Online Advertising and Marketing Claims by Providers of Proton Beam Therapy: Are They Guideline Based?

Abstract

Purpose/Objective(s): To correlate parameters derived from apparent diffusion coefficient (ADC) volumes associated with the changes in specified abnormal white matter (WM) to overall survival (OS) following therapies in glioblastoma (GBM). The unsupervised machine learning was designed to reduce uncertainties on a relatively small size data for a prediction model. Materials/Methods: The study employed 41 GBM patients treated with radiotherapy (60 Gy) followed by Temozolomide. The ADC ranges for normal WM and gray matter (GM) were established from a pool of ADC voxels over 66 individual brains. The predictors were the averaged values of pre/post treated (TX) over the masked volumes, where (abnormal) pre-TX WMs were in normal GM ADC range, then applied the mask to the post-TX volume. The learning process has 2 main parts: (1) the probability of mapping from predictors to OS, (2) data resampling extracted the features of the mapping in parametric space with different complex levels of models. The number of coefficients in linear models can be from 3 to 7 (or more) for higher complexity. The probability was based on Bayesian with likelihood probability from institutional data and the prior information from published OS reports. The data were resampled with total number and location of datapoints being altered with bandwidth of kernel density estimation, cluster analysis in parametric space. Results: The characterized ADC volumes(1) provide more objective parameters for machine learning than manually contoured clinical tumor volume (CTV), (2) are within the sampled ADC volume based on FLAIR & T1-post highlighted regions, where the ADC histogram illustrates a unique pattern of pre-/post-TX dynamics; i.e. "WM looking like GM before treatment". Without resampling in the learning process, the predicted OS had 0.57 of correlation coefficient (CC) with the data fitted with the simpler model. The model underestimated survival at late time points (>450 days) and overestimated survival in early time points. With resampling, the model CC improved (CC w 0.65) secondary to outlier suppression at later time points (survival: 200w450 days). The use of more sophisticated models did not improve the model fit. Conclusion: The subtle changes detected by ADC parameters could not be accurately quantified by T1, T2 or FLAIR suggesting that ADC offers additional information useful for prognostication. Despite high uncertainties presented in the small dataset, the correlation was non-trivial, and it can also be enhanced further with the learning process to feature the given data and a priori. Because the WM scaled as GM by ADC indicates WM abnormities, the relation of "quantitative abnormity" with OS could be pathologically meaningful. The algorithm appears to represent an optimum on the likely feature that data given as more complex models were limited by the small data size.Purpose/Objective(s): Stereotactic body radiation therapy (SBRT) has become an acceptable treatment modality for medically inoperable stage I non-small cell lung cance...

General and Health-Related Internet Use Among Cancer Survivors in the United States: A 2013–2018 Cross-Sectional Analysis

“…Although the internet may contain useful health information, the quality of many websites is unregulated. [14][15][16][17][18][19]22,45,46 Perhaps ironically, peer-reviewed medical information, such as in the form of journal articles or society guidelines, may be financially restricted and therefore not easily accessible to the general population. Given that misinformation or inappropriate interpretation of information may impact health-related choices among patients with cancer, [23][24][25] our finding of increasing healthspecific internet use among cancer survivors with later year of survey underscores the value of improving the quality of health information websites.…”

“…12 Although medically sponsored websites with evidencebased guidelines exist, the internet can also serve as a platform for dissemination of potentially harmful medical misinformation. 11,13 Studies regarding the quality of online health information in oncology [14][15][16][17] and other fields 18,19 have shown the accuracy of such pages to be variable, with many online resources with poor-quality information garnering high-volume readership. 20 In addition, commercial websites, some of which are run by companies that pay to rank themselves among the top hits for healthrelated searches, 18 may provide information biased toward the use of particular products or treatments.…”

Overall Survival After Treatment of Localized Prostate Cancer With Proton Beam Therapy, External-Beam Photon Therapy, or Brachytherapy

“…For men with prostate cancer, proton therapy treatment plans typically reduce the radiation dose to the rectum, bladder, and other nontarget normal pelvic tissues relative to photon-based EBRT using intensity-modulated radiotherapy (IMRT), 7 although singleinstitution retrospective studies have not identified a measurable difference in physician-assessed acute or late toxicities. 8,9 While proton therapy represents a small percentage of radiation therapy treatments for prostate cancer and remains a relatively scarce resource, the growth in proton therapy from approximately 2% to 5% of EBRT cases between 2004 to 2012, 10 the increased cost of treatment, 11 the increasing number of proton centers, the sometimes questionable marketing claims, 12 and the lack of randomized data demonstrating its superiority to alternative treatments for prostate cancer have underscored the scrutiny this treatment modality continues to receive. Previous population-based analyses from the Surveillance, Epidemiology, and End Results (SEER) database, a linked SEER-Medicare analysis, and the MarketScan Commercial Claims and Encounters database have reached conflicting conclusions about the acute and late toxicity profile of proton therapy relative to IMRT.…”

Back to the XXIII Russian oncology congress: will radiotherapy soon become entirely the proton one?

“…Поэтому миф, что протоны эффективнее и безопаснее -всего лишь миф, но становящийся религией. По данным постера, представленного на ASCO 2019 канадскими авторами [52], вебсайты центров протонной терапии вводят больных в заблуждение, утверждая, что протоны повышают шанс излечивания (61 % утверждений), минимизируют осложнения (85 %) и приводят к улучшению качества жизни (39 %).…”