Prediction of extranodal extension in oropharyngeal cancer patients and carcinoma of unknown primary: value of metabolic tumor imaging with hybrid PET compared with MRI and CT

Objectives: The aim of this study was to investigate the value of metabolic tumor imaging using hybrid PET for the preoperative detection of extranodal extension (ENE) in lymph node metastases of oropharyngeal squamous cell carcinoma (OPSCC). Methods: We performed a retrospective analysis of a consecutive cohort of patients with OPSCC treated with primary surgery with or without adjuvant (chemo-) radiotherapy at the Kantonsspital Sankt-Gallen and the University Hospital Zurich, Switzerland, from 2010 until 2019. Hybrid PET was compared to conventional cross-sectional imaging with MRI and CT. Histopathological presence of ENE of neck dissection specimen served as gold standard. Results: A total number of 234 patients were included in the study, 95 (40.6%) of which had pathological ENE (pENE). CT has a good specificity with 93.7%; meanwhile, MRI was the most sensitive diagnostic method (72.0%). The nodal metabolic tumor parameters (SUVmax, TLG, MTV) were significantly higher in patients with positive ENE (p < 0.001 for all three parameters) than in patients with negative ENE (p < 0.001, for all three parameters). Conclusions: CT achieved the best specificity, while MRI had the best sensitivity to detect ENE. Nodal metabolic tumor parameters differed significantly between ENE-positive/negative and p16-positive/negative patients. Hence, quantitative data obtained by metabolic imaging might predict presence of ENE and, therefore, could be helpful in customizing therapy management. Keywords: Biomarkers; Computed tomography; Extranodal extension; Head and neck cancer; Human papillomavirus; Magnetic resonance imaging; Oropharynx; Positron emission tomography; Squamous cell carcinoma; Unknown primary

Gender, age at onset, and duration of being ill as predictors for the long-term course and outcome of schizophrenia : an international multicenter study

Background The aim of the current study was to explore the effect of gender, age at onset, and duration on the long-term course of schizophrenia. Methods Twenty-nine centers from 25 countries representing all continents participated in the study that included 2358 patients aged 37.21 +/- 11.87 years with a DSM-IV or DSM-5 diagnosis of schizophrenia; the Positive and Negative Syndrome Scale as well as relevant clinicodemographic data were gathered. Analysis of variance and analysis of covariance were used, and the methodology corrected for the presence of potentially confounding effects. Results There was a 3-year later age at onset for females (P &lt; .001) and lower rates of negative symptoms (P &lt; .01) and higher depression/anxiety measures (P &lt; .05) at some stages. The age at onset manifested a distribution with a single peak for both genders with a tendency of patients with younger onset having slower advancement through illness stages (P = .001). No significant effects were found concerning duration of illness. Discussion Our results confirmed a later onset and a possibly more benign course and outcome in females. Age at onset manifested a single peak in both genders, and surprisingly, earlier onset was related to a slower progression of the illness. No effect of duration has been detected. These results are partially in accord with the literature, but they also differ as a consequence of the different starting point of our methodology (a novel staging model), which in our opinion precluded the impact of confounding effects. Future research should focus on the therapeutic policy and implications of these results in more representative samples

Staging of Schizophrenia With the Use of PANSS : An International Multi-Center Study

Introduction A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method. Methods Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed. Results Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified &gt;85% of patients. Discussion This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time.Funding Agencies|NHMRC Senior Principal Research FellowshipNational Health and Medical Research Council of Australia [APP1059660, APP1156072]</p

Staging of Schizophrenia With the Use of PANSS: An International Multi-Center Study

INTRODUCTION: A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method. METHODS: Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed. RESULTS: Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified >85% of patients. DISCUSSION: This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time.status: publishe