A proprietary multianalyte test for predicting extreme resistance to neoadjuvant 5-FU based chemoradiation (CTRT) in esophageal adenocarcinoma (EC).

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 51-51
Author(s):  
Weiwei Shan ◽  
Natalie Lassen ◽  
Clare Johnson ◽  
Yaeli Biermann-Harrar ◽  
Kristen M. Oelschlager ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Predictive Value ◽  
Validation Cohort ◽  
Neoadjuvant Treatment ◽  
Clinical Validation ◽  
Training Set ◽  
Extreme Resistance ◽  
Accurate Identification ◽  
Response To Chemotherapy ◽  
Gli 1

51 Background: Standard of care for localized EC is neoadjuvant CTRT followed by surgery. Although 5-FU based regimens are still commonly used, other regimens (CROSS) are also prescribed. Published EC studies report 20-25% of patients exhibit extreme resistance (exCTRT) to 5-FU based neoadjuvant treatment (NT); these patients may benefit from alternative treatment regimens. We have developed a proprietary assay using a training set of 167 patients to accurately identify patients with exCTRT (ROC 0.96). The results presented herein constitute an independent clinical validation. Methods: Biopsy samples from 71 pts diagnosed to have EC and who had undergone surgical excision following NT were obtained. IHC detection of NF-kB, SHH, and Gli-1 proteins in FFPE sections was performed in a CLIA approved lab. A GI pathologist and an expert clinical scientist blindly evaluated resection specimens and assigned a labeling index (LI) score. The LI for each case was compared to the established training set and the predicted response determined using a logistic regression algorithm. Blinded pathology scoring for exCTRT vs. non-exCTRT was performed for all samples using both CAP Tumor Response Grade (TRG) and the Rohatgi research scale. Results: Of the 71 EC cases in the clinical validation cohort, 24 had an outcome of exCTRT (<50% reduction in tumor following neoadjuvant treatment; TRG 3) and 47 had an outcome of non-exCTRT (>50% reduction in tumor; TRG 0-2). ROC for the validation cohort was 0.85. The positive predictive value for the validation study was 83%, reflecting an assay that can accurately predict those likely to have some degree of response to chemotherapy / radiation. Conversely, a negative predictive value of 83% with specificity of 94% was achieved indicating accurate identification of those not likely to benefit from neoadjuvant treatment. Conclusions: The analysis of NF-kB, SHH, and Gli-1 in EC tissue can accurately identify patients unlikely to respond to 5-FU based NT. These results are now confirmed using a CLIA accredited lab and a multicenter independent validation cohort of esophageal adenocarcinoma biopsies.

scholarly journals Development and validation of a prognostic COVID-19 severity assessment (COSA) score and machine learning models for patient triage at a tertiary hospital

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Verena Schöning ◽  
Evangelia Liakoni ◽  
Christine Baumgartner ◽  
Aristomenis K. Exadaktylos ◽  
Wolf E. Hautz ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Stratification ◽  
Clinical Outcomes ◽  
Predictive Value ◽  
Validation Cohort ◽  
Tertiary Hospital ◽  
Learning Models ◽  
Clinical Risk ◽  
Machine Learning Models ◽  
Risk Stratification Score

Abstract Background Clinical risk scores and machine learning models based on routine laboratory values could assist in automated early identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients at risk for severe clinical outcomes. They can guide patient triage, inform allocation of health care resources, and contribute to the improvement of clinical outcomes. Methods In- and out-patients tested positive for SARS-CoV-2 at the Insel Hospital Group Bern, Switzerland, between February 1st and August 31st (‘first wave’, n = 198) and September 1st through November 16th 2020 (‘second wave’, n = 459) were used as training and prospective validation cohort, respectively. A clinical risk stratification score and machine learning (ML) models were developed using demographic data, medical history, and laboratory values taken up to 3 days before, or 1 day after, positive testing to predict severe outcomes of hospitalization (a composite endpoint of admission to intensive care, or death from any cause). Test accuracy was assessed using the area under the receiver operating characteristic curve (AUROC). Results Sex, C-reactive protein, sodium, hemoglobin, glomerular filtration rate, glucose, and leucocytes around the time of first positive testing (− 3 to + 1 days) were the most predictive parameters. AUROC of the risk stratification score on training data (AUROC = 0.94, positive predictive value (PPV) = 0.97, negative predictive value (NPV) = 0.80) were comparable to the prospective validation cohort (AUROC = 0.85, PPV = 0.91, NPV = 0.81). The most successful ML algorithm with respect to AUROC was support vector machines (median = 0.96, interquartile range = 0.85–0.99, PPV = 0.90, NPV = 0.58). Conclusion With a small set of easily obtainable parameters, both the clinical risk stratification score and the ML models were predictive for severe outcomes at our tertiary hospital center, and performed well in prospective validation.

Echocardiography for the 10-year prediction of cardiomyopathy in long-term survivors of childhood cancer

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J.M Leerink ◽  
H.J.H Van Der Pal ◽  
E.A.M Feijen ◽  
P.G Meregalli ◽  
M.S Pourier ◽  
...  
Keyword(s):  
Childhood Cancer ◽  
Median Time ◽  
Cancer Diagnosis ◽  
Predictive Value ◽  
Validation Cohort ◽  
Funding Source ◽  
Derivation Cohort ◽  
After Cancer ◽  
Radiotherapy Dose

Abstract Background Childhood cancer survivors (CCS) treated with anthracyclines and/or chest-directed radiotherapy receive life-long echocardiographic surveillance to detect cardiomyopathy early. Current risk stratification and surveillance frequency recommendations are based on anthracycline- and chest-directed radiotherapy dose. We assessed the added prognostic value of an initial left ventricular ejection fraction (EF) measurement at &gt;5 years after cancer diagnosis. Patients and methods Echocardiographic follow-up was performed in asymptomatic CCS from the Emma Children's Hospital (derivation; n=299; median time after diagnosis, 16.7 years [inter quartile range (IQR) 11.8–23.15]) and from the Radboud University Medical Center (validation; n=218, median time after diagnosis, 17.0 years [IQR 13.0–21.7]) in the Netherlands. CCS with cardiomyopathy at baseline were excluded (n=16). The endpoint was cardiomyopathy, defined as a clinically significant decreased EF (EF&lt;40%). The predictive value of the initial EF at &gt;5 years after cancer diagnosis was analyzed with multivariable Cox regression models in the derivation cohort and the model was validated in the validation cohort. Results The median follow-up after the initial EF was 10.9 years and 8.9 years in the derivation and validation cohort, respectively, with cardiomyopathy developing in 11/299 (3.7%) and 7/218 (3.2%), respectively. Addition of the initial EF on top of anthracycline and chest radiotherapy dose increased the C-index from 0.75 to 0.85 in the derivation cohort and from 0.71 to 0.92 in the validation cohort (p&lt;0.01). The model was well calibrated at 10-year predicted probabilities up to 5%. An initial EF between 40–49% was associated with a hazard ratio of 6.8 (95% CI 1.8–25) for development of cardiomyopathy during follow-up. For those with a predicted 10-year cardiomyopathy probability &lt;3% (76.9% of the derivation cohort and 74.3% of validation cohort) the negative predictive value was &gt;99% in both cohorts. Conclusion The addition of the initial EF &gt;5 years after cancer diagnosis to anthracycline- and chest-directed radiotherapy dose improves the 10-year cardiomyopathy prediction in CCS. Our validated prediction model identifies low-risk survivors in whom the surveillance frequency may be reduced to every 10 years. Calibration in both cohorts Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Dutch Heart Foundation

scholarly journals Predictive value of the early response to chemotherapy in high-risk stages II and III Hodgkin's disease

Cancer ◽  
1987 ◽  
Vol 60 (8) ◽  
pp. 1713-1719 ◽  
Author(s):  
Alessandro Levis ◽  
Umberto Vitolo ◽  
Maria A. Ciocca Vasino ◽  
Giovanni Cametti ◽  
Alessandro Urgesi ◽  
...  
Keyword(s):  
High Risk ◽  
Predictive Value ◽  
Hodgkin's Disease ◽  
Hodgkin’S Disease ◽  
Early Response ◽  
Response To Chemotherapy

scholarly journals Molecular characterization of the response to chemotherapy in conventional osteosarcomas: Predictive value of HSD17B10 and IFITM2

2009 ◽  
Vol 125 (4) ◽  
pp. 851-860 ◽  
Author(s):  
Sébastien Salas ◽  
Pascal Jézéquel ◽  
Loic Campion ◽  
Jean-Laurent Deville ◽  
Frédéric Chibon ◽  
...  
Keyword(s):  
Molecular Characterization ◽  
Predictive Value ◽  
Response To Chemotherapy

scholarly journals Neoadjuvant Ifosfamide and Epirubicin in the Treatment of Malignant Peripheral Nerve Sheath Tumors

Sarcoma ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Angela C. Hirbe ◽  
Pippa F. Cosper ◽  
Sonika Dahiya ◽  
Brian A. Van Tine
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Peripheral Nerve ◽  
Clinical Benefit ◽  
Metabolic Response ◽  
Neoadjuvant Treatment ◽  
Soft Tissue Sarcomas ◽  
Nerve Sheath Tumors ◽  
Peripheral Nerve Sheath Tumors ◽  
Nerve Sheath ◽  
Response To Chemotherapy

Background and Objectives. Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft tissue sarcomas with poor overall survival. Response to chemotherapy has been debated for these tumors. Methods. We performed a retrospective analysis of the patients at our institution with a biopsy-proven diagnosis of MPNST that underwent neoadjuvant chemotherapy prior to surgery. Results. We retrospectively identified five patients who received neoadjuvant chemotherapy with epirubicin and ifosfamide that demonstrated a 30% reduction in tumor growth and a 60% response rate by RECIST criteria. Additionally, a metabolic response was observed in all three patients who received serial PET scans during neoadjuvant treatment. The clinical benefit rate, which includes stable disease, was 100%. Conclusions. Our data suggest that MPNSTs do respond to epirubicin and ifosfamide based chemotherapy and prospective studies are warranted to further define the clinical benefit.

scholarly journals A stepwise composite echocardiographic score predicts severe pulmonary hypertension in patients with interstitial lung disease

2018 ◽  
Vol 4 (2) ◽  
pp. 00124-2017 ◽  
Author(s):  
Simon Bax ◽  
Charlene Bredy ◽  
Aleksander Kempny ◽  
Konstantinos Dimopoulos ◽  
Anand Devaraj ◽  
...  
Keyword(s):  
Pulmonary Hypertension ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Predictive Value ◽  
Validation Cohort ◽  
Systolic Pressure ◽  
Right Atrial ◽  
Receiver Operating Curve ◽  
Severe Pulmonary Hypertension ◽  
Right Heart Catheterisation

European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs.Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used “additional PH signs” where RVSP was unavailable, using a bootstrapping technique.Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%).This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD.

Abstract WP158: Validation of a Preliminary Prediction Model with MR Plaque Imaging to Estimate Risk for New Ischemic Brain Lesions after Carotid Endarterectomy or Stenting

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Kohkichi Hosoda ◽  
Nobuyuki Akutsu ◽  
Atsushi Fujita ◽  
Eiji Kohmura
Keyword(s):  
Prediction Model ◽  
Carotid Stenosis ◽  
Predictive Value ◽  
Signal Intensity ◽  
Carotid Plaque ◽  
Brain Lesions ◽  
Black Blood ◽  
Training Set ◽  
Ischemic Brain ◽  
Validation Set

[Objective] Recently, we reported a preliminary prediction model with carotid plaque MRI to estimate risk for new ischaemic brain lesions after CEA or CAS. The objective of this study was to validate this model in new set of patients with carotid stenosis. [Methods] One hundred four patients with carotid stenosis undergoing treatment (63 CEA, 41 CAS) were used as a training set for construction of a preliminary prediction model to estimate risk for new ischemic brain lesions after CEA or CAS. T1 and T2 signal intensity of carotid plaque were measured on black-blood MRI. Associations among MRI findings, treatment, clinical factors, and occurrence of new ischemic lesions on DWI 1 day after treatment were studied by logistic regression. The validity of the prediction model was examined using a new set of patients with carotid stenosis (n = 43) as a validation set. [Results] In the training set, new DWI lesions after treatment were observed in 25 patients (24%). The model demonstrated that T1-signal intensity and CAS were positively associated with new lesions on post-treatment DWI scans, and T2 signal intensity was negatively associated (Fig. 1). The C-index was 0.79, which indicated some predictive value. In the validation set, new DWI lesions after treatment were observed in 10 patients (23%). However, C-index was 0.6 and positive predictive value was 33% (Fig. 2), which suggested overfitting of our model and/or differences in case-mix between the training set and validation set. [Conclusions] Our preliminary prediction model may provide some useful information for decision-making regarding treatment strategy, but needs further collection of patients to improve its predictive value.

Sign in / Sign up

Export Citation Format

Share Document