Genetic drivers and cellular selection of female mosaic X chromosome loss.

Mosaic loss of the X chromosome (mLOX) is the most common clonal somatic alteration in leukocytes of female individuals1,2, but little is known about its genetic determinants or phenotypic consequences. Here, to address this, we used data from 883,574 female participants across 8 biobanks; 12% of participants exhibited detectable mLOX in approximately 2% of leukocytes. Female participants with mLOX had an increased risk of myeloid and lymphoid leukaemias. Genetic analyses identified 56 common variants associated with mLOX, implicating genes with roles in chromosomal missegregation, cancer predisposition and autoimmune diseases. Exome-sequence analyses identified rare missense variants in FBXO10 that confer a twofold increased risk of mLOX. Only a small fraction of associations was shared with mosaic Y chromosome loss, suggesting that distinct biological processes drive formation and clonal expansion of sex chromosome missegregation. Allelic shift analyses identified X chromosome alleles that are preferentially retained in mLOX, demonstrating variation at many loci under cellular selection. A polygenic score including 44 allelic shift loci correctly inferred the retained X chromosomes in 80.7% of mLOX cases in the top decile. Our results support a model in which germline variants predispose female individuals to acquiring mLOX, with the allelic content of the X chromosome possibly shaping the magnitude of clonal expansion.

Targeted long-read sequencing of the Ewing sarcoma 6p25.1 susceptibility locus identifies germline-somatic interactions with EWSR1-FLI1 binding.

Ewing sarcoma (EwS) is a rare bone and soft tissue malignancy driven by chromosomal translocations encoding chimeric transcription factors, such as EWSR1-FLI1, that bind GGAA motifs forming novel enhancers that alter nearby expression. We propose that germline microsatellite variation at the 6p25.1 EwS susceptibility locus could impact downstream gene expression and EwS biology. We performed targeted long-read sequencing of EwS blood DNA to characterize variation and genomic features important for EWSR1-FLI1 binding. We identified 50 microsatellite alleles at 6p25.1 and observed that EwS-affected individuals had longer alleles (>135 bp) with more GGAA repeats. The 6p25.1 GGAA microsatellite showed chromatin features of an EWSR1-FLI1 enhancer and regulated expression of RREB1, a transcription factor associated with RAS/MAPK signaling. RREB1 knockdown reduced proliferation and clonogenic potential and reduced expression of cell cycle and DNA replication genes. Our integrative analysis at 6p25.1 details increased binding of longer GGAA microsatellite alleles with acquired EWSR-FLI1 to promote Ewing sarcomagenesis by RREB1-mediated proliferation.

Serum biomarkers are altered in UK Biobank participants with mosaic chromosomal alterations.

Age-related clonal expansion of cells harbouring mosaic chromosomal alterations (mCAs) is one manifestation of clonal haematopoiesis. Identifying factors that influence the generation and promotion of clonal expansion of mCAs are key to investigate the role of mCAs in health and disease. Herein, we report on widely measured serum biomarkers and their possible association with mCAs, which could provide new insights into molecular alterations that promote acquisition and clonal expansion. We performed a cross-sectional investigation of the association of 32 widely measured serum biomarkers with autosomal mCAs, mosaic loss of the Y chromosome, and mosaic loss of the X chromosome in 436 784 cancer-free participants from the UK Biobank. mCAs were associated with a range of commonly measured serum biomarkers such as lipid levels, circulating sex hormones, blood sugar homeostasis, inflammation and immune function, vitamins and minerals, kidney function, and liver function. Biomarker levels in participants with mCAs were estimated to differ by up to 5% relative to mCA-free participants, and individuals with higher cell fraction mCAs had greater deviation in mean biomarker values. Polygenic scores associated with sex hormone binding globulin, vitamin D, and total cholesterol were also associated with mCAs. Overall, we observed commonly used clinical serum biomarkers related to disease risk are associated with mCAs, suggesting mechanisms involved in these diseases could be related to mCA proliferation and clonal expansion.

Telomere length and clonal chromosomal alterations in peripheral blood of patients with severe aplastic anaemia.

Severe aplastic anaemia (SAA) is a rare and life-threatening bone marrow failure disorder. We used data from the transplant outcomes in aplastic anaemia study to characterize mosaic chromosomal alterations (mCAs) in the peripheral blood of 738 patients with acquired SAA and evaluate their associations with telomere length (TL) and survival post-haematopoietic cell transplant (HCT). The median age at HCT was 20.4 years (range = 0.2-77.4). Patients with SAA had shorter TL than expected for their age (median TL percentile for age: 35.7th; range <1-99.99). mCAs were detected in 211 patients (28.6%), with chr6p copy-neutral loss of heterozygosity (6p-CNLOH) in 15.9% and chr7 loss in 3.0% of the patients; chrX loss was detected in 4.1% of female patients. Negative correlations between mCA cell fraction and measured TL (r = -0.14, p = 0.0002), and possibly genetically predicted TL (r = -0.07, p = 0.06) were noted. The post-HCT 3-year survival probability was low in patients with chr7 loss (39% vs. 72% in patients with chr6-CNLOH, 60% in patients with other mCAs and 70% in patients with no mCAs; p-log rank = 0.001). In multivariable analysis, short TL (p = 0.01), but not chr7 loss (p = 0.29), was associated with worse post-HCT survival. TL may guide clinical decisions in patients with SAA.

Genetically predicted telomere length is associated with clonal somatic copy number alterations in peripheral leukocytes.

Telomeres are DNA-protein structures at the ends of chromosomes essential in maintaining chromosomal stability. Observational studies have identified associations between telomeres and elevated cancer risk, including hematologic malignancies; but biologic mechanisms relating telomere length to cancer etiology remain unclear. Our study sought to better understand the relationship between telomere length and cancer risk by evaluating genetically-predicted telomere length (gTL) in relation to the presence of clonal somatic copy number alterations (SCNAs) in peripheral blood leukocytes. Genotyping array data were acquired from 431,507 participants in the UK Biobank and used to detect SCNAs from intensity information and infer telomere length using a polygenic risk score (PRS) of variants previously associated with leukocyte telomere length. In total, 15,236 (3.5%) of individuals had a detectable clonal SCNA on an autosomal chromosome. Overall, higher gTL value was positively associated with the presence of an autosomal SCNA (OR = 1.07, 95% CI = 1.05-1.09, P = 1.61×10-15). There was high consistency in effect estimates across strata of chromosomal event location (e.g., telomeric ends, interstitial or whole chromosome event; Phet = 0.37) and strata of copy number state (e.g., gain, loss, or neutral events; Phet = 0.05). Higher gTL value was associated with a greater cellular fraction of clones carrying autosomal SCNAs (ß = 0.004, 95% CI = 0.002-0.007, P = 6.61×10-4). Our population-based examination of gTL and SCNAs suggests inherited components of telomere length do not preferentially impact autosomal SCNA event location or copy number status, but rather likely influence cellular replicative potential.

PCAmatchR: a flexible R package for optimal case-control matching using weighted principal components.

SUMMARY: A concern when conducting genome-wide association studies (GWAS) is the potential for population stratification, i.e. ancestry-based genetic differences between cases and controls, that if not properly accounted for, could lead to biased association results. We developed PCAmatchR as an open source R package for performing optimal case-control matching using principal component analysis (PCA) to aid in selecting controls that are well matched by ancestry to cases. PCAmatchR takes user supplied PCA outputs and selects matching controls for cases by utilizing a weighted Mahalanobis distance metric which weights each principal component by the percentage of genetic variation explained. Results from the 1000 Genomes Project data demonstrate both the functionality and performance of PCAmatchR for selecting matching controls for case populations as well as reducing inflation of association test statistics. PCAmatchR improves genomic similarity between matched cases and controls, which minimizes the effects of population stratification in GWAS analyses. AVAILABILITY AND IMPLEMENTATION: PCAmatchR is freely available for download on GitHub (https://github.com/machiela-lab/PCAmatchR) or through CRAN (https://CRAN.R-project.org/package=PCAmatchR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A machine learning compatible method for ordinal propensity score stratification and matching.

Although machine learning techniques that estimate propensity scores for observational studies with multivalued treatments have advanced rapidly in recent years, the development of propensity score adjustment techniques has not kept pace. While machine learning propensity models provide numerous benefits, they do not produce a single variable balancing score that can be used for propensity score stratification and matching. This issue motivates the development of a flexible ordinal propensity scoring methodology that does not require parametric assumptions for the propensity model. The proposed method fits a one-parameter power function to the cumulative distribution function (CDF) of the generalized propensity score (GPS) vector resulting from any machine learning propensity model, and is henceforth called the GPS-CDF method. The estimated parameter from the GPS-CDF method, ã , is a scalar balancing score that can be used to group similar subjects in outcome analyses. Specifically, subjects who received different levels of the treatment are stratified or matched based on their ã value to produce unbiased estimates of the average treatment effect (ATE). Simulation studies presented show remediation of covariate balance, minimal bias in ATEs, and maintain coverage probability. The proposed method is applied to the Mexican-American Tobacco use in Children (MATCh) study to determine whether an ordinal treatment of exposure to smoking imagery in movies causes cigarette experimentation in Mexican-American adolescents.

Propensity score stratification methods for continuous treatments.

Continuous treatments propensity scoring remains understudied as the majority of methods are focused on the binary treatment setting. Current propensity score methods for continuous treatments typically rely on weighting in order to produce causal estimates. It has been shown that in some continuous treatment settings, weighting methods can result in worse covariate balance than had no adjustments been made to the data. Furthermore, weighting is not always stable, and resultant estimates may be unreliable due to extreme weights. These issues motivate the current development of novel propensity score stratification techniques to be used with continuous treatments. Specifically, the generalized propensity score cumulative distribution function (GPS-CDF) and the nonparametric GPS-CDF approaches are introduced. Empirical CDFs are used to stratify subjects based on pretreatment confounders in order to produce causal estimates. A detailed simulation study shows superiority of these new stratification methods based on the empirical CDF, when compared with standard weighting techniques. The proposed methods are applied to the "Mexican-American Tobacco use in Children" study to determine the causal relationship between continuous exposure to smoking imagery in movies, and smoking behavior among Mexican-American adolescents. These promising results provide investigators with new options for implementing continuous treatment propensity scoring.

sparrpowR: a flexible R package to estimate statistical power to identify spatial clustering of two groups and its application.

BACKGROUND: Cancer epidemiology studies require sufficient power to assess spatial relationships between exposures and cancer incidence accurately. However, methods for power calculations of spatial statistics are complicated and underdeveloped, and therefore underutilized by investigators. The spatial relative risk function, a cluster detection technique that detects spatial clusters of point-level data for two groups (e.g., cancer cases and controls, two exposure groups), is a commonly used spatial statistic but does not have a readily available power calculation for study design. RESULTS: We developed sparrpowR as an open-source R package to estimate the statistical power of the spatial relative risk function. sparrpowR generates simulated data applying user-defined parameters (e.g., sample size, locations) to detect spatial clusters with high statistical power. We present applications of sparrpowR that perform a power calculation for a study designed to detect a spatial cluster of incident cancer in relation to a point source of numerous environmental emissions. The conducted power calculations demonstrate the functionality and utility of sparrpowR to calculate the local power for spatial cluster detection. CONCLUSIONS: sparrpowR improves the current capacity of investigators to calculate the statistical power of spatial clusters, which assists in designing more efficient studies. This newly developed R package addresses a critically underdeveloped gap in cancer epidemiology by estimating statistical power for a common spatial cluster detection technique.

A novel approach for propensity score matching and stratification for multiple treatments: Application to an electronic health record-derived study.

Currently, methods for conducting multiple treatment propensity scoring in the presence of high-dimensional covariate spaces that result from "big data" are lacking-the most prominent method relies on inverse probability treatment weighting (IPTW). However, IPTW only utilizes one element of the generalized propensity score (GPS) vector, which can lead to a loss of information and inadequate covariate balance in the presence of multiple treatments. This limitation motivates the development of a novel propensity score method that uses the entire GPS vector to establish a scalar balancing score that, when adjusted for, achieves covariate balance in the presence of potentially high-dimensional covariates. Specifically, the generalized propensity score cumulative distribution function (GPS-CDF) method is introduced. A one-parameter power function fits the CDF of the GPS vector and a resulting scalar balancing score is used for matching and/or stratification. Simulation results show superior performance of the new method compared to IPTW both in achieving covariate balance and estimating average treatment effects in the presence of multiple treatments. The proposed approach is applied to a study derived from electronic medical records to determine the causal relationship between three different vasopressors and mortality in patients with non-traumatic aneurysmal subarachnoid hemorrhage. Results suggest that the GPS-CDF method performs well when applied to large observational studies with multiple treatments that have large covariate spaces.

A review of patient questions from physicist-patient consults.

PURPOSE: To provide insight into the types of questions asked to medical physicists by patients during one-on-one physicist-patient consults at one institution. MATERIALS AND METHODS: Medical physicists trained in patient communication techniques met with patients to provide an overview of the treatment planning and delivery processes, discuss the patient's treatment plan, and answer any technical questions. From August 2016 to December 2019, 152 physicist-patient consults were conducted. In the initial months of the study (August 2016-December 2017), following each physicist-patient consult, all patient questions were documented by the physicists. For the remaining time period (January 2018-December 2019), any newly encountered questions were periodically added to the list. The questions were compiled into a comprehensive list and organized into categories. RESULTS: There were a total of 88 unique patient questions. These questions fit into four topical categories. Fifty-four questions (61.4%) were in the "Treatment Planning and Delivery Questions" category, 15 questions (17.1%) were in the "General Radiation Questions or Concerns" category, 13 questions (14.8%) were in the "Safety and Quality Assurance Questions" category, and 6 questions (6.8%) were in the "Medical Questions" category. Overall, patients were primarily concerned about how radiation works, the treatment planning and delivery processes, and what is being done to keep them safe throughout their treatment. CONCLUSION: Physicist-patient consults provided an opportunity to address the technical aspects of radiation therapy with patients in greater detail. The fact that patient questions could be conveniently grouped into only four topical categories indicates that it may be straightforward for other medical physicists to prepare for effectively addressing technical questions during physicist-patient consults.

Global differences in the prevalence of the CpG island methylator phenotype of colorectal cancer.

BACKGROUND: CpG Island Methylator Phenotype (CIMP) is an epigenetic phenotype in CRC characterized by hypermethylation of CpG islands in promoter regions of tumor suppressor genes, leading to their transcriptional silencing and loss of function. While the prevalence of CRC differs across geographical regions, no studies have compared prevalence of CIMP-High phenotype across regions. The purpose of this project was to compare the prevalence of CIMP across geographical regions after adjusting for variations in methodologies to measure CIMP in a meta-analysis. METHODS: We searched PubMed, Medline, and Embase for articles focusing on CIMP published from 2000 to 2018. Two reviewers independently identified 111 articles to be included in final meta-analysis. We classified methods used to quantify CIMP into 4 categories: a) Classical (MINT marker) Panel group b) Weisenberg-Ogino (W-O) group c) Human Methylation Arrays group and d) Miscellaneous group. We compared the prevalence of CIMP across geographical regions after correcting for methodological variations using meta-regression techniques. RESULTS: The pooled prevalence of CIMP-High across all studies was 22% (95% confidence interval:21-24%; I2 = 94.75%). Pooled prevalence of CIMP-H across Asia, Australia, Europe, North America and South America was 22, 21, 21, 27 and 25%, respectively. Meta-regression analysis identified no significant differences in the prevalence of CIMP-H across geographical regions after correction for methodological variations. In exploratory analysis, we observed variations in CIMP-H prevalence across countries. CONCLUSION: Although no differences were found for CIMP-H prevalence across countries, further studies are needed to compare the influence of demographic, lifestyle and environmental factors in relation to the prevalence of CIMP across geographical regions.

Characterizing red blood cell age exposure in massive transfusion therapy: the scalar age of blood index (SBI).

BACKGROUND: The mortality of trauma patients requiring massive transfusion to treat hemorrhagic shock approaches 17% at 24 hours and 26% at 30 days. The use of stored RBCs is limited to less than 42 days, so older RBCs are delivered first to rapidly bleeding trauma patients. Patients who receive a greater quantity of older RBCs may have a higher risk for mortality. METHODS AND MATERIALS: Characterizing blood age exposure requires accounting for the age of each RBC unit and the quantity of transfused units. To address this challenge, a novel Scalar Age of Blood Index (SBI) that represents the relative distribution of RBCs received is introduced and applied to a secondary analysis of the Pragmatic, Randomized Optimal Platelet and Plasma Ratios (PROPPR) randomized controlled trial (NCT01545232, https://clinicaltrials.gov/ct2/show/NCT01545232). The effect of the SBI is assessed on the primary PROPPR outcome, 24-hour and 30-day mortality. RESULTS: The distributions of blood storage ages successfully maps to a parameter (SBI) that fully defines the blood age curve for each patient. SBI was a significant predictor of 24-hour and 30-day mortality in an adjusted model that had strong predictive ability (odds ratio, 1.15 [1.01-1.29], p = 0.029, C-statistic, 0.81; odds ratio, 1.14 [1.02-1.28], p = 0.019, C-statistic, 0.88, respectively). CONCLUSION: SBI is a simple scalar metric of blood age that accounts for the relative distribution of RBCs among age categories. Transfusion of older RBCs is associated with 24-hour and 30-day mortality, after adjustment for total units and clinical covariates.

Sensitivity of the Mount Fuji Sign After Evacuation of Chronic Subdural Hematoma in Nonagenarians.

BACKGROUND: The Mount Fuji sign (MFS) is a radiological sign on computed tomographic scans depicting air between the frontal lobes. Air in this location indicates tension pneumocephalus (TP), considered a neurosurgical emergency.We evaluate the correlation between the MFS and perioperative mortality attributed to TP in nonagenarians who have undergone evacuation of chronic subdural hemorrhage (cSDH). MATERIALS AND METHODS: We retrospectively reviewed the records of nonagenarians who had cSDH evacuation between 2006 and 2015. Postoperative computed tomographic images were evaluated for findings consistent with the MFS. RESULTS: Of 45 patients, 15 patients (33%) had radiological MFS, and 3 patients (20%) with MFS required reoperation because of new blood collection. No patient required reoperation because of TP. Perioperative (30-day) mortality in patients demonstrating the MFS was 6.67% caused by cardiac arrhythmia versus 13.33% mortality in patients with no evidence of the MFS. CONCLUSION: Mount Fuji sign in nonagenarians after cSDH evacuation is not a specific sign of TP.

A program to train medical physicists for direct patient care responsibilities.

OBJECTIVES: To develop a training program designed to meet the specific needs of medical physicists as they transition into a clinical role with direct patient care responsibilities. MATERIALS AND METHODS: The training program was designed in collaboration with the faculty at the UC San Diego School of Medicine and incorporates training techniques that have been shown to be effective in improving communication skills. The program emphasizes experiential, practice-based learning over didactic presentations. RESULTS: The training program is comprised of 5 components: 1) a 1-day Clinician-Patient Communication Workshop run by the UC San Diego School of Medicine, 2) Communication Strategies for Radiation Oncology, which consists of two, 2-hour sessions designed to provide trainees with patient communication skills that are specific to patient interactions in radiation oncology, 3) Simulated Patient Interactions, in which trainees perform mock physicist-patient consults with trained patient actors, 4) Faculty-Observed Patient Consults, and 5) a Case-Based Treatment Toxicity Course. A competency assessment mechanism was also developed to provide a clear set of objectives and to guide trainer feedback. [Correction added after first online publication on November 7, 2018: The phrase ", which consists of two, 2-hour" was added above.] CONCLUSIONS: The training program that we have developed incorporates an array of established education techniques and provides a comprehensive, accessible, means of improving medical physicists' patient communication skills.

Two-dimensional in vivo dose verification using portal imaging and correlation ratios.

The electronic portal imaging device (EPID) has the potential to be used for in vivo dosimetry during radiation therapy as an additional dose delivery check. In this study we have extended a method developed by A. Piermattei and colleagues in 2006 that made use of EPID transit images (acquired during treatment) to calculate dose in the isocenter point. The extension allows calculation of two-dimensional dose maps of the entire radiation field at the depth of isocenter. We quantified the variability of the ratio of EPID signal to dose in the isocenter plane in Solid Water phantoms of various thicknesses and with various field sizes, and designed a field edge dose calculation correction. To validate the method, we designed three realistic conventional radiation therapy treatment plans on a thorax and head anthropomorphic phantom (whole brain, brain primary, lung tumor). Using CT data, EPID transit images, EPID signal-to-dose correlation, and our edge correction, we calculated dose in the isocenter plane and compared it with the treatment planning system's prediction. Gamma evaluation (3%, 3 mm) showed good agreement (Pγ<1 ≥ 96.5%) for all fields of the whole brain and brain primary plans. In the presence of lung, however, our algorithm overestimated dose by 7%-9%. This 2D EPID-based in vivo dosimetry method can be used for posttreatment dose verification, thereby improving the safety and quality of patient treatments. With future work, it may be extended to measure dose in real time and to prevent harmful delivery errors.

Measurement of ctDNA Tumor Fraction Identifies Informative Negative Liquid Biopsy Results and Informs Value of Tissue Confirmation.

PURPOSE: Liquid biopsy (LBx) for tumor profiling is increasingly used, but concerns remain regarding negative results. A lack of results may truly reflect tumor genomics, or it may be a false negative that would be clarified by tissue testing. A method of distinguishing between these scenarios could help clarify when follow-on tissue testing is valuable. EXPERIMENTAL DESIGN: Here we evaluate circulating tumor DNA (ctDNA) tumor fraction (TF), a quantification of ctDNA in LBx samples, for utility in identifying true negative results. We assessed concordance between LBx and tissue-based results, stratified by ctDNA TF, in a real-world genomic dataset of paired samples across multiple disease types. We also evaluated the frequency of tissue results identifying driver alterations in patients with lung cancer after negative LBx in a real-world clinicogenomic database. RESULTS: The positive percent agreement and negative predictive value between liquid and tissue samples for driver alterations increased from 63% and 66% for all samples to 98% and 97% in samples with ctDNA TF ≥1%. Among 505 patients with lung cancer with no targetable driver alterations found by LBx who had subsequent tissue-based profiling, 37% had a driver, all of which had ctDNA TF <1%. CONCLUSIONS: Patients with lung cancer with negative LBx and ctDNA TF ≥1% are unlikely to have a driver detected on confirmatory tissue testing; such informative negative results may benefit instead from prompt treatment initiation. Conversely, negative LBx with ctDNA TF <1% will commonly have a driver identified by follow-up tissue testing and should be prioritized for reflex testing.

Clonal hematopoiesis due to mosaic chromosomal alterations: Impact on disease risk and mortality.

Mosaic chromosomal alterations (mCAs) are the clonal expansion of large somatically acquired structural chromosomal changes present on the autosomes and sex chromosomes. Most studies of mCAs use existing genotype array intensity data from large populations to investigate potential risk factors and disease outcomes associated with mCAs. In this review, we perform a comprehensive examination of existing evidence for mCA disease and mortality associations and provide a framework for interpreting these associations in the context of important biases specific to mCA studies. Our goal is to motivate well-designed mCA studies to assist in unlocking the potential of mCAs to improve understanding of the effects of ageing and accelerate translational applications for improving public health.

Mosaic chromosomal alterations detected in men living with HIV and the relationship to non-Hodgkin lymphoma.

OBJECTIVES: People with HIV (PWH) have an elevated risk of non-Hodgkin lymphoma (NHL) and other diseases. Studying clonal hematopoiesis (CH), the clonal expansion of mutated hematopoietic stem cells, could provide insights regarding elevated NHL risk. DESIGN: Cohort analysis of participants in the Multicenter AIDS Cohort Study ( N  = 5979). METHODS: Mosaic chromosomal alterations (mCAs), a type of CH, were detected from genotyping array data using MoChA. We compared CH prevalence in men with HIV (MWH) to HIV-uninfected men using logistic regression, and among MWH, assessed the associations of CH with NHL incidence and overall mortality using Poisson regression. RESULTS: Comparing MWH to HIV-uninfected men, we observed no difference in the frequency of autosomal mCAs (3.9% vs. 3.6%, P -value = 0.09) or mosaic loss of the Y chromosome (mLOY) (1.4% vs. 2.9%, P -value = 0.13). Autosomal mCAs involving copy-neutral loss of heterozygosity (CN-LOH) of chromosome 14q were more common in MWH. Among MWH, mCAs were not associated with subsequent NHL incidence (autosomal mCA P -value = 0.65, mLOY P -value = 0.48). However, two MWH with diffuse large B-cell lymphoma had overlapping CN-LOH mCAs on chromosome 19 spanning U2AF2 (involved in RNA splicing), and one MWH with Burkitt lymphoma had high-frequency mCAs involving chromosome 1 gain and chromosome 17 CN-LOH (cell fractions 22.1% and 25.0%, respectively). mCAs were not associated with mortality among MWH (autosomal mCA P -value = 0.52, mLOY P -value = 0.93). CONCLUSIONS: We found limited evidence for a relationship between HIV infection and mCAs. Although mCAs were not significantly associated with NHL, mCAs detected in several NHL cases indicate a need for further investigation.

Examining the Effect of Direct Patient Care for Medical Physicists: A Randomized Prospective Phase III Trial.

PURPOSE: Our purpose was to investigate the effect of physicist-patient consults on patient anxiety and patient satisfaction with a randomized prospective phase III clinical trial. METHODS AND MATERIALS: Sixty-six patients were randomly assigned to the physics direct patient care (PDPC) arm or the control arm of the trial. Patients assigned to the PDPC arm received 2 physicist-patient consults to educate them on the technical aspects of their radiation therapy, while patients assigned to the control arm received the standard of care (ie, standard radiation therapy workflow without any additional physicist-patient consults). Questionnaires were administered to all patients at 4 time points (after enrollment, after the simulation, after the first treatment, and after the last treatment) to assess anxiety and satisfaction. RESULTS: The decrease in anxiety for the PDPC arm, compared with the control arm, was statistically significant at the first treatment (P = .027) time point. The increase in technical satisfaction for the PDPC arm, compared with the control arm, was statistically significant at the simulation (P = .005), first treatment (P < .001), and last treatment (P = .002) time points. The increase in overall satisfaction for the PDPC arm, compared with the control arm, was statistically significant at the first treatment (P = .014) and last treatment (P = .001) time points. CONCLUSIONS: Physicist-patient consults improved the patient experience by decreasing anxiety and increasing satisfaction. Future work is needed to modify current radiation oncology workflows and medical physics responsibilities to allow all patients to benefit from this advancement in patient care.