as a biomarker in clinical risk scoring and estimation of thrombus burden in patients with acute PE.

Personalized Decision Making on Genomic Testing in Early Breast Cancer: Expanding the MINDACT Trial with Decision-Analytic Modeling.

BackgroundGenomic tests may improve upon clinical risk estimation with traditional prognostic factors. We aimed to explore how evidence on the prognostic strength of a genomic signature (clinical validity) can contribute to individualized decision making on starting chemotherapy for women with breast cancer (clinical utility).MethodsThe MINDACT trial was a randomized trial that enrolled 6693 women with early-stage breast cancer. A 70-gene signature (Mammaprint) was used to estimate genomic risk, and clinical risk was estimated by a dichotomized version of the Adjuvant!Online risk calculator. Women with discordant risk results were randomized to the use of chemotherapy. We simulated the full risk distribution of these women and estimated individual benefit, assuming a constant relative effect of chemotherapy.ResultsThe trial showed a prognostic effect of the genomic signature (adjusted hazard ratio 2.4). A decision-analytic modeling approach identified far fewer women as candidates for genetic testing (4% rather than 50%) and fewer benefiting from chemotherapy (3% rather than 27%) as compared with the MINDACT trial report. The selection of women benefitting from genetic testing and chemotherapy depended strongly on the required benefit from treatment and the assumed therapeutic effect of chemotherapy.ConclusionsA high-quality pragmatic trial was insufficient to directly inform clinical practice on the utility of a genomic test for individual women. The indication for genomic testing may be far more limited than suggested by the MINDACT trial.

WAM to SeeSaw model for cancer therapy – overcoming LQM difficulties –

Purpose The assessment of biological effects caused by radiation exposure has been currently carried out with the linear-quadratic (LQ) model as an extension of the linear non-threshold (LNT) model. In this study, we suggest a new mathematical model named as SeaSaw (SS) model, which describes proliferation and cell death effects by taking account of Bergonie-Tribondeau’s law in terms of a differential equation in time. We show how this model overcomes the long-standing difficulties of the LQ model. Materials and methods We construct the SS model as an extended Wack-A-Mole (WAM) model by using a differential equation with respect to time in order to express the dynamics of the proliferation effect. A large number of accumulated data of such parameters as α and β in the LQ based models provide us with valuable pieces of information on the corresponding parameter and the maximum volume of the SS model. The dose rate and the notion of active cell can explain the present data without introduction of β, which is obtained by comparing the SS model with not only the cancer therapy data but also with in vitro experimental data. Numerical calculations are presented to grasp the global features of the SS model. Results The SS model predicts the time dependence of the number of active- and inactive-cells. The SS model clarifies how the effect of radiation depends on the cancer stage at the starting time in the treatment. Further, the time dependence of the tumor volume is calculated by changing individual dose strength, which results in the change of the irradiation duration for the same effect. We can consider continuous irradiation in the SS model with interesting outcome on the time dependence of the tumor volume for various dose rates. Especially by choosing the value of the dose rate to be balanced with the total growth rate, the tumor volume is kept constant. Conclusions The SS model gives a simple equation to study the situation of clinical radiation therapy and risk estimation of radiation. The radiation parameter extracted from the cancer therapy is close to the value obtained from animal experiment in vitro and in vivo. We expect the SS model leads us to a unified description of radiation therapy and protection and provides a great development in cancer-therapy clinical-planning.

Fatality and risk factors for severe courses of COVID-19 pneumonia

Die Schwere einer SARS-CoV-2-Pneumonie, ihr Verlauf, die Letalität und Mortalität werden multifaktoriell durch den unmittelbaren Parenchymschaden im Bereich der Lungen (inklusive der Pulmonalgefäße), vorbestehende Komorbiditäten, extrapulmonale Komplikationen, sekundäre Infektionen und die Qualität der verfügbaren medizinischen Versorgung bedingt. Diesbezüglich ist COVID-19 vergleichbar mit anderen schweren ambulant erworbenen Pneumonien durch konventionelle Erreger, auch wenn sich die Pathogenese unterscheidet. Die Letalität von hospitalisierten COVID-19-Patienten beträgt näherungsweise 20 % (damit höher als bei anderen Pneumonieerregern), bei intensivpflichtigen Patienten 30–40 % und von invasiv beatmeten Patienten ca. 50 %. Für die Letalität ausschlaggebende Risikofaktoren sind hohes Alter, Übergewicht, männliches Geschlecht und typische altersabhängige kardiopulmonale Grunderkrankungen. Die klinische Risikoeinschätzung im Krankenhaus sollte im Wesentlichen entsprechend den gültigen Pneumonieleitlinien erfolgen. Die Wertigkeit von COVID-19-spezifischen laborchemischen Surrogatmarkern zur Risikoeinschätzung und Behandlungsoptimierung ist noch nicht ausreichend beurteilbar.

A DIAGNOSTIC DILEMMA: NORMAL D-DIMER IN A PATIENT WITH EXTENSIVE PULMONARY EMBOLISM

SESSION TITLE: Medical Student/Resident Pulmonary Vascular Disease Posters SESSION TYPE: Med Student/Res Case Rep Postr PRESENTED ON: October 18-21, 2020 INTRODUCTION: The presentation of pulmonary embolism (PE) is very non-specific and carries a significant morbidity and mortality. Typically, D-dimer assay has a very high sensitivity and a negative predictive value of 99-100% in both low and moderate risk groups. We present a unique case of diagnosing extensive PE with deep vein thrombosis (DVT) in presence of a normal D-dimer. CASE PRESENTATION: A 69-year-old female with significant history of hypertension and diabetes presented with dry cough and worsening of dyspnea on exertion for four days. Patient denied chest pain, palpitations, fever, chills, diaphoresis, leg pain or swelling. Vitals showed a T 98.6, BP 112/64 mmHg, HR 56, RR 16, oxygen saturation of 90% on 3LPM of nasal canula. Physical exam, especially the pulmonary exam, was largely unremarkable. No swelling or pain in the lower extremities was noted. Laboratory findings including the metabolic panel, blood count, and a set of troponins were within normal limits. ECG showed a normal sinus rhythm, and a follow-up chest radiograph and a non-contrast CT scan of chest did not demonstrate any significant findings. Acute PE was ruled out since the D-dimer assay was normal and the pretest probability was low-moderate. Preliminary diagnosis of pulmonary hypertension was suspected and worked up. An echocardiogram showed severe pulmonary hypertension with elevated right ventricular systolic pressure in the setting of a normal LV ejection fraction. A ventilation perfusion scan was subsequently done to evaluate for CTEPH, and was overwhelmingly positive with a high probability of PE. A CT angiogram revealed extensive bilateral central and segmental PE. Doppler ultrasound of lower extremities revealed an acute non-occlusive DVT involving the left popliteal vein. Patient was subsequently started on anti-coagulants and the supplemental oxygen was continued prior to safe discharge. DISCUSSION: D-dimer assay is a highly sensitive test used in the evaluation of PE. It is a measure of monoclonal antibody to D-Dimer produced during the process of fibrinolysis. D-dimer has a half-life of 4-6 hours and stays elevated for about seven days. Once the clot organization and adherence begins, levels of D-dimer drop. As such, D-dimer levels correlate with the presence of fibrin clots. The assay can be falsely negative if the specimen is collected very early or later than 7 days of clot formation. Regardless, a negative assay should be able to safely rule out a large PE in low and moderate risk patients. A low d-dimer assay on presentation in light of an extensive PE/DVT makes our case unique. CONCLUSIONS: D-dimer assay usually provides excellent diagnostic yield while ruling out a PE/DVT. However, it remains prudent to consider the overall clinical presentation and go through a step by step approach to not miss a disease with a fatal potential such as a PE in our case. Reference #1: Dagkiran H, Atas R, Tomic I, Plachtzik C, Geisler T, Gawaz MP, Oberhoff M, Anger T. Severe Pulmonary Embolism with Negative D-Dimer-Testing. Journal of Cardiology and Therapy 2015; 2(1): 265-268 Available from: URL: http://www.ghrnet.org/index.php/jct/article/view/1033 Reference #2: Gupta RT, Kakarla RK, Kirshenbaum KJ, Tapson VF. D-dimers and efficacy of clinical risk estimation algorithms: sensitivity in evaluation of acute pulmonary embolism. AJR Am J Roentgenol. 2009;193(2):425-430 Reference #3: Le Gal G, Righini M, Roy P, et al. Value of D-Dimer Testing for the Exclusion of Pulmonary Embolism in Patients With Previous Venous Thromboembolism. Arch Intern Med. 2006;166(2):176 -180. doi:http://dx.doi.org/10.1001/archinte.166.2.176 DISCLOSURES: No relevant relationships by Richard Miller, source=Web Response No relevant relationships by Kinjal Patel, source=Web Response No relevant relationships by Rutwik Patel, source=Web Response No relevant relationships by Krunal Trivedi, source=Web Response

Clinically high-risk breast cancer displays markedly discordant molecular risk predictions between the MammaPrint and EndoPredict tests

Inter-test concordance between the MammaPrint and the EndoPredict tests used to predict the risk of recurrence in breast cancer was evaluated in 94 oestrogen receptor-positive, HER2-negative breast cancers. We correlated histopathological data with clinical risk estimation as defined in the MINDACT trial. 42.6% (40/94) of cases were high-risk by MammaPrint, 44.7% (42/94) by EndoPredict (EPclin), and 45.7% (43/94) by clinical risk definition. Thirty-six percent of genomic risk predictions were discordant with a low inter-test correlation between EndoPredict and MammaPrint (p = 0.012; κ = 0.27, 95% CI [0.069, 0.46]). Clinical risk stratification did not correlate with MammaPrint (p = 0.476) but highly correlated with EndoPredict (p < 0.001). Consequently, clinically high-risk tumours (n = 43) were more frequently high-risk by EndoPredict than by MammaPrint (76.6% vs. 46.5%, p = 0.004), with 44% of cases discordantly classified and no significant association between genomic risk predictions (p = 0.294). Clinicians need to be aware that clinical pre-stratification can profoundly influence multigenomic test performance.

Nomogram to predict prolonged postoperative ileus after gastrectomy in gastric cancer.

BACKGROUNDProlonged postoperative ileus (PPOI) is one of the common complications in gastric cancer patients who underwent gastrectomy. Evidence on the predictors of PPOI after gastrectomy is limited and few prediction models of nomogram are used to estimate the risk of PPOI. We hypothesized that a predictive nomogram can be used for clinical risk estimation of PPOI in gastric cancer patients.AIMTo investigate the risk factors for PPOI and establish a nomogram for clinical risk estimation.METHODSBetween June 2016 and March 2017, the data of 162 patients with gastrectomy were obtained from a prospective and observational registry database. Clinical data of patients who fulfilled the criteria were obtained. Univariate and multivariable logistic regression models were performed to detect the relationship between variables and PPOI. A nomogram for PPOI was developed and verified by bootstrap resampling. The calibration curve was employed to detect the concentricity between the model probability curve and ideal curve. The clinical usefulness of our model was evaluated using the net benefit curve.RESULTSThis study analyzed 14 potential variables of PPOI in 162 gastric cancer patients who underwent gastrectomy. The incidence of PPOI was 19.75% in patients with gastrectomy. Age older than 60 years, open surgery, advanced stage (III–IV), and postoperative use of opioid analgesic were independent risk factors for PPOI. We developed a simple and easy-to-use prediction nomogram of PPOI after gastrectomy. This nomogram had an excellent diagnostic performance [area under the curve (AUC) = 0.836, sensitivity = 84.4%, and specificity = 75.4%]. This nomogram was further validated by bootstrapping for 500 repetitions. The AUC of the bootstrap model was 0.832 (95%CI: 0.741–0.924). This model showed a good fitting and calibration and positive net benefits in decision curve analysis.CONCLUSIONWe have developed a prediction nomogram of PPOI for gastric cancer. This novel nomogram might serve as an essential early warning sign of PPOI in gastric cancer patients.

A comprehensive validation of very early rule-out strategies for non-ST-segment elevation myocardial infarction in emergency departments: protocol for a multicentre prospective cohort study

IntroductionRecent advances in troponin sensitivity enabled early and accurate judgement of ruling-out myocardial infarction, especially non-ST elevation myocardial infarction (NSTEMI) in emergency departments (EDs) with development of various prediction-rules and...

HumanMethylation450K Array-Identified Biomarkers Predict Tumour Recurrence/Progression at Initial Diagnosis of High-risk Non-muscle Invasive Bladder Cancer.

Background:High-risk non-muscle invasive bladder cancer (HR-NMIBC) is a clinically unpredictable disease. Despite clinical risk estimation tools, many patients are undertreated with intra-vesical therapies alone, whereas others may be over-treated with early radical surgery. Molecular biomarkers, particularly DNA methylation, have been reported as predictive of tumour/patient outcomes in numerous solid organ and haematologic malignancies; however, there are few reports in HR-NMIBC and none using genome-wide array assessment. We therefore sought to identify novel DNA methylation markers of HR-NMIBC clinical outcomes that might predict tumour behaviour at initial diagnosis and help guide patient management.Patients and methods:A total of 21 primary initial diagnosis HR-NMIBC tumours were analysed by Illumina HumanMethylation450 BeadChip arrays and subsequently bisulphite Pyrosequencing. In all, 7 had not recurred at 1 year after resection and 14 had recurred and/or progressed despite intra-vesical BCG. A further independent cohort of 32 HR-NMIBC tumours (17 no recurrence and 15 recurrence and/or progression despite BCG) were also assessed by bisulphite Pyrosequencing.Results:Array analyses identified 206 CpG loci that segregated non-recurrent HR-NMIBC tumours from clinically more aggressive recurrence/progression tumours. Hypermethylation of CpG cg11850659 and hypomethylation of CpG cg01149192 in combination predicted HR-NMIBC recurrence and/or progression within 1 year of diagnosis with 83% sensitivity, 79% specificity, and 83% positive and 79% negative predictive values.Conclusions:This is the first genome-wide DNA methylation analysis of a unique HR-NMIBC tumour cohort encompassing known 1-year clinical outcomes. Our analyses identified potential novel epigenetic markers that could help guide individual patient management in this clinically unpredictable disease.

Identifying people at higher risk of melanoma across the U.K.: a primary-care-based electronic survey.

Melanoma incidence is rising rapidly worldwide among white populations. Defining higher-risk populations using risk prediction models may help targeted screening and early detection approaches. To assess the feasibility of identifying people at higher risk of melanoma using the Williams self-assessed clinical risk estimation model in U.K. primary care. We recruited participants from the waiting rooms of 22 general practices covering a total population of > 240 000 in three U.K. regions: Eastern England, North East Scotland and North Wales. Participants completed an electronic questionnaire using tablet computers. The main outcome was the mean melanoma risk score using the Williams melanoma risk model. Of 9004 people approached, 7742 (86%) completed the electronic questionnaire. The mean melanoma risk score for the 7566 eligible participants was 17·15 ± 8·51, with small regional differences [lower in England compared with Scotland (P = 0·001) and Wales (P < 0·001), mainly due to greater freckling and childhood sunburn among Scottish and Welsh participants]. After weighting to the age and sex distribution, different potential cut-offs would allow between 4% and 20% of the population to be identified as higher risk, and those groups would contain 30% and 60%, respectively of those likely to develop melanoma. Collecting data on the melanoma risk profile of the general population in U.K. primary care is both feasible and acceptable for patients in a general practice setting, and provides opportunities for new methods of real-time risk assessment and risk stratified cancer interventions.

Fine needle aspiration cytological diagnosis of thyroid nodule with its clinical correlation

Background: Nodular goiter is common in Bangladesh. Thyroid nodules are important for their malignant potential especially the solitary and cold ones and when functionally euthyroid. Objectives: This study was designed to investigate the frequency of malignancy and cellular aberration detected by fine needle aspiration cytology (FNAC) in euthyroid nodules and its correlation with clinical findings. Methods: Subjects with nodular goiter attending Endocrine out patient department [n=150, nonpregnant, age (mean± SD): 37±12 years; sex (male: female): 21:129] were recruited for this study. All subjects underwent clinical risk stratification, estimation ofFT4 and TSH as well as ultrnsonogram (USG) and isotope scan of thyroid. Thyroid nodules were categorized into malignant, suspicious, benign and indeterminant on the basis of cellular character by FNAC. Statistical analysis was done by Chi-square and multiple regression analysis. Results: Patients were mostly females (86%) and 4.7% had family history of thyroid problems. Some had recent changes of size (14.7%), pain in the nodule (4%) and dysphagia (6%). Nodules were solitary in 45.3% and the rest (54.7%) had multinodular goiter. Enlarged regional lymph node was found in 12.7% patients. About 41 % were partially-cold followed by cold nodules (26.7%), patchy (16.7%), isoform (12%) and hot (4%) by isotope scan. Frequency of malignant (10%) character was highest in cold nodules followed by uniform (5.6%), patchy (4.0%) and partially cold (1.6%) while none in hot nodules; which were 22.5%, 11.1 %, 4.0%, 9.8% and 16.7% respectively for suspicious nodules. About 17% showed cellular aberration and 4.7% were clearly malignant, whereas 124 (82.7%) were benign. Of the malignant, 4 were solitary and 3 were multinodular; which were 10 and 9 among the suspicious ones. A significant number (77%, 20 out of 26) among the malignant/suspicious nodules fell into moderate to high risk category (x2=22.861, p&lt;0.001), while 23.1 % of the FNAC proven malignant/suspicious nodules were of low risk category. Enlarged lymph nodes (p&lt;0.001), increased diameter of nodules of &gt;4 cm (p=0.039) and recent changes in nodular size (p=0.042) were independently and signifi­cantly related to cellular aberration. Conclusions: FNAC is a useful tool for cellular diagnosis of thyroid nodules. Clinical suspicion for malignancy strongly correlates with the FNAC findings. But a good number of clinically Low risk categories would escape malignant cellular character unless FNAC is done.

Meta-analysis of the side-effect profiles of modern radiation therapies for patients with prostate cancer

One of the most relevant focus of recent developments in radiotherapy technology was the adequate irradiation of prostate cancer. The aim of this study was to analyse the safety of normo- and hypofractionated and high dose intensity-modulated radiotherapy. Toxicities were identified through literature review and evidence was synthetized with meta-analytical methods. The use of high dose intensity-modulated radiotherapy resulted in no difference in severe genitourinary (acute p = 0.9; late p = 0.95) and moderate or severe gastrointestinal (acute: N/A; late: p = 0.08) toxicities compared to 3D conformal radiation therapy. The risk ratio of moderate acute (RR = 1.39, 95% CI: 1.09-1.78; p = 0.008) and late genitourinary toxicities (RR = 1.48, 95% CI: 1.26-1.75; p<0,00001) was higher. There was no difference in hypo- and normofractionated intensity-modulated radiotherapy regarding severe genitourinary (acute: N/A; late: p = 0.73) and moderate or severe gastrointestinal (acute: p = 0.73; late: p = 0.55) toxicities, the risk of late moderate genitourinary toxicities was higher when using hypofractionation scheme (RR = 1.39, 95% CI: 1.00-1.94; p = 0.05). The use of normo- and hypofractionated and high dose intensity-modulated radiotherapy proved to be safe. However the higher risk of moderate genitourinary adverse events require an extensive clinical risk estimation.

GENETIC RISK SCORES PREDICT RECURRENCE OF ACUTE CORONARY SYNDROME

Clinical risk estimation tools have established their role in the prediction of recurrence of acute coronary syndrome (ACS). The value of genetic risk scores (GRS) for this purpose remains unclear. We examined how well three different GRSs estimate recurrent ACS. A cohort of 2,090 consecutive ACS