Useful Tool For Clinical Decision Research Articles

A novel risk classification system based on the eighth edition of TNM frameworks for esophageal adenocarcinoma patients: A deep learning approach.

To develop and validate a deep learning predictive model with better performance in survival estimation of esophageal adenocarcinoma (EAC). Cases diagnosed between January 2010 and December 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. A deep learning survival neural network was developed and validated based on 17 variables, including demographic information, clinicopathological characteristics, and treatment details. Based on the total risk score derived from this algorithm, a novel risk classification system was constructed and compared with the 8th edition of the tumor, node, and metastasis (TNM) staging system. Of 7,764 EAC patients eligible for the study, 6,818 (87.8%) were men and the median (interquartile range, IQR) age was 65 (58-72) years. The deep learning model generated significantly superior predictions to the 8th edition staging system on the test data set (C-index: 0.773 [95% CI, 0.757-0.789] vs. 0.683 [95% CI, 0.667-0.699]; P < 0.001). Calibration curves revealed that the deep learning model was well calibrated for 1- and 3-year OS, most points almost directly distributing on the 45° line. Decision curve analyses (DCAs) showed that the novel risk classification system exhibited a more significant positive net benefit than the TNM staging system. A user-friendly and precise web-based calculator with a portably executable file was implemented to visualize the deep learning predictive model. A deep learning predictive model was developed and validated, which possesses more excellent calibration and discrimination abilities in survival prediction of EAC. The novel risk classification system based on the deep learning algorithm may serve as a useful tool in clinical decision making given its easy-to-use and better clinical applicability.

Five EMT-Related Gene Signatures Predict Acute Myeloid Leukemia Patient Outcome

Background The epithelial mesenchymal transition (EMT) gene has been shown to be significantly associated with the prognosis of solid tumors; however, there is a lack of models for the EMT gene to predict the prognosis of AML patients. Methods First, we downloaded clinical data and raw transcriptome sequencing data from the TCGA database of acute myeloid leukemia (AML) patients. All currently confirmed EMT-related genes were obtained from the dbEMT 2.0 database, and 30% of the TCGA data were randomly selected as the test set. Univariate Cox regression analysis, random forest, and lasso regression were used to optimize the number of genes for model construction, and multivariate Cox regression was used for model construction. Area under the ROC curve was used to assess the efficacy of the model application, and the internal validation set was used to assess the stability of the model. Results A total of 173 AML samples were downloaded, and a total of 1184 EMT-related genes were downloaded. The results of univariate batch Cox regression analysis suggested that 212 genes were associated with patient prognosis, random forest and lasso regression yielded 18 and 8 prognosis-related EMT genes, respectively, and the results of multifactorial COX regression model suggested that 5 genes, CBR1, HS3ST3B1, LIMA1, MIR573, and PTP4A3, were considered as independent risk factors affecting patient prognosis. The model ROC results suggested that the area under the curve was 0.868 and the internal validation results showed that the area under the curve was 0.815. Conclusion During this study, we constructed a signature model of five EMT-related genes to predict overall survival in patients with AML; it will provide a useful tool for clinical decision making.

BIOM-24. PROTEIN SURFACE SIGNATURE ON SERUM EXTRACELLULAR VESICLES FOR NON-INVASIVE DETECTION OF TUMOR PROGRESSION IN GLIOBLASTOMA PATIENTS

Abstract INTRODUCTION Detection of tumor progression in glioblastoma patients remains a major challenge for clinicians due to equivocal MRI results. Extracellular vesicles (EVs) are potential biomarkers and can be detected in the blood of tumor patients. In this study, we evaluated the potential of serum-derived EVs from glioblastoma patients to serve as a marker for tumor progression in adjunction with MRI assessment. METHODS Glioblastoma patients from two independent cohorts, one from the multicenter Phase III CeTeG/NOA-09 trial (n=36) and the other from patients treated at the University of Bonn (n=31), were included in this study. EVs from serum of glioblastoma patients and healthy volunteers were separated by size exclusion chromatography and ultracentrifugation. EV markers were defined by using a proximity-extension assay and bead-based flow cytometry. Tumor progression was defined according to modified RANO criteria. RESULTS EVs from the serum of glioblastoma patients (n=67) showed an upregulation of CD29 (p=0.08), CD44 (p&amp;lt; 0.0001), CD81 (p&amp;lt; 0.0001), CD146 (p&amp;lt; 0.0001), C1QA (p=0.003), and histone H3 (p&amp;lt; 0.0001) as compared to serum EVs from healthy volunteers. For both independent cohorts of glioblastoma patients, we noted upregulation of C1QA, CD44, and histone H3 upon tumor progression, but not in patients with stable disease. Notably, six patients with worse survival compared to the median survival of the cohort did not fulfill RANO criteria at the time of suspected progression, yet showed an elevation of at least one out of these three markers. In a multivariable logistic regression analysis, a combination of CD29, CD44, CD81, C1QA, and histone H3 correlated with RANO-defined tumor progression with an AUC of 0.76. CONCLUSION Measurement of CD29, CD44, CD81, C1QA, and histone H3 in serum-derived EVs of glioblastoma patients, along with standard MRI assessment, could improve detection of true tumor progression and thus be a useful tool for clinical decision making.

Usefulness of carotid and femoral plaque burden quantification by 3-dimensional vascular ultrasound for cardiovascular risk assessment in the cardiovascular disease prevention unit

Abstract Introduction Subclinical atherosclerosis improves cardiovascular risk assessment and is considered a risk modifier in individuals at borderline-to-intermediate estimated risk by clinical risk scores. Purpose We seek to propose a new decision algorithm for statin allocation based on the quantification of carotid and/or femoral atherosclerosis burden by novel 3-dimensional vascular ultrasound (3DVUS) and to explore its potential additive value when used in combination with conventional risk evaluation. Methods We conducted an observational study in all outpatients without previous history of cardiovascular events assessed in the Cardiovascular Disease Prevention Unit during 2017–2020. Cardiovascular risk was assessed with the ACC/AHA 10-year atherosclerotic cardiovascular disease (ASCVD) risk algorithm to establish the indication for initiating statin therapy following current clinical guidelines. All patients underwent 3DVUS evaluation for carotid plaque burden (CPB) calculated as the sum of all plaque volumes present in bilateral carotid arteries. Femoral 3DVUS evaluation was included later in the study protocol. Global plaque burden (GPB) was calculated in patients with both carotid and femoral 3DVUS as the sum of all plaque volumes present in bilateral carotid and femoral arteries. Carotid and global plaque burden was classified as high, moderate and low if a patient presented a percentile (p) &amp;gt;75, p50–75 and p&amp;lt;50, respectively, based on the age and sex-adjusted reference values reported by PESA study (1). We determined the percentage of patients reclassified for considering (p&amp;gt;75) or discouraging (p&amp;lt;50) statin therapy over clinical recommendation. Results One hundred sixty-three patients (age 51±8 years; 72,4% men; 10y-ASCVD 5,9%±4,8%) were included, being the most frequent reason for referral the presence of metabolic syndrome (37%), followed by intermediate or indeterminate estimated CV risk (33%), one markedly elevated single risk factor (15%) and family history of early CVD (13%). 10y-ASCVD score classified 80 (49%) patients as low-risk without recommendation for initiating statins, 18 (11%) as high-risk indicating statin therapy and 65 (40%) patients that needed clinical-patient risk discussion. Among patients under risk discussion, the CPB percentile re-stratified 51 (78%) of them, recommending statins in 26 (40%) and discouraging statins in 25 (38%). In addition, CPB re-stratified 24 (30%) low-risk patients to recommend statins. A sub-group of 114 patients additionally underwent femoral 3DVUS, and calculated GPB led to similar results of patient re-stratification (Figure). Conclusions Quantification of 3D atherosclerosis burden and its percentile would re-stratify a significant number of patients with intermediate risk, becoming a potentially useful tool for clinical decision making. In addition, it possibly improves the detection of low-risk patients who would benefit from statin therapy. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Dr. Lόpez-Melgar has received a grant from the Spanish Society of Cardiology “Proyecto de investigaciόn traslacional en Cardiología 2020” Patient re-stratification with CPB/GPB

Abstract 552: Circulating tumor DNA predicts disease recurrence in ovarian cancer patients

Abstract Introduction: Epithelial ovarian, fallopian tube, and peritoneal cancer (EOC) is the most lethal gynecologic malignancy with a 5-year survival rate of 47%. While primary treatment generally results in remission, most patients relapse within 3 years. CA-125 is a commonly used biomarker for recurrence detection, however, it lacks specificity and is not associated with improved survival. Here we examine the utility of circulating tumor DNA (ctDNA) as a biomarker for EOC by assessing its relationship to patient outcome and CA-125 when measured pre-surgically and during patient monitoring. Methods: This study included patients diagnosed with stage I-IV EOC with plasma samples collected pre-surgically (n=44) and a group of patients (n=22) with serially collected samples after surgery. Median follow-up for patients with pre-surgical samples and with prospectively collected samples was 29 months (range: 6-150) and 15 months (range: 0.6-26), respectively. Whole exome sequencing was performed on patient tumors and matched normal tissue to design patient-specific ctDNA assays (bespoke mPCR NGS assay) for variant detection in plasma samples. The relationship between ctDNA status, CA-125 levels, and recurrence-free survival (RFS) were evaluated (Fisher's exact, log-rank test). Results: Among patients with presurgical plasma samples high-grade serous was the most common histological subtype 66% (29/44). Endometrioid represented 11% (5/44) of tumors and 23% (10/44) were tumors of other epithelial subtypes. In this cohort 75% (33/44) had early-stage disease, 7% (3/44) were metastatic and 18% (8/44) had the unstaged disease. The presence of ctDNA was observed in 73% of samples at baseline with detection rates of 69% (20/29) for serous and 80% (4/5) for endometrioid histologies. Pre-surgical ctDNA detection was significantly associated with a higher grade (p=0.003). All patients with ctDNA negative status at baseline (n=12) survived until the end of follow-up (median: 25 months), while 3 deaths were observed among ctDNA positive patients (n=32; p=0.003). In the sub-cohort of patients with prospective post-surgical plasma collection, ctDNA was observed in samples of all patients who relapsed (7/7; 100% sensitivity). ctDNA detection preceded radiological findings by a median of 9 months (range: 2-36). None of the patients with ctDNA negative status within 6 months after enrollment experienced disease progression (13/13; 100% specificity). The presence of ctDNA was observed to be a strong predictor of relapse (HR: 12.75, 95%CI: 1.7-94 p&amp;lt;0.0001), while CA-125 was not significantly associated with RFS (HR: 1.3, 95%CI: 0.3-6.3; p=0.09). Conclusions: The presence of ctDNA post-surgically is highly prognostic of decreased RFS and was found to be a stronger predictor of disease progression than CA-125 monitoring. These results suggest that monitoring ctDNA could be a useful tool in clinical decision making for patients with EOC. Citation Format: Jocelyn S. Chapman, William E. Pierson, Karen Smith-McCune, Geovanni Pineda, Reena M. Vattakalam, Alexandra Ross, Meredith A. Mills, Carlos J. Suarez, Tracy Davis, Robert P. Edwards, Michelle Boisen, James M. Ford, June Y. Hou, Hsin-Ta Wu, Scott Dashner, Ekaterina Kalashnikova, Angel Rodriguez, Bernhard Zimmermann, Sarah Sawyer, Himanshu Sethi, Alexey Aleshin. Circulating tumor DNA predicts disease recurrence in ovarian cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 552.

Development and Validation of a Nomogram for Predicting Overall Survival in Pediatric Patients with Atypical Teratoid/Rhabdoid Tumors.

To construct a reliable prediction model for pediatric atypical teratoid/rhabdoid tumor (ATRT) patients. Population-based data of patients diagnosed with intracranial ATRT were extracted from the National Cancer Institute?s Surveillance, Epidemiology, and End Results database. These patients were randomly assigned into training and validation cohorts at a ratio of 2:1. Univariable and multivariable Cox analyses were conducted to determine independent factors of overall survival (OS). A nomogram was then developed using the covariates with the best prognostic value, and the predictive performance of the nomogram was assessed by calibration curves, concordance index, time-dependent receiver operating characteristic curve analysis, and decision curve analysis. A total of 267 cases were included. The OS rates at 6 months, 1 year, and 3 years were 61.6%, 50.1%, and 35.4%, respectively. The results of multivariable Cox analysis showed that tumor extension, surgery type, radiotherapy, and chemotherapy were independent prognostic indicators. A nomogram integrating these factors was established to predict the 6-month, 1-year, and 3-year OS rates. This prediction model was validated in the validation cohort. The nomogram had favorable predictive performance and discrimination ability. We developed and validated a novel nomogram with favorable discrimination ability to predict prognosis for newly diagnosed pediatric ATRT patients. Although additional validation is required, this may be a useful tool in clinical decision making.

Synchronous Malignancies Identified by 18F-fluciclovine Positron Emission Tomography for Prostate Cancer: Case Series and Mini-Review.

Positron emission tomography using the fluorine-18 (18F) fluciclovine radiotracer has been approved for use in recurrent prostate cancer and is a useful tool for clinical decision making. However, 18F-fluciclovine is not specific for prostate cancer tumor cells, and false-positive results have been reported. In the present study, we have reported our experience with synchronous malignancies identified using 18F-fluciclovine and reviewed other reported cases, with a special emphasis on highlighting the clinical decisions that led to the correct diagnosis.

O24-6 - Tailor-made Simulation by UT-Heart Can Predict the Response of Heart Failure Patients to Cardiac Resynchronization Therapy

We have developed a multi-scale 3-D heart simulator “UT-Heart”, which reproduces the function of heart based on the molecular mechanisms of excitation-contraction coupling process. Combined with the personalization technology, of this simulator. we tested the capability of tailor-made heart model to reproduce the response to cardiac resynchronization therapy (CRT) in a retrospective study. We created heart models of nine patients treated by CRT based on the clinical data recorded before treatment. To each heart model, we performed CRT simulation according to the actual protocol and compared the results with clinical data. We found that simulated improvement in the maximum derivative of ventricular pressure can predict the clinically observed improvement in the ejection fraction. CRT simulation using tailor-made heart model can be a useful tool in clinical decision making.

Multi-scale, tailor-made heart simulation can predict the effect of cardiac resynchronization therapy

BackgroundThe currently proposed criteria for identifying patients who would benefit from cardiac resynchronization therapy (CRT) still need to be optimized. A multi-scale heart simulation capable of reproducing the electrophysiology and mechanics of a beating heart may help resolve this problem. The objective of this retrospective study was to test the capability of patient-specific simulation models to reproduce the response to CRT by applying the latest multi-scale heart simulation technology. Methods and resultsWe created patient-specific heart models with realistic three-dimensional morphology based on the clinical data recorded before treatment in nine patients with heart failure and conduction block treated by biventricular pacing. Each model was tailored to reproduce the surface electrocardiogram and hemodynamics of each patient in formats similar to those used in clinical practice, including electrocardiography (ECG), echocardiography, and hemodynamic measurements. We then performed CRT simulation on each heart model according to the actual pacing protocol and compared the results with the clinical data. CRT simulation improved the ECG index and diminished wall motion dyssynchrony in each patient. These results, however, did not correlate with the actual response. The best correlation was obtained between the maximum value of the time derivative of ventricular pressure (dP/dtmax) and the clinically observed improvement in the ejection fraction (EF) (r=0.94, p<0.01). ConclusionsBy integrating the complex pathophysiology of the heart, patient-specific, multi-scale heart simulation could successfully reproduce the response to CRT. With further verification, this technique could be a useful tool in clinical decision making.

Clinical relevance of narrow-band imaging in flexible cystoscopy: the DaBlaCa-7 study

Objective: This multicenter study investigated whether the use of narrow-band imaging (NBI) in flexible cystoscopy could improve diagnostics to a degree where clinical management was relevantly changed. Materials and methods: From May 2014 to June 2015, 955 patients were enrolled at three Danish urological departments. Patients had either hematuria (n = 483) or known recurrent non-muscle-invasive bladder cancer (NMIBC) (n = 472). High-definition (HD) cystoscopy was performed in white light (WL) and a preliminary clinical decision was made. Then, a second cystoscopy was performed in NBI and a conclusive clinical decision was made. A difference between the two decisions that had a clinical impact on the patient was considered clinically relevant. Results: Pathology was found in 216 WL cystoscopies, and additional pathology in 15 NBI cystoscopies (6.9%). Based on NBI, pathology was suspected in 23 patients (3.1%) in whom a WL cystoscopy revealed no tumor. In total, NBI changed the clinical decision relevantly in 1.9% of the patients. In hematuria patients, the calculated sensitivities of both NBI and WL were identically high, whereas sensitivity in patients with known NMIBC was significantly higher in NBI compared to WL (NBI: 100.0% vs WL: 83.2%, p < .05). NBI had a lower specificity compared to WL, especially in follow-up cystoscopies (NBI: 86.5% vs WL: 92.1, p < .05). Conclusion: NBI can be a useful tool in clinical decision making as a supplement to WL because it yields a significantly higher detection rate than WL cystoscopy alone. This is particularly relevant in patients with known recurrent NMIBC.

Diagnosis and follow-up of idiopathic retroperitoneal fibrosis: role of (18)F-FDG-PET/CT and biochemical parameters in patients with renal involvement.

Idiopathic retroperitoneal fibrosis (IRF) is a rare disease characterized by fibro-inflammatory reaction surrounding ureters and other inner organs with possible secondary renal involvement. Symptoms are aspecific and recurrent phases of activity are generally associated with elevation of inflammatory indices. 18F-FDG-PET is nowadays an important tool for the detection of this disease, allowing differentiation between metabolically active tissue and fibrotic one. The purpose of this study was to investigate the role of 18F-FDG-PET in the management of IRF and to evaluate possible correlations between biochemical parameters and PET/CT findings of disease activity. We enrolled seven consecutive patients with IRF (in five histology proved the disease) observed from 2003 to 2012 (5M:2 F, mean age 53.8 years, range 44-86 years). All patients presented with fever as first symptom; two had obstructive renal failure requiring hemodialysis; one underwent monolateral nephrectomy for parenchyma infiltration; six presented ureteral involvement; three underwent ureteral stent placement. For each patient, during a mean total follow-up of 26.5months we evaluated serum creatinine, BUN, Hb, RBCs, WBCs, PLT, CRP, ESR. Periodic 18F-FDG-PET/CT scans (every 5.9months-mean) were performed in all patients. Statistical evaluation was performed using "stepwise regression" analysis. Steroids and immunosuppressive agents induced a progressive normalization of PET/CT scans in all patients at the end of follow-up. Stepwise regression analysis showed that BUN, serum creatinine and CRP only if considered together, significantly correlated with SUV max (p value=0.000003057). 18F-FDG-PET is a useful tool for clinical decision making in patient with IRF, allowing to evaluate the efficacy of the pharmacological treatment and to detect early recurrences, to modify the therapeutic approach. Acute phase reactants are not reliable alone for the management and the follow-up as they are often not concordant with metabolic assessment of the disease. In patients with ureteral involvement, CRP together with BUN and serum creatinine has a significant correlation with PET/CT results, and can help physicians in therapeutic approach, better than a single parameter.

A proposal for a preoperative clinical scoring system for acute cholecystitis

BackgroundAcute cholecystitis is a common diagnosis for which surgery is usually indicated. However, the heterogeneity of clinical presentation makes it difficult to standardize management. The variation in clinical presentation is influenced by both patient-dependent and disease-specific factors. A preoperative clinical scoring system designed to included patient-dependent and clinical factors might be a useful tool in clinical decision making. MethodsThe data of patients undergoing laparoscopic cholecystectomy for acute cholecystitis in a university hospital were retrospectively reviewed. Patient-dependent factors (age, sex, body mass index, and American Society of Anesthesiologists score) and disease-specific factors (history of biliary colics, white blood count, C-reactive protein, and gallbladder wall thickness) were used to compute a clinical score between zero and nine for each patient. Cholecystitis was classified as mild (score ≤ 3), moderate (4 ≤ score ≤ 6), or severe (score ≥ 7). ResultsCholecystitis was mild in 45 cases, moderate in 105 cases, and severe in 27 cases.Among patient-dependent factors, the male gender, age >65 y, and American Society of Anesthesiologists score >2 correlated significantly with high scores, P = 0.001. Equally, high white blood count, elevated C-reactive protein, and gallbladder wall thickness >4 mm correlated significantly with high scores, P = 0.001. These findings were confirmed on multivariate analyses. High scores correlated significantly with the duration of surgery (P = 0.007), the need of intensive care unit management (P = 0.001) and the length of stay (P = 0.001). However, there was no significant association between the preoperative score and the rate of conversion (P = 0.103) or the rate of complication (P = 0.209). ConclusionsThis preoperative clinical scoring system has a potential to select patients with severe cholecystitis and therefore might be a useful tool in clinical decision making.

Abstract 1937: Development of microRNA-based prediction model of Trastuzumab treatment response for HER2-positive breast cancer using FFPE specimens.

Abstract [Background and Aim] Although Trastuzumab has been used for HER2(+) breast cancer, the treatment response of Trastuzumab therapy depends on unknown mechanisms among individual cases. In order to avoid unnecessary adverse events and to lighten financial burden, pre-treatment prediction of trastuzumab treatment response would be beneficial for patients. Thus, in this study, we develop a prediction algorithm using microRNA expression profile using formalin-fixed paraffin-embedded (FFPE) specimens of HER2(+) breast cancer. [Materials and Methods] Eighty-three breast cancer patients who underwent trastuzumab-chemo combined therapy before operations were enrolled with written informed consent. FFPE specimens of pre-treatment core needle biopsy samples were collected, and regions containing cancer and adjacent stromal cells were laser-microdissected. Total RNA samples extracted from the microdissected specimens were subjected for microRNA microarray (3D-Gene®, Toray, Japan) analysis. Among these 83 patients, 39 cases had pCR (definition: complete response in IDC regions regardless presence of DCIS without lymph node metastasis), and the other 44 cases did not. According to the pCR/non-pCR information, we develop a prediction model using 35 signature microRNAs by a SVM technique. Prediction accuracy assessed by Leave-one-out validation was AUROC=0.889. The 35 signature microRNAs for trastuzumab treatment response included 7 out of 8 let-7 family members and miR-125a-5p/b-5p, which were downregulated in pCR specimens. [Conclusion] microRNA profile could predict treatment response of trastuzumab-chemo combined therapy for HER2(+) breast cancer, and the developed prediction algorithm might be a useful tool for clinical decision making. Prediction Accuracy Outcome: non-pCR Outcome: pCR total Prediction: non-sensitive 35 6 41 Prediction: sensitive 9 33 42 total 44 39 83 Citation Format: Fumiaki Sato, Zhipeng Wang, Takayuki Ueno, Akira Myomoto, Satoko Takizawa, Feng Ling Pu, Norikazu Masuda, Yoshiki Mikami, Yoshiki Mikami, Kazuharu Shimizu, Shigehira Saji, Masakazu Toi. Development of microRNA-based prediction model of Trastuzumab treatment response for HER2-positive breast cancer using FFPE specimens. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1937. doi:10.1158/1538-7445.AM2013-1937

775: Which findings at the start of the second phase of labor are associated with operative delivery?

labor are associated with operative delivery? Mariette Ruckert, Myrthe Peelen, Michelle van Vliet, Mieke ten Eikelder, Nikki van Desel, Katrien Oude Rengerink, Ben Willem Mol, Irene de Graaf Diakonessenhuis, Obstetrics and Gynecology, Utrecht, Netherlands, Academic Medical Center, Obstetrics and Gynecology, Amsterdam, Netherlands, Groene Hart Hospital, Obstetrics and Gynecology, Gouda, Netherlands, Kennemer Gasthuis, Obstetrics and Gynecology, Haarlem, Netherlands OBJECTIVE: At present, there is little scientific fundament behind the interpretation of physical examination during labor and delivery. We aimed to indentify which findings at the start of the second phase of labor were associated with instrumental vaginal delivery (IVD) and emergency caesarean section (ECS). STUDY DESIGN: We performed a prospective cohort study in five hospitals in the Netherlands. Consecutive laboring women, with a viable singleton pregnancy in cephalic presentation and a gestational age of at least 34 weeks, were included. We assessed the predictive value of antepartum and intrapartum characteristics and findings at digital examination prior to the second phase of labor (start pushing) for operative delivery (OD) using logistic regression analysis. We selected variables based on literature and clinical experience. Backward selection was used to develop a prediction model, predictors with a p 0.157 remained in the final model. The discriminative ability of the model was assessed using ROC analyses (perfect when AUC 1). The correspondence between the predicted probability for OD and the observed number of operative deliveries over groups was assessed with a calibration plot (perfect when all points are on the diagonal). RESULTS: Between December 2010 and October 2011, we included 473 women, of whom 74 (16%) had a VID and 22 (5%) an ECS. For 425 women, data on all relevant variables were available. Predictors for OD at start of the second phase of labor were 10 cm dilatation, Caucasian etnicity, nulliparity, epidural analgesia, spontaneous start, molding, engagement and position of the fetal head (Table). The model including these variables showed good discriminative ability: AUC ROC 0.82 (95% CI 0.77-0.87). The model calibrated well (Figure). CONCLUSION: At start of the second phase of labor, antepartum and intrapartum characteristics can predict the need for OD. The prediction model may be implied as a useful tool for clinical decision making and assembling logistics at the delivery ward. 776 The validity of the variable “NICU admission” as an outcome measure for neonatal morbidity Nora Danhof, Melanie Wiegerinck, Anton van Kaam, Ben Willem Mol Academic Medical Center, Obstetrics & Gynecology, Amsterdam, Netherlands OBJECTIVE: The variable “neonatal intensive care (NICU) admission” is a frequently used outcome measure in clinical studies, as can be illustrated by the fact that it is reported as such in nearly one hundred Cochrane reviews from the Pregnancy and Childbirth Group. We addressed the question whether NICU admission is a valid surrogate outcome measure for neonatal morbidity, specifically when comparing different birth settings with different access to the NICU. STUDY DESIGN: We performed a retrospective cohort study among neonates admitted at the NICU of a tertiary hospital in the Netherlands during a ten-year period. The inclusion was restricted to singletons born at term, who were admitted at the NICU for delivery-related morbidity within 24 hours of birth. Patient characteristics and admission data were compared for four groups based on the line of care during delivery, i.e. home birth (group Ia), midwive lead hospital delivery (Ib), secondary care (II) and tertiary care (III). We specifically looked at the mortality rate, defined as the percentage of children that died at any time during NICU admission. RESULTS: We studied 871 newborns of which 53 were born at home, 25 under supervision of a midwife in the hospital, 166 in secondary Calibration plot, showing the average observed operative delivery rate (Y-axis) against the average calculated operative delivery rate (X-axis)

Abstract P5-10-09: Prediction of Trastuzumab treatment response for HER2-positive breast cancer by microRNA profiling

Abstract [Background and Aim] Although Trastuzumab has been used for HER2(+) breast cancer, the treatment response of Trastuzumab therapy depends on unknown mechanisms among individual cases. In order to avoid unnecessary adverse events and to lighten financial burden for patients, pre-treatment prediction of trastuzumab treatment response would be beneficial for patients. Thus, in this study, we develop a prediction algorithm using microRNA expression profile of breast cancer tissues. [Materials and Methods] Eighty-three breast cancer patients who underwent trastuzumab-chemo combined therapy before operations were enrolled with written informed consent. FFPE specimens of pre-treatment core needle biopsy samples were collected, and regions containing cancer and adjacent stromal cells were laser-microdissected. Total RNA samples extracted from the microdissected specimens were subjected for microRNA microarray (3D-Gene®, Toray, Japan) analysis. Among these 83 patients, 39 cases had pCR (complete response in IDC regions regardless presense of DCIS without lymphnode metastasis), and the other 44 cases did not. According to the pCR/non-pCR information, we develop a prediction model using 35 signature microRNAs by a SVM technique. Prediction accuracy assessed by Leave-one-out validation was AUROC=0.889. The 35 signature microRNAs for trastuzumab treatment response included 7 out of 8 let-7 family members and miR-125a-5p/b-5p. [Conclusion] microRNA profile could predict treatment response of trastuzumab-chemo combined therapy for HER2(+) breast cancer, and the developed prediction algorithm might be a useful tool for clinical decision making. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P5-10-09.

Comparative effectiveness of antibiotics for uncomplicated urinary tract infections: Network meta-analysis of randomized trials

The efficacies and adverse effects of different antibiotics for uncomplicated urinary tract infections (UTIs) have been studied by standard meta-analytic methods using pairwise direct comparisons of antimicrobial treatments: the effects of one treatment are compared to those of either another treatment or placebo. However, for clinical decisions, we need to know the effectiveness of each possible treatment in comparison with all relevant alternatives, not with just one. To compare the efficacies and adverse effects of all relevant antibiotics for UTI treatment simultaneously by performing a network meta-analysis using direct and indirect treatment comparisons. Using logistic regression analysis, we performed a network meta-analysis of randomized controlled trials (RCTs) published after 1999 that compared different oral antibiotic or placebo regimens for UTI treatment in general practice or outpatient settings. We looked at five binary outcomes: early clinical, early bacteriological, late clinical and late bacteriological outcomes, as well as adverse effects. Consequently, a ranking of the antibiotic regimens could be composed. Using a network structure, we could compare and rank nine treatments from 10 studies. Overall, ciprofloxacin and gatifloxacin appeared the most effective treatments, and amoxicillin-clavulanate appeared the least effective treatment. In terms of adverse effects, there were no significant differences. Network meta-analysis shows some clear efficacy differences between different antibiotic treatments for UTI in women. It provides a useful tool for clinical decision making in everyday practice. Moreover, the method can be used for meta-analyses of RCTs across primary care and beyond.

305: The influence of parity on maternal and neonatal outcomes in shoulder dystocia

305: The influence of parity on maternal and neonatal outcomes in shoulder dystocia

Risk assessment model for first-cycle chemotherapy-induced neutropenia in patients with solid tumours

LÓPEZ-POUSA A., RIFÀ J., CASAS DE TEJERINA A., GONZÁLEZ-LARRIBA J.L., IGLESIAS C., GASQUET J.A. & CARRATO A. (2010) European Journal of Cancer Care Risk assessment model for first-cycle chemotherapy-induced neutropenia in patients with solid tumoursChemotherapy-induced neutropenia, the major dose-limiting toxicity of chemotherapy, is directly associated with concomitant morbidity, mortality and health-care costs. The use of prophylactic granulocyte colony-stimulating factors may reduce the incidence and duration of chemotherapy-induced neutropenia, and is recommended in high-risk patients. The objective of this study was to develop a model to predict first-cycle chemotherapy-induced neutropenia (defined as neutropenia grade ≥3, with or without body temperature ≥38°C) in patients with solid tumours. A total of 1194 patients [56% women; mean age 58 ± 12 years; 94% Eastern Cooperative Oncology Group (ECOG) status ≤1] with solid tumours were included in a multi-centre non-interventional prospective cohort study. A predictive logistic regression model was developed. Several factors were found to influence chemotherapy-induced neutropenia. Higher ECOG status values increased toxicity (ECOG 2 vs. 0, P= 0.003; odds ratio 3.12), whereas baseline lymphocyte (P= 0.011; odds ratio 0.67) and neutrophil counts (P= 0.026; odds ratio 0.90) were inversely related to neutropenia occurrence. Sex and treatment intention also significantly influenced chemotherapy-induced neutropenia (P= 0.012). The sensitivity and specificity of the model were 63% and 67% respectively, and the positive and negative predictive values were 17% and 94% respectively. Once validated, this model should be a useful tool for clinical decision making.

A one year prospective study to compare and evaluate diagnostic accuracy of modified Alvarado score and ultrasonography in acute appendicitis, in adults.

To compare and evaluate diagnostic accuracy of modified Alvarado score and ultrasonography in co-relation to histopathology report for diagnosis of acute appendicitis. A prospective study of the patients who underwent appendectomy for suspected acute appendicitis at K.L.E.S. Hospital and M.R.C. Belgaum. The clinical, radiological and ultrasonogrpahic data of 60 patients with suspected appendicits was collected. These patients were evaluated by modified Alvarado here and ultrasonographically, which was correlated with histopatholocial finding. Out of 60 patients, 38.33% had acute appendicitis. 40% had modified Alvarado score ≥ 7 and 38.33% patients were ultrasonographically positive. In the present study, modified Alvarado score has sensitivity of 78.26%, specificity 83.78%, positive predictive value 75.00%, negative predictive value 86.11%, diagnostic accuracy 81.00% false positive error rate 16.22% and false negative error rate 21.74%. Ultrasonography had sensitivity of 82.61%, specificity of 89.19%, positive predictive value of 82.61, negative predictive value of 89.19.Diagnostic accuracy of 86.67%, false positive error rate of 10.81%, false negative error rate of 17.39%. When modified Alvarado score and ultrasonography were positive, 17 true positive cases and no false positive cases. The false negative cases in modified Alvarado score were five. When it was combined with ultrasonography the false negative cases reduced to two that is 60% reduction in false negative cases. Modified Alvarado score is useful tool in clinical decision making. When compared with ultrasonography neither one is advantageous. However, additional information provided by ultrasonography improves diagnostic accuracy.

A Prognostic Model for Predicting the Impact of Comorbidities on Survival of Patients with Myelodysplastic Syndromes.

Myelodysplastic syndromes (MDS) occur mainly in older persons, and these patients are likely to have comorbidities. We studied the impact of comorbidities on non-leukemic death (NLD) and overall survival (OS) in MDS patients with the aim of developing a specific prognostic index. Eight hundred forty consecutive patients receiving a diagnosis of MDS at Policlinico San Matteo, Pavia, Italy, between 1992 and 2006 were retrospectively evaluated. One or more comorbidities were present in 455/840 (54%) patients: the older the age, the higher their prevalence (P<0.001). Cardiac disease was observed in 25% of patients, liver disease in 16%, diabetes in 11%, prior solid tumor in 10%, nephropathy and pulmonary disease in 4%. Non-leukemic causes of death included cardiac failure (63%), infection (24%) and hemorrhage (7%). In a Cox analysis with age, sex, WHO category, cytogenetics and transfusion-dependency as time-dependent covariates, the presence of one or more comorbidities significantly affected both the risk of NLD (HR=1.91, P=0.001) and OS (HR=1.51, P=0.01), while it did not influence the risk of leukemic progression. The negative effect of comorbidities on OS was more evident in patients without excess of blasts (HR=1.8 P=0.007), while it retained a borderline significance in patients with more advanced disease (P=0.05). By including comorbidities as distinct entities in multivariable analysis, cardiac failure, liver or pulmonary disease, and solid tumors were found to independently affect the risk of NLD (HR=3.7, HR=2.08, HR=2.07 HR=2.23, respectively; P values from <0.001 to 0.033). Based on results of uni- and multivariable analysis, we developed a prognostic model for predicting the effect of comorbidities on NLD and OS. For each comorbidity, risk scores were estimated from the coefficients of the Cox regression. This MDS-specific comorbidity index (MDS-CI) allowed us to identify 3 groups of patients with different probability of NLD and OS (HR 2.78, P<0.001; HR 1.67 P=0.001), and provided a better stratification than the available non MDS-specific indices. Focusing on WPSS categories [J Clin Oncol 2007; 25:3503–10], MDS-CI significantly stratified survival of patients with very-low, low and intermediate risk groups (P<0.001), while it had no effect in high and very-high risk groups. We then investigated the relationship between transfusion-dependency, secondary iron overload and comorbidities. Heart failure (28% vs. 18% P=0.001) and cardiac death (69% vs 55% P=0.03) were significantly more frequent in transfusion-dependent patients. In a Cox analysis with time-dependent covariates, transfusion-dependent patients showed an increased risk of NLD (HR=2.12 P=<0.001), heart failure (HR 1.34 P=0.03), and cardiac death (HR 2.99 P=0.01). The development of secondary iron overload significantly affected the risk of NLD and OS (HR=1.25 and 1.16 respectively, P<0.001), and this effect was maintained after adjusting for transfusion burden. Iron overload specifically increased the risk of developing heart failure (HR=1.17, P<0.001). In summary, the presence of non-hematological comorbidities significantly worsens the survival of MDS patients. Transfusion-dependency and secondary iron overload are associated with an increased risk of cardiac complications and cardiac death. The MDS-CI might be a useful tool for clinical decision making in patients with myelodysplastic syndromes.