The importance of multimodality therapy in the treatment of sinonasal neuroendocrine carcinoma

<p>Sinonasal carcinoma with neuroendocrine differentiation (SCND) is a rare group of tumors known for their aggressive behavior and poor response to treatment. The data in the literature are sparse and cover a wide range of therapeutic approaches over a protracted timeline. Therefore, it is important that institutions report on their experience with these rare neoplasms. Clinical data, such as age at diagnosis, gender, tumor subtype and stage, treatment intention and modality, recurrence, salvage treatment, and survival of patients with a SCND, diagnosed at our department between 1980 and 2010, were retrospectively analyzed. Fifteen patients were available for analysis; eight with sinonasal undifferentiated carcinoma (SNUC), five with sinonasal neuroendocrine carcinoma (SNEC), and two with small cell neuroendocrine carcinoma (SmCC). The median age at the time of diagnosis was 68 years (range 28-87). Treatment consisted of surgery (2), radiotherapy (4), a combination of these modalities (6) and palliation (3). The estimated 5-year overall survival was 60 % for SNEC, 44 % for SNUC and 0 % for SmCC. According to our institutional experience an aggressive multi-modality approach incorporating (neoadjuvant) chemoradiotherapy, radical surgery and elective treatment of the neck is the best treatment strategy for SCND. The high propensity for distant metastasis and poor prognosis of SmCC warrants consideration of the impact of treatment on the remaining quality of life in these patients.</p>

Lung cancer risk at low cumulative asbestos exposure: meta-regression of the exposure–response relationship

Purpose: Existing estimated lung cancer risks per unit of asbestos exposure are mainly based on, and applicable to, high exposure levels. To assess the risk at low cumulative asbestos exposure, we provide new evidence by fitting flexible meta-regression models, a notably new and more robust method. Methods: Studies were selected if lung cancer risk per cumulative asbestos exposure in at least two exposure categories was reported. From these studies (n = 19), we extracted 104 risk estimates over a cumulative exposure range of 0.11-4,710 f-y/ml. We fitted linear and natural spline meta-regression models to these risk estimates. A natural spline allows risks to vary nonlinearly with exposure, such that estimates at low exposure are less affected by estimates in the upper exposure categories. Associated relative risks (RRs) were calculated for several low cumulative asbestos exposures. Results: A natural spline model fitted our data best. With this model, the relative lung cancer risk for c umulative exposure levels of 4 and 40 f-y/ml was estimated between 1.013 and 1.027, and 1.13 and 1.30, respectively. After stratification by fiber type, a non-significant three- to fourfold difference in RRs between chrysotile and amphibole fibers was found for exposures below 40 f-y/ml. Fiber-type-specific risk estimates were strongly influenced by a few studies. Conclusions: The natural spline regression model indicates that at lower asbestos exposure levels, the increase in RR of lung cancer due to asbestos exposure may be larger than expected from previous meta-analyses. Observed potency differences between different fiber types are lower than the generally held consensus. Low-exposed industrial or population-based cohorts with quantitative estimates of asbestos exposure a required to substantiate the risk estimates at low exposure levels from our new, flexible meta-regression