Sources of pre-analytical variations in yield of DNA extracted from blood samples: analysis of 50,000 DNA samples in EPIC.

The European Prospective Investigation into Cancer and nutrition (EPIC) is a long-term, multi-centric prospective study in Europe investigating the relationships between cancer and nutrition. This study has served as a basis for a number of Genome-Wide Association Studies (GWAS) and other types of genetic analyses. Over a period of 5 years, 52,256 EPIC DNA samples have been extracted using an automated DNA extraction platform. Here we have evaluated the pre-analytical factors affecting DNA yield, including anthropometric, epidemiological and technical factors such as center of subject recruitment, age, gender, body-mass index, disease case or control status, tobacco consumption, number of aliquots of buffy coat used for DNA extraction, extraction machine or procedure, DNA quantification method, degree of haemolysis and variations in the timing of sample processing. We show that the largest significant variations in DNA yield were observed with degree of haemolysis and with center of subject recruitment. Age, gender, body-mass index, cancer case or control status and tobacco consumption also significantly impacted DNA yield. Feedback from laboratories which have analyzed DNA with different SNP genotyping technologies demonstrate that the vast majority of samples (approximately 88%) performed adequately in different types of assays. To our knowledge this study is the largest to date to evaluate the sources of pre-analytical variations in DNA extracted from peripheral leucocytes. The results provide a strong evidence-based rationale for standardized recommendations on blood collection and processing protocols for large-scale genetic studies.

Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries

Background. The use of hospital discharge administrative data (HDAD) has been recommended for automating, improving, even substituting, population-based cancer registries. The frequency of false positive and false negative cases recommends local validation. Methods. The aim of this study was to detect newly diagnosed, false positive and false negative cases of cancer from hospital discharge claims, using four Spanish population-based cancer registries as the gold standard. Prostate cancer was used as a case study. Results. A total of 2286 incident cases of prostate cancer registered in 2000 were used for validation. In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5% (CI95% 10.3-19.6) to 45.7% (CI95% 41.4-50.1). In the most predictive algorithm (that using five diagnostic and five surgical codes) Positive Predictive Value estimates ranged from 55.9% (CI95% 42.4-68.8) to 74.3% (CI95% 67.0-80.6). The most frequent reason for false positive cases was the number of prevalent cases inadequately considered as newly diagnosed cancers, ranging from 61.1% to 82.3% of false positive cases. The most frequent reason for false negative cases was related to the number of cases not attended in hospital settings. In this case, figures ranged from 34.4% to 69.7% of false negative cases, in the most predictive algorithm. Conclusions. HDAD might be a helpful tool for cancer registries to reach their goals. The findings suggest that, for automating cancer registries, algorithms combining diagnoses and procedures are the best option. However, for cancer surveillance purposes, in those cancers like prostate cancer in which care is not only hospital-based, combining inpatient and outpatient information will be required.