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Schwameis R.,Medical University of Vienna | Grimm C.,Medical University of Vienna | Petru E.,Medical University of Graz | Natter C.,Medical University of Vienna | And 8 more authors.
PLoS ONE | Year: 2015

Objective: C-reactive protein (CRP) has previously been shown to serve as a prognostic parameter in women with gynecologic malignancies. Due to the lack of valid prognostic markers for uterine leiomyosarcoma (ULMS) this study set out to investigate the value of pre-treatment CRP serum levels as prognostic parameter. Methods: Data of women with ULMS were extracted from databases of three Austrian centres for gynaecologic oncology. Pre-treatment CRP serum levels were measured and correlated with clinico-pathological parameters. Univariate and multivariable survival analyses were performed. Results: In total, 53 patients with ULMS were included into the analysis. Mean (SD) CRP serum level was 3.46 mg/dL (3.96). Solely, an association between pre-treatment CRP serum levels and tumor size (p = 0.04) but no other clinic-pathologic parameter such as tumor stage (p = 0.16), or histological grade (p = 0.07), was observed. Univariate and multivariable survival analyses revealed that CRP serum levels (HR 2.7 [1.1-7.2], p = 0.037) and tumor stage (HR 6.1 [1.9-19.5], p = 0.002) were the only independent prognostic factors for overall survival (OS) in patients with ULMS. Patients with high pre-treatment CRP serum levels showed impaired OS compared to women with low levels (5-year-OS rates: 22.6% and 52.3%, p = 0.007). Conclusion: High pre-treatment CRP serum levels were independently associated with impaired prognosis in women with ULMS and might serve as a prognostic parameter in these patients. © 2015 Schwameis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Source


Mailath-Pokorny M.,Medical University of Vienna | Polterauer S.,Medical University of Vienna | Polterauer S.,Karl Landsteiner Institute for General Gynecology and Experimental Gynecologic Oncology | Worda K.,Medical University of Vienna | And 2 more authors.
PLoS ONE | Year: 2015

Objective: To determine the association between isolated mid-trimester short fetal femur length and adverse perinatal outcome. Methods: This is a retrospective cohort study of patients with singleton gestations routinely assessed by second trimester ultrasound examination during 2006-2013. A fetal isolated short femur was defined as a femur length (FL) below the 5th percentile in a fetus with an abdominal circumference greater than the 10th percentile. Cases of aneuploidy, skeletal dysplasia and major anomalies were excluded. Primary outcomes of interest included the risk of small for gestational age neonates, low birth weight and preterm birth (PTB). Secondary outcome parameters were a 5-min Apgar score less than 7 and a neonatal intensive care unit admission. A control group of 200 fetuses with FL ≥ 5th percentile was used to compare primary and secondary outcome parameters within both groups. Chi-square and Student's t-tests were used where appropriate. Results: Out of 608 eligible patients with a short FL, 117 met the inclusion criteria. Isolated short FL was associated with an increased risk for small for gestational age (19.7% versus 8.0%, p = 0.002) neonates, low birth weight (23.9% versus 8.5%, p<0.001), PTB (19.7% versus 6.0%, p<0.001) and neonatal intensive care unit admissions (13.7% versus 3.5%, p = 0.001). The incidence of a 5-min Apgar score less than 7 was similar in both groups. Conclusion: Isolated short FL is associated with a subsequent delivery of small for gestational age and Low birth weight neonates as well as an increased risk for PTB. This information should be considered when counseling patients after mid-trimester isolated short FL is diagnosed. © 2015 Mailath-Pokorny et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Source


Polterauer S.,Medical University of Vienna | Grimm C.,Medical University of Vienna | Hofstetter G.,Innsbruck Medical University | Concin N.,Innsbruck Medical University | And 7 more authors.
British Journal of Cancer | Year: 2012

Background: Nomograms are predictive tools that are widely used for estimating cancer prognosis. The aim of this study was to develop a nomogram for the prediction of overall survival (OS) in patients diagnosed with cervical cancer. Methods :Cervical cancer databases of two large institutions were analysed. Overall survival was defined as the clinical endpoint and OS probabilities were estimated using the Kaplan-Meier method. Based on the results of survival analyses and previous studies, relevant covariates were identified, a nomogram was constructed and validated using bootstrap cross-validation. Discrimination of the nomogram was quantified with the concordance probability.Results:In total, 528 consecutive patients with invasive cervical cancer, who had all nomogram variables available, were identified. Mean 5-year OS rates for patients with International Federation of Gynecologists and Obstetricians (FIGO) stage IA, IB, II, III, and IV were 99.0%, 88.6%, 65.8%, 58.7%, and 41.5%, respectively. Seventy-six cancer-related deaths were observed during the follow-up period. FIGO stage, tumour size, age, histologic subtype, lymph node ratio, and parametrial involvement were selected as nomogram covariates. The prognostic performance of the model exceeded that of FIGO stage alone and the models estimated optimism-corrected concordance probability was 0.723, indicating accurate prediction of OS. We present the prediction model as nomogram and provide a web-based risk calculator (http://www.ccc.ac.at/gcu). Conclusion :Based on six easily available parameters, a novel statistical model to predict OS of patients diagnosed with cervical cancer was constructed and validated. The model was implemented in a nomogram and provides accurate prediction of individual patients prognosis useful for patient counselling and deciding on follow-up strategies. © 2012 Cancer Research UK All rights reserved. Source


Mailath-Pokorny M.,Medical University of Vienna | Polterauer S.,Medical University of Vienna | Polterauer S.,Karl Landsteiner Institute for General Gynecology and Experimental Gynecologic Oncology | Kohl M.,Medical University of Vienna | And 4 more authors.
European Journal of Obstetrics Gynecology and Reproductive Biology | Year: 2015

Objectives To construct two prediction models for individualized assessment of preterm delivery risk within 48 h and before completed 32 weeks of gestation and to test the validity of modified and previously published models. Study design Data on 617 consecutive women with preterm labor transferred to a tertiary care center for threatened preterm delivery between 22 and 32 weeks of gestation were analysed. Variables predicting the risk of delivery within 48 h and before completed 32 weeks of gestation were assessed and applied to previously published prediction models. Multivariate analyses identified variables that were incorporated into two modified models that were subsequently validated. Results Two modified prediction models were developed and internally validated, incorporating four and six of the following variables to predict the risk of delivery within 48 h and before completed 32 weeks of gestation, respectively: presence of preterm premature rupture of membranes and/or vaginal bleeding, sonographic cervical length, week of gestation, fetal fibronectin, and serum C-reactive protein. The correspondence between the actual and the predicted preterm birth rates suggests excellent calibration of the models. Internal validation analyses for the modified 48 h and 32 week prediction models revealed considerably high concordance-indices of 0.8 (95%CI: [0.70-0.81]) and 0.85 (95%CI: [0.82-0.90]), respectively. Conclusions Two modified prediction models to assess the risk of preterm birth were constructed and validated. The models can be used for individualized prediction of preterm birth and allow more accurate risk assessment than based upon a single risk factor. An online-based risk-calculator was constructed and can be assessed through: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/clinical-software/prematurebirth/. © 2014 Elsevier Ireland Ltd. All rights reserved. Source


Helmy S.,Medical University of Vienna | Marschalek J.,Medical University of Vienna | Bader Y.,Saarland University | Koch M.,Medical University of Vienna | And 8 more authors.
International Journal of Gynecological Cancer | Year: 2016

Objective Transplantation results in a 5-time elevated risk for a variety of malignancies (Kaposi sarcoma, skin, liver, lung, gastrointestinal cancer). A patient's risk for malignancies could be of particular interest for the follow-up programs of patients and risk adaption after kidney transplantation. The aim of this study was to identify independent risk factors for de novo malignancies in women after renal transplantation. Methods and Materials This is a multicenter transversal study, conducted at the Medical University of Vienna and Hospital Rudolfstiftung, Vienna, Austria. We included female kidney graft recipients who were transplanted between 1980 and 2012 and followed-up at our institutions (N = 280). Clinical data of patients were extracted from hospital charts and electronic patient files. Patients were interviewed using a standardized questionnaire regarding their medical history, history of transplantation, and malignant diseases. Detailed information about present and past immunosuppressive regimens, rejection episodes and therapies, renal graft function, and information about primary disease was obtained. Diagnostic work-up and/or surgical exploration was performed if any presence of malignancy was suspected during routine follow-up. Histological specimens were obtained from all patients. Main outcome measures: the presence of de novo malignancy after kidney transplantation. Results Two hundred sixty-two women were included for statistical analysis. Median (interquartile range) follow-up period after transplantation was 101.1 (27.3-190.7) months. Thirty-two patients (12.2%) developed a malignancy: dermatologic malignancies (5.7%), breast cancer (3.4%), cervical cancer (0.8%), lung cancer (0.4%), gastrointestinal malignancies (1.5%), vulvar cancer (0.4%), and unclassified malignancies (1.9%). Median (interquartile range) time to malignancy after transplantation was 185.9 (92.0-257.6) months. Cumulative cancer rates were 4.9% (1 year), 14.4% (3 years), 16.4% (5 years), and 21.8% (10 years). Second transplantations were identified as independent risk factor for development of malignancy after transplantation. Conclusions Long-term risk of developing a malignancy after kidney transplantation is high, which might justify a follow-up of more than 10 years. Copyright © 2016 by IGCS and ESGO. Source

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