5 research outputs found
Association between disease status and abnormal FISH marker (>2 copies per cell) for the top 4 markers (CEP3, <i>TP63</i>, CEP6, <i>MYC</i>).
*<p>Adjusted by multiple logistic regression for gender, age, center, current smoking status and histologic grade.</p
Distribution of lung cancer cases and controls according to demographic and histology variables.
<p>Distribution of lung cancer cases and controls according to demographic and histology variables.</p
Percentage of lesions with abnormal FISH copy numbers according to case or control status (70 subjects).
*<p>Adjusted by multiple logistic regression for gender, age, center, and current smoking status.</p
Receiver operating characteristic curves describing the diagnostic prediction accuracy of three models, demographics alone (plain line, area under the curve (AUC) 73.4%), in combination with cytology (dashed line, AUC 86.6%) or demographics in combination with cytology and 4 FISH biomarker candidates (dotted line, AUC 92.6%).
<p>The demographic information represents gender, age, pack years smoking history, and smoking status.</p
Achieving thoracic oncology data collection in Europe: a precursor study in 35 countries
Background: A minority of European countries have participated in international comparisons with high level data on lung cancer. However, the nature and extent of data collection across the continent is simply unknown, and without accurate data collection it is not possible to compare practice and set benchmarks to which lung cancer services can aspire.
Methods: Using an established network of lung cancer specialists in 37 European countries, a survey was distributed in December 2014. The results relate to current practice in each country at the time, early 2015. The results were compiled and then verified with co-authors over the following months.
Results: Thirty-five completed surveys were received which describe a range of current practice for lung cancer data collection. Thirty countries have data collection at the national level, but this is not so in Albania, Bosnia-Herzegovina, Italy, Spain and Switzerland. Data collection varied from paper records with no survival analysis, to well-established electronic databases with links to census data and survival analyses.
Conclusion: Using a network of committed clinicians, we have gathered validated comparative data reporting an observed difference in data collection mechanisms across Europe. We have identified the need to develop a well-designed dataset, whilst acknowledging what is feasible within each country, and aspiring to collect high quality data for clinical research.</p