Attitudes and access to resources and strategies to improve quality of radiotherapy among US radiation oncologists: A mixed methods study

INTRODUCTION

We aimed to assess contouring-related practices among US radiation oncologists and explore how access to and use of resources and quality improvement strategies vary based on individual- and organization-level factors.

METHODS

We conducted a mixed methods study with a sequential explanatory design. Surveys were emailed to a random 10% sample of practicing US radiation oncologists. Participating physicians were invited to a semi-structured interview. Kruskal-Wallis and Wilcoxon rank-sum tests and a multivariable regression model were used to evaluate associations. Interview data were coded using thematic content analysis.

RESULTS

Survey overall response rate was 24%, and subsequent completion rate was 97%. Contouring-related questions arise in ≥50% of clinical cases among 73% of respondents. Resources accessed first include published atlases (75%) followed by consulting another radiation oncologist (60%). Generalists access consensus guidelines more often than disease-site specialists (P = 0.04), while eContour.org is more often used by generalists (OR 4.3, 95% CI 1.2-14.8) and younger physicians (OR 1.33 for each 5-year increase, 95% CI 1.08-1.67). Common physician-reported barriers to optimizing contour quality are time constraints (58%) and lack of access to disease-site specialists (21%). Forty percent (40%, n = 14) of physicians without access to disease-site specialists indicated it could facilitate the adoption of new treatments. Almost all (97%) respondents have formal peer review, but only 43% have contour-specific review, which is more common in academic centres (P = 0.02).

CONCLUSION

Potential opportunities to improve radiation contour quality include improved access to disease-site specialists and contour-specific peer review. Physician time must be considered when designing new strategies.

Radiation oncologist perceptions of therapeutic cannabis use among cancer patients

INTRODUCTION

Cancer patients are increasingly incorporating medical marijuana into the management of treatment-related side effects. Currently however, data is limited regarding the risks and benefits of therapeutic cannabis for cancer patients. We sought to characterize radiation oncologists' practices and opinions regarding therapeutic cannabis via a nationwide survey.

MATERIALS AND METHODS

An anonymous survey was distributed via email to 873 radiation oncologists in the American Society for Radiation Oncology member database. Radiation oncologists were asked their opinions and practices regarding the use of therapeutic cannabis for their patients. Bivariate analyses of potential predictors for responses were conducted using standard statistical techniques.

RESULTS

One hundred seven radiation oncologists completed the survey. According to the survey, 36% of respondents would recommend therapeutic cannabis to their patients to mitigate treatment toxicity. Physicians practicing in states where medical marijuana is legal were more likely to recommend it compared to physicians working in states that have not legalized medical marijuana (OR = 3.79, 1.19-12.1, p = 0.01). Seventy-one percent of respondents reported therapeutic cannabis as being effective at least some of the time for managing treatment-related toxicities. Fifty-eight percent of physicians reported lacking sufficient knowledge to advise patients regarding therapeutic cannabis, while 86% of respondents were interested in learning more about therapeutic cannabis for cancer patients.

CONCLUSIONS

Although a majority of radiation oncologists believe there are benefits to therapeutic cannabis, many are hesitant to recommend for or against its use. Radiation oncologists appear to be interested in learning more about how therapeutic cannabis may play a role in their patients' care.

Abstract P2-09-01: Patient reported outcomes of multiplex breast cancer susceptibility testing utilizing a tiered-binned counseling and informed consent model in BRCA1/2 negative patients

Background:The risks, benefits and utilities of multiplex panels for breast cancer susceptibility are unknown and new counseling and informed consent models are needed. We sought to obtain patient reported outcomes of multiplex testing in BRCA1/2 negative patients utilizing a novel, previously piloted tiered-binned counseling model for multiplex testing. Methods:BRCA1/2 negative participants completed pre(V1) and post-test counseling(V2) and surveys evaluating cognitive, affective and behavioral responses to a 25-gene multiplex testing panel. We used linear regressions with estimation by GEE where appropriate. Results:376 patients have been approached. To date, 124 participants(33%) have consented to the study, 21(6%) declined and 231(61%) are considering. Of 95 who have completed pre-test counseling(V1), 88(93%) elected to proceed with 25-gene panel testing and (81%) were classified as making an informed choice after tiered-binned counseling. 6/53(11%) participants received a positive result, including 1 mutation in MSH2 and 5 in moderate penetrance genes (2 ATM, 1 BARD1, 1 CHEK2, 1 PALB2). 22/53(42%) participants received a variant of unknown significance(VUS). General anxiety and perceived utility decreased significantly with pre-test counseling and after results (Table 1). Knowledge increased with pre-test counseling; cancer worry increased after receipt of multiplex results. Higher cancer worry was associated only with lower income (2.6 points/income category, p<0.01). Those with a VUS had greater decreases in perceived utility compared to negative (p=0.01) or positive (p=0.003) results. To date, there are no other significant differences in knowledge, distress or uncertainty by test result. Medical management recommendations for the proband changed in 3/6 with a positive result. Cascade testing in the family was discussed as an option in 3/6 with a positive result. Conclusions:Many BRCA1/2-negative patients proceed with 25-gene cancer susceptibility testing if offered and most make informed choices utilizing a tiered-binned genetic counseling model. The tiered-binned counseling model is associated with increased knowledge, decreases in general anxiety and uncertainty after pre-test counseling and disclosure of results, but an increase in cancer worry after result disclosure. The clinical utility, long-term outcomes and differences in patient reported outcomes by test result remain unknown.

Table 1 Baseline, Mean(SD)After V1, Mean(SD)After V2, Mean(SD) N=75ˆ;N=49ˆˆN=75ˆ;N=49ˆˆN=49ˆˆGeneral Anxiety (range 0-21)6.4(3.9)*;6.9(3.9)**6.0(4.3)*;6.6(4.2)**5.8(4.5)**General Depression (range 0-212.8(2.9);3.1(3.2)3.0(3.5);3.1(3.6)3.0(3.7)State Anxiety (range 20-80)35.5(11.2);36.6(11.9)35.5(11.8);36.8(11.9)36.1(12.2)Cancer Worry (range 0-75)18.2(13.5);20.1(13.8)**16.7(12.5);17.2(11.9)**21.0(13.9)**Knowledge (range 17-82)65.7(5.0)**;66.5(5.0)**68.0(5.7)**;68.4(5.6)**67.3(4.9)**Uncertainty (range 0-15)5.8(3.9);6.2(4.3)5.6(3.7);5.4(3.2)5.6(3.5)Perceived Utility (range 24-120)75.2(14.0)*;75.9(14.0)**73.0(14.1)*;74.1(13.4)**68.4(16.9)***p≤0.05 **p≤0.01. ˆcompleted V1. ˆˆcompleted V1 & V2. To date, 53 have received results and 49 have completed post-disclosure surveys.

Citation Format: Bradbury AR, Patrick-Miller L, Egleston BE, Maxwell KN, Brandt A, Brower J, DiGiovanni L, Long JM, Powers J, Stopfer J, Nathanson KL, Domchek SM. Patient reported outcomes of multiplex breast cancer susceptibility testing utilizing a tiered-binned counseling and informed consent model in BRCA1/2 negative patients. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-09-01.

The National Environmental Respiratory Center (NERC) experiment in multi-pollutant air quality health research: IV. Vascular effects of repeated inhalation exposure to a mixture of five inorganic gases

An experiment was conducted to test the hypothesis that a mixture of five inorganic gases could reproduce certain central vascular effects of repeated inhalation exposure of apolipoprotein E-deficient mice to diesel or gasoline engine exhaust. The hypothesis resulted from preceding multiple additive regression tree (MART) analysis of a composition-concentration-response database of mice exposed by inhalation to the exhausts and other complex mixtures. The five gases were the predictors most important to MART models best fitting the vascular responses. Mice on high-fat diet were exposed 6 h/d, 7 d/week for 50 d to clean air or a mixture containing 30.6 ppm CO, 20.5 ppm NO, 1.4 ppm NO₂, 0.5 ppm SO₂, and 2.0 ppm NH₃ in air. The gas concentrations were below the maxima in the preceding studies but in the range of those in exhaust exposure levels that caused significant effects. Five indicators of stress and pro-atherosclerotic responses were measured in aortic tissue. The exposure increased all five response indicators, with the magnitude of effect and statistical significance varying among the indicators and depending on inclusion or exclusion of an apparent outlying control. With the outlier excluded, three responses approximated predicted values and two fell below predictions. The results generally supported evidence that the five gases drove the effects of exhaust, and thus supported the potential of the MART approach for identifying putative causal components of complex mixtures.

Measurement of the electric form factor of the neutron at Q2=0.5 and 1.0 GeV2/c2

The electric form factor of the neutron was determined from measurements of the d-->(e-->,e'n)p reaction for quasielastic kinematics. Polarized electrons were scattered off a polarized deuterated ammonia (15ND3) target in which the deuteron polarization was perpendicular to the momentum transfer. The scattered electrons were detected in a magnetic spectrometer in coincidence with neutrons in a large solid angle detector. We find G(n)(E)=0.0526+/-0.0033(stat)+/-0.0026(sys) and 0.0454+/-0.0054+/-0.0037 at Q(2)=0.5 and 1.0 (GeV/c)(2), respectively.

Application of a pruning algorithm to optimize artificial neural networks for pharmaceutical fingerprinting

The present study investigates an application of artificial neural networks (ANNs) for use in pharmaceutical fingerprinting. Several pruning algorithms were applied to decrease the dimension of the input parameter data set. A localized fingerprint region was identified within the original input parameter space from which a subset of input parameters was extracted leading to enhanced ANN performance. The present results confirm that ANNs can provide a fast, accurate, and consistent methodology applicable to pharmaceutical fingerprinting.

Preprocessing of HPLC trace impurity patterns by wavelet packets for pharmaceutical fingerprinting using artificial neural networks

The immediate objective of this research program is to evaluate several computer-based classifiers as potential tools for pharmaceutical fingerprinting based on analysis of HPLC trace organic impurity patterns. In the present study, wavelet packets (WPs) are investigated for use as a preprocessor of the chromatographic data taken from commercial samples of L-tryptophan (LT) to extract input data appropriate for classifying the samples according to manufacturer using artificial neural networks (ANNs) and the standard classifiers KNN and SIMCA. Using the Haar function, WP decompositions for levels L = 0-10 were generated for the trace impurity patterns of 253 chromatograms corresponding to LT samples that had been produced by six commercial manufacturers. Input sets of N = 20, 30, 40, and 50 inputs were constructed, each one consisting of the first N/2 WP coefficents and corresponding positions from the overall best level (L = 2). The number of hidden nodes in the ANNs was also varied to optimize performance. Optimal ANN performance based on percent correct classifications of test set data was achieved by ANN-30-30-6 (97%) and ANN-20-10-6 (94%), where the integers refer to the numbers of input, hidden, and output nodes, respectively. This performance equals or exceeds that obtained previously (Welsh, W.J.; et al.Anal.Chem. 1996, 68, 3473) using 46 inputs from a so-called Window preprocessor (93%). KNN performance with 20 inputs (97%) or 30 inputs (90%) from the WP preprocessor also exceeded that obtained from the Window preprocessor (85%), while SIMCA performance with 20 inputs (86%) or 30 inputs (82%) from the WP preprocessor was slightly inferior to that obtained from the Window preprocessor (87%). These results indicate that, at least for the ANN and KNN classifiers considered here, the WP preprocessor can yield superior performance and with fewer inputs compared to the Window preprocessor.

Pharmaceutical fingerprinting: evaluation of neural networks and chemometric techniques for distinguishing among same-product manufacturers

The present study was undertaken to evaluate several computer-based classifiers as potential tools for pharmaceutical fingerprinting by utilizing normalized data obtained from HPLC trace organic impurity patterns. To assess the utility of this approach, samples of L-tryptophan (LT) drug substance were analyzed from commercial production lots of six different manufacturers. The performance of several artificial neural network (ANN) architectures was compared with that of two standard chemometric methods, K-nearest neighbors (KNN) and soft independent modeling of class analogy (SIMCA), as well as with a panel of human experts. The architecture of all three computer-based classifiers was varied with respect to the number of input variables. The ANNs were also optimized with respect to the number of nodes per hidden layer and to the number of hidden layers. A novel preprocessing scheme known as the Window method was devised for converting the output of 899 data entries extracted from each chromatogram into an appropriate input file for the classifiers. Analysis of the test set data revealed that an ANN with 46 inputs (i.e., ANN-46) was superior to all other classifiers evaluated, with 93% of the chromatograms correctly classified. Among the classifiers studied in detail, the order of performance was ANN-46 (93%) > SIMCA-46 (87%) > KNN-46 (85%) = ANN-899 (85%) > "human experts" (83%) > SIMCA-899 (78%) > or = ANN-22 (77%) = KNN-22 (77%) > or = KNN-899 (76%) > SIMCA-22 (73%). These results confirm that ANNs, particularly when used in conjunction with the Window preprocessing scheme, can provide a fast, accurate, and consistent methodology applicable to pharmaceutical fingerprinting. Particular attention was paid to variations in the HPLC patterns of same-manufacturer samples due to differences in LT production lots, HPLC columns, and even run-days to quantify how these factors might hinder correct classifications. The results from these classification studies indicate that the chromatograms evidenced variations across LT manufacturers, across the three HPLC columns and, for one manufacturer, across lots. The extent of column-to-column variations is particularly noteworthy in that all three columns had identical specifications with respect to their stationary-phase characteristics and two of the three columns were from the same vendor.