We retrospectively analysed the results of patients with advanced non-small-cell lung cancer treated with gefitinib to derive clinical factors predictive of response and a favourable survival outcome. Patients were treated with gefitinib 250 mg per day and reevaluated 4 -8 weeks later with repeat CT scan and every 8 weeks thereafter to assess response and the duration of response. Pathology review by a histopathologist was conducted, in particular to confirm a recently published result of bronchioloalveolar carcinoma histology or its components as predictive of response to gefitinib. Logistic regression and Cox regression analytical methods were applied to determine factors that could predict for response and improved overall survival. A total of 110 patients were treated. The overall response rate was 32% partial responses (PRs). Only never-smoking status was predictive of response in the logistic regression analysis, adjusted OR ¼ 6.1, 95% CI ¼ 1.7, 21.5. The presence of a PR and good performance status were predictive of a favourable survival outcome from the Cox regression modelling. Responders had an adjusted HR of 3.0, 95% CI ¼ 1.5 -5.8 compared to nonresponders, while patients with ECOG status 0 -1 had an adjusted HR of 0.42, 95% CI ¼ 0.25 -0.72, compared with patients with ECOG status 2 -4. Bronchioloalveolar carcinoma or its components were distinctly absent on pathology review. In conclusions, Never-smoking status is an important clinical predictor of a favourable response to gefitinib.

To study the utilisation pattern of head computed tomography (CT) for non-trauma adult cases in an urban emergency department (ED) and the rate of clinically significant CT abnormalities. We also tried to identify any useful clinical indicators that could be used to predict abnormal scans. Methodology: A one-year case series of adult non-trauma cranial CT scans ordered in an urban ED was studied. Patients less than 16 years old, with CT head done prior to presentation and/or attendance precipitated by trauma were excluded. Logistic regression was used to identify significant predictors for abnormal scans. Clinical indicators that were studied included age, altered mental status (AMS), headache and vomiting, elevated blood pressure, previous history of hypertension, Glasgow Coma Scale (GCS) and presence of focal neurological sign (FNS). Results: 183 adult non-trauma cranial CT scans were included in the study, and 109 (59.6%) CT scans revealed clinically significant abnormalities. Only AMS and FNS were found to be statistically significant in predicting abnormal scans. Patients with AMS had a 2.5 times (95% CI: 1.1 to 5.8) higher odds for an abnormal scan compared to those without AMS, adjusting for FNS. Patients with FNS had adjusted odds of 8.9 (95% CI: 4.2 to 18.8). Conclusion: This study reports a high (59.6%) rate of abnormal adult non-trauma cranial CT compared with previous studies. Altered mental status and the presence of focal neurological sign are significant predictors for an abnormal scan. They should serve as useful criteria when devising utilisation strategies for emergency non-trauma cranial CT in future studies.