http://repub.eur.nl/res/aut/20433/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/37218/ 2012-01-01T00:00:00Z Background. Electronic patient files generate an enormous amount of medical data. These data can be used for research, such as prognostic modeling. Automatization of statistical prognostication processes allows automatic updating of models when new data is gathered. The increase of power behind an automated prognostic model makes its predictive capability more reliable. Cox proportional hazard regression is most frequently used in prognostication. Automatization of a Cox model is possible, but we expect the updating process to be time-consuming. A possible solution lies in an alternative modeling technique called random survival forests (RSFs). RSF is easily automated and is known to handle the proportionality assumption coherently and automatically. Performance of RSF has not yet been tested on a large head and neck oncological dataset. This study investigates performance of head and neck overall survival of RSF models. Performances are compared to a Cox model as the "gold standard." RSF might be an interesting alternative modeling approach for automatization when performances are similar. Methods. RSF models were created in R (Cox also in SPSS). Four RSF splitting rules were used: log-rank, conservation of events, log-rank score, and log-rank approximation. Models were based on historical data of 1371 patients with primary head-and-neck cancer, diagnosed between 1981 and 1998. Models contain 8 covariates: tumor site, T classification, N classification, M classification, age, sex, prior malignancies, and comorbidity. Model performances were determined by Harrell's concordance error rate, in which 33% of the original data served as a validation sample. Results. RSF and Cox models delivered similar error rates. The Cox model performed slightly better (error rate, 0.2826). The log-rank splitting approach gave the best RSF performance (error rate, 0.2873). In accord with Cox and RSF models, high T classification, high N classification, and severe comorbidity are very important covariates in the model, whereas sex, mild comorbidity, and a supraglottic larynx tumor are less important. A discrepancy arose regarding the importance of M1 classification (see Discussion). Conclusion. Both approaches delivered similar error rates. The Cox model gives a clinically understandable output on covariate impact, whereas RSF becomes more of a "black box." RSF complements the Cox model by giving more insight and confidence toward relative importance of model covariates. RSF can be recommended as the approach of choice in automating survival analyses. http://repub.eur.nl/res/pub/29321/ 2008-04-01T00:00:00Z Background: The OM-6 survey is a validated and multinationally accepted instrument to measure the treatment effect of otitis media in children. Routine use of the OM-6 in a busy general practice is not always possible and can lead to incomplete returned surveys. A simplified method is favoured when the aim is a continuous process of complete treatment-outcome-data collection. This study tests if a VAS can quantify how much a child suffers from chronic otitis media and how much this changes due to surgical treatment. The change in overall OM-6 scores due to surgical treatment, functions as the gold reference standard. Furthermore, this study tests if the VAS is faster to use than the OM-6 and if it leads to an improvement in complete data collection. Methods: Prospective cohort follow-up study of 175 consecutive children with chronic otitis media in a paediatric otolaryngology practice in a metropolitan area. Data collected included patient's age, gender, clinical presentation, type of surgical procedure performed, overall OM-6 score and VAS score (at initial presentation and at follow-up), time needed to complete an OM-6 survey and VAS separately and number of incorrect OM-6 surveys and VAS questions returned. Results: The VAS scores and overall OM-6 scores show a good, positive correlation at baseline (Spearman's ρ = 0.71). This correlation improves at follow-up, one and 6 months after intervention (ρ = 0.73 and ρ = 0.80, respectively). The change in VAS scores and overall OM-6 scores, interpreted as change due to surgical intervention, show a good positive correlation at follow-up (ρ = 0.70 and ρ = 0.77, respectively). The VAS is almost three times faster than the OM-6 (28 s versus 81 s). More than 13% of OM-6 surveys were returned incomplete. All VAS questions were returned correct. Conclusions: The VAS can be used as a simplified method for routine surgical treatment effect analysis in children with chronic otitis media. http://repub.eur.nl/res/pub/16991/ 1998-10-23T00:00:00Z Rhinitis is a very common disorder. Most people suffer from an infectious rhinitis at least once a year. The symptoms usually disappear within a week. The patients with chronic rhinitis pose a much greater problem. At least 10 % of the general population are affected by a chronic allergic or non-allergic non-infectious rhiilltis (l). The impact of the nasal complaints such as in rhinitis is often underestimated. Bousquet and Juniper demonstrated that the impact of the disease on the quality of life is greater in rhinitis than in asthma patients (2-4). There is no generally accepted system for the definition, classification and terminology of rhinitis (5). A distinction can be made between rhinitis of known and unknown etiology. Known causes for rhinitis can be subdivided in mechanical Jactors (e.g. septal deviation, foreign body,), injections (viral, bacterial, fungal), miscellaneous causes (e.g. rhinitis medicarnentosa, pregnancy, cystic fibrosis) and allergy. Syndromes of unknown etiology include non-allergic non-infectious perennial rhinitis (NANIPER), nasal polyposis and nonallergic rhinitis with eosinophilia (NARES). The subject of this thesis is the pathogenesis and treatment of NANIPER. As this teml suggests the disorder is diagnosed through the exclusion of the known causes for rhinitis. Available studies are often difficult to compare. Different authors use different methods to exclude "the known causes". The patients are sometimes presented in a study as NANIPER patients without further specification. The way in which an allergic pathogenesis is excluded varies from skin prick tests, senllu testing for specific IgE, total IgE, nasal provocation tests or a combination of these methods. To exclude infection some authors rely on the history (chronicity of the illness, lack of purulent secretions and or the classic symptoms of acute rhinosinusitis), some rely on laboratory parameters (sedimentation rate, white blood cell count, nasal smears), others use negative radiological findings (noffilal sinus X-ray or CATscan), all with or without the use of a nasal symptom score.