Development of Query Strategies to Identify a Histologic Lymphoma Subtype in a Large Linked Database System

Background: Large linked databases (LLDB) represent a novel resource for cancer outcomes research. However, accurate means of identifying a patient population of interest within these LLDBs can be challenging. Our research group developed a fully integrated platform that provides a means of combining independent legacy databases into a single cancer-focused LLDB system. We compared the sensitivity and specifi city of several SQL-based query strategies for identifying a histologic lymphoma subtype in this LLDB to determine the most accurate legacy data source for identifying a specifi c cancer patient population.Methods: Query strategies were developed to identify patients with follicular lymphoma from a LLDB of cancer registry data, electronic medical records (EMR), laboratory, administrative, pharmacy, and other clinical data. Queries were performed using common diagnostic codes (ICD-9), cancer registry histology codes (ICD-O), and text searches of EMRs. We reviewed medical records and pathology reports to confirm each diagnosis and calculated the sensitivity and specificity for each query strategy.Results: Together the queries identified 1538 potential cases of follicular lymphoma. Review of pathology and other medical reports confirmed 415 cases of follicular lymphoma, 300 pathology-verifi ed and 115 verified from other medical reports. The query using ICD-O codes was highly specific (96%). Queries using text strings varied in sensitivity (range 7–92%) and specifi city (range 86–99%). Queries using ICD-9 codes were both less sensitive (34–44%) and specific (35–87%).Conclusions: Queries of linked-cancer databases that include cancer registry data should utilize ICD-O codes or employ structured free-text searches to identify patient populations with a precise histologic diagnosis.Abbreviations: LLDB: Large Linked Database; SEER: Surveillance Epidemiology and End Results; EMR: Electronic Medical Record; ICD-9: International Classifi cation of Diseases (9th revision); ICD-O: International Classifi cation of Diseases for Oncology; AP: Anatomical Pathology; WHO: World Health Organization

Out-of-field in vivo dosimetry using TLD in SABR for primary kidney cancer involving mixed photon fields

Purpose To assess out-of-field dose using three different variants of LiF thermoluminescence dosimeters (TLD) for ten patients who underwent stereotactic ablative body radiotherapy (SABR) for primary renal cell carcinoma (RCC) and compare with treatment planning system (TPS) dose calculations. Methods and materials Thermoluminescent dosimeter (TLD) measurements were conducted at 20, 30, 40 and 50 cm from isocentre on ten patients undergoing SABR for primary RCC. Three types of high-sensitivity LiF:Mg,Cu,P TLD material with different 6Li/7Li isotope ratios were used. Patient plans were calculated using Eclipse Anisotropic Analytical Algorithm (AAA) for clinical evaluation and recalculated using Pencil Beam Convolution (PBC) algorithm for comparison. Results Both AAA and PBC showed diminished accuracy for photon doses at increasing distance out-of-field. At 50 cm, measured photon dose was 0.3 cGy normalised to a 10 Gy prescription on average with only small variation across all patients. This is likely due to the leakage component of the out-of-field dose. The 6Li-enriched TLD materials showed increased signal attributable to additional neutron contribution. Conclusion LiF:Mg,Cu,P TLD containing 6Li is sensitive enough to measure out-of-field dose 50 cm from isocentre however will over-estimate the photon component of out-of-field dose in high energy treatments due to the presence of thermal neutrons. 7Li enriched materials which are insensitive to neutrons are therefore required for accurate photon dosimetry. Neutron signal has been shown here to increase with MUs and is higher for patients treated using certain non coplanar beam arrangements. Further work is required to convert this additional neutron signal to dose

The importance of quasi-4D path-integrated dose accumulation for more accurate risk estimation in stereotactic liver radiotherapy

Intrafraction organ deformation may be accounted for by inclusion of temporal information in dose calculation models. In this article, we demonstrate a quasi-4-dimensional method for improved risk estimation. Conventional 3-dimensional and quasi- 4-dimensional calculations employing dose warping for dose accumulation were undertaken for patients with liver metastases planned for 42 Gy in 6 fractions of stereotactic body radiotherapy. Normal tissue complication probabilities and stochastic risks for radiation-induced carcinogenesis and cardiac complications were evaluated for healthy peripheral structures. Hypothetical assessments of other commonly employed dose/fractionation schedules on normal tissue complication probability estimates were explored. Conventional 3-dimensional dose computation may result in significant under- or overestimation of doses to organ at risk. For instance, doses differ (on average) by 17% (s ¼ 14%) for the left kidney, by 14% (s ¼ 7%) for the right kidney, by 7% (s ¼ 9%) for the large bowel, and by 10% (s ¼ 14%) for the duodenum. Discrepancies in the excess relative risk range up to about 30%. The 3-dimensional approach was shown to result in cardiac complication risks underestimated by >20%. For liver stereotactic body radiotherapy, we have shown that conventional 3-dimensional dose calculation may significantly over-/underestimate dose to organ at risk (90%-120% of the 4-dimensional estimate for the mean dose and 20%-150% for D2%). Providing dose estimates that most closely represent the actual dose delivered will provide valuable information to improve our understanding of the dose response for partial volume irradiation using hypofractionated schedules. Excess relative risks of radiocarcinogenesis were shown to range up to approximately excess relative risk ¼ 4 and the prediction thereof depends greatly on the use of either 3-dimensional or 4-dimensional methods (with corresponding results differing by tens of percent)

Detection and assessment of copy number variation using PacBio long-read and Illumina sequencing in New Zealand dairy cattle

Single nucleotide polymorphisms have been the DNA variant of choice for genomic prediction, largely because of the ease of single nucleotide polymorphism genotype collection. In contrast, structural variants (SV), which include copy number variants (CNV), translocations, insertions, and inversions, have eluded easy detection and characterization, particularly in nonhuman species. However, evidence increasingly shows that SV not only contribute a substantial proportion of genetic variation but also have significant influence on phenotypes. Here we present the discovery of CNV in a prominent New Zealand dairy bull using long-read PacBio (Pacific Biosciences, Menlo Park, CA) sequencing technology and the Sniffles SV discovery tool (version 0.0.1; https://github.com/fritzsedlazeck/Sniffles). The CNV identified from long reads were compared with CNV discovered in the same bull from Illumina sequencing using CNVnator (read depth–based tool; Illumina Inc., San Diego, CA) as a means of validation. Subsequently, further validation was undertaken using whole-genome Illumina sequencing of 556 cattle representing the wider New Zealand dairy cattle population. Very limited overlap was observed in CNV discovered from the 2 sequencing platforms, in part because of the differences in size of CNV detected. Only a few CNV were therefore able to be validated using this approach. However, the ability to use CNVnator to genotype the 557 cattle for copy number across all regions identified as putative CNV allowed a genome-wide assessment of transmission level of copy number based on pedigree. The more highly transmissible a putative CNV region was observed to be, the more likely the distribution of copy number was multimodal across the 557 sequenced animals. Furthermore, visual assessment of highly transmissible CNV regions provided evidence supporting the presence of CNV across the sequenced animals. This transmission-based approach was able to confirm a subset of CNV that segregates in the New Zealand dairy cattle population. Genome-wide identification and validation of CNV is an important step toward their inclusion in genomic selection strategies