Lessons From Large-Scale Collection of Patient-Reported Outcomes: Implications for Big Data Aggregation and Analytics

The Performance of Kaizen Tasks Across Three Online Discrete Choice Experiment Surveys: An Evidence Synthesis

BACKGROUND

Kaizen is a Japanese term for continuous improvement (kai ~ change, zen ~ good). In a kaizen task, a respondent makes sequential choices to improve an object's profile, revealing a preference path. Including kaizen tasks in a discrete choice experiment has the advantage of collecting greater preference evidence than pick-one tasks, such as paired comparisons. OBJECTIVE AND METHODS: So far, three online discrete choice experiments have included kaizen tasks: the 2020 US COVID-19 vaccination (CVP) study, the 2021 UK Children's Surgery Outcome Reporting (CSOR) study, and the 2023 US EQ-5D-Y-3L valuation (Y-3L) study. In this evidence synthesis, we describe the performance of the kaizen tasks in terms of response behaviors, conditional logit and Zermelo-Bradley-Terry (ZBT) estimates, and their standard errors in each of the surveys.

RESULTS

Comparing the CVP and Y-3L, including hold-outs (i.e., attributes shared by all alternatives) seems to reduce positional behavior by half. The CVP tasks excluded multi-level improvements; therefore, we could not estimate logit main effects directly. In the CSOR, only 12 of the 21 logit estimates are significantly positive (p < 0.05), possibly due to the fixed attribute order. All Y-3L estimates are significantly positive, and their predictions are highly correlated (Pearson: logit 0.802, ZBT 0.882) and strongly agree (Lin: logit 0.744, ZBT 0.852) with the paired-comparison probabilities.

CONCLUSIONS

These discrete choice experiments offer important lessons for future studies: (1) include warm-up tasks, hold-outs, and multi-level improvements; (2) randomize the attribute order (i.e., up-down) at the respondent level; and (3) recruit smaller samples of respondents than traditional discrete choice experiments with only pick-one tasks.

Pain prevalence, intensity, and association with neuropsychiatric symptoms of dementia in immigrant and non-immigrant aged care residents in Australia

Pain recognition for culturally diverse people is complex as pain experience is subjective and influenced by cultural background. We compared the prevalence, intensity, and association of pain with neuropsychiatric symptoms (NPS) between immigrants and non-immigrants living with dementia in residential aged care homes (RACHs) who were referred to two Dementia Support Australia programs. Immigrant status was defined by the documented country of birth. Pain and NPS were assessed using PainChek® and the Neuropsychiatric Inventory, respectively. Subgroup analyses were also completed for English-speaking and non-English-speaking immigrants. A total of 17,637 referrals [immigrants, n = 6340; non-immigrants, n = 11,297] from 2792 RACHs were included. There were no significant differences for the prevalence of pain across all groups. Immigrants were slightly more likely to have moderate pain or severe pain than non-immigrants. Non-English-speaking immigrants had 0.5 points higher total pain scores on average (Cohen's d = 0.10 [0.05, 0.15], p < 0.001) than non-immigrants. Total pain score had a significant effect on total NPS severity scores in all groups. While pain prevalence is similar across groups, higher pain intensities are more common among immigrants living with dementia. Increased care staff awareness, education, and training about the potential effect of culture on pain expression is needed.

Comparing clinico-demographics and neuropsychiatric symptoms for immigrant and non-immigrant aged care residents living with dementia: a retrospective cross-sectional study from an Australian dementia-specific support service

BACKGROUND

Neuropsychiatric symptoms of dementia such as agitation and aggression are common in people living with dementia. The presentation of neuropsychiatric symptoms is influenced by the cultural background of people living with dementia. Further, identifying factors contributing to neuropsychiatric symptoms may be complicated if people living with dementia are immigrants or from non-English-speaking backgrounds. Most of what is known about differences in neuropsychiatric symptoms between racial and ethnic groups living with dementia come from community-based samples. This study investigated differences in clinico-demographics and neuropsychiatric symptoms between immigrants and non-immigrants living with dementia in residential aged care homes who were referred to two Dementia Support Australia programs.

METHODS

This was a retrospective observational cross-sectional study from 2018 to 2022 using data extracted from the Dementia Support Australia database. Immigrant status was identified by documented country of birth. We conducted exploratory subgroup analyses for English-speaking or non-English-speaking immigrants in comparison to non-immigrants. Neuropsychiatric Inventory and PainChek® were used to assess neuropsychiatric symptoms of dementia and pain, respectively.

RESULTS

Of the 23,889 referrals, 36% were immigrants living with dementia. Immigrants were 0.8 years older than non-immigrants on average. Immigrants had a slightly higher prevalence of mixed dementia (9.5%) than non-immigrants (8.2%). Overall, the groups had no difference in the severity of neuropsychiatric symptoms and associated caregiver distress. However, there was a significant difference in the total number of neuropsychiatric inventory domains (Cohen's d = -0.06 [-0.09, - 0.02], p <.001) between non-English-speaking immigrants and non-immigrants. Immigrants were more likely to present with agitation/aggression, while non-immigrants were more likely to present with hallucinations. Factors contributing to neuropsychiatric symptoms were common between the groups, with language barriers and cultural considerations frequently endorsed for immigrants.

CONCLUSION

This study reveals a mixed picture of neuropsychiatric symptoms between immigrants and non-immigrants. However, due to the exploratory nature of the hypotheses, our findings need to be replicated in future studies to confirm any conclusions. There is a need for increased awareness on the impact of culture and language on neuropsychiatric symptoms for people receiving residential care. Future studies investigating neuropsychiatric symptoms in different immigrant groups will help increase our understanding of neuropsychiatric symptoms for all people.

Faces of Pain in Dementia: Learnings From a Real-World Study Using a Technology-Enabled Pain Assessment Tool

Pain is common in people living with dementia (PLWD), including those with limited verbal skills. Facial expressions are key behavioral indicators of the pain experience in this group. However, there is a lack of real-world studies to report the prevalence and associations of pain-relevant facial micro-expressions in PLWD. In this observational retrospective study, pain-related facial features were studied in a sample of 3,144 PLWD [mean age 83.3 years (SD = 9.0); 59.0% female] using the Face domain of PainChek®, a point-of-care medical device application. Pain assessments were completed by 389 users from two national dementia-specific care programs and 34 Australian aged care homes. Our analysis focused on the frequency, distribution, and associations of facial action units [AU(s)] with respect to various pain intensity groups. A total of 22,194 pain assessments were completed. Of the AUs present, AU7 (eyelid tightening) was the most frequent facial expression (48.6%) detected, followed by AU43 (closing eyes; 42.9%) and AU6 (cheek raising; 42.1%) during severe pain. AU20 (horizontal mouth stretch) was the most predictive facial action of higher pain scores. Eye-related AUs (AU6, AU7, AU43) and brow-related AUs (AU4) were more common than mouth-related AUs (e.g., AU20, AU25) during higher pain intensities. No significant effect was found for age or gender. These findings offer further understanding of facial expressions during clinical pain in PLWD and confirm the usefulness of artificial intelligence (AI)-enabled real-time analysis of the face as part of the assessment of pain in aged care clinical practice.

Patient-reported outcomes version of the common terminology criteria for adverse events and quality-of-life linear analogue self-assessment in breast cancer patients receiving radiation therapy: single-institution prospective registry

Purpose/objectives

We sought to investigate the impact of patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE) on overall quality-of-life (QOL) employing linear analogue self-assessment (LASA) in breast cancer (BC) patients undergoing radiation therapy (RT).

Materials/methods

All patients treated with RT for BC with curative intent from 2015 to 2019 at our institution were included. Breast specific PRO-CTCAE and overall QOL LASA questionnaires were administered at baseline, end-of-treatment, 3, 6, 12 months, and then annually. Minimal clinically important difference in overall QOL was a 10-point change in LASA. Hypofractionation was any treatment > 2 Gy per fraction. Mixed models for repeated measures were used to determine the association of PRO-CTCAE and overall QOL LASA.

Results

Three hundred thirty-one (331) patients with a median follow-up of 3.1 years (range 0.4–4.9) were included. Average overall QOL LASA scores were 78.5 at baseline, 79.8 at end-of-treatment, 79.8 at 3 months, 77.1 at 6 months, 79.4 at 12 months, and 79.7 at 24 months. On univariate analysis, patients reporting a grade ≥ 3 PRO-CTCAE had, on average, a 10.4-point reduction in overall LASA QOL (p < 0.0001). On multivariate analysis, not being treated with hypofractionation and higher BMI were predictive for worse overall LASA QOL with a 10-point reduction in LASA for patients reporting a grade ≥ 3 PRO-CTCAE (p < 0.0001).

Conclusions

Patients reporting a grade ≥ 3 PRO-CTCAE experienced statistically significant and clinically meaningful deterioration in overall QOL LASA. Hypofractionation improved QOL while higher BMI predicted for worse QOL. PRO-CTCAE should be integrated into future clinical trials.

Association of Fatigue and Outcomes in Advanced Cancer: An Analysis of Four SWOG Treatment Trials

PURPOSE

Patient-reported outcomes may be associated with cancer outcomes. We evaluated clinically significant fatigue (CSF), overall survival, adverse events (AEs), and quality of life (QOL) during cancer treatment.

METHODS

We compared outcomes in four phase II or III chemotherapy trials, two advanced non-small-cell lung cancer and two advanced hormone-refractory prostate cancer, with or without baseline CSF. CSF was defined as a rating of two or greater on the Functional Assessment of Cancer Therapy fatigue question or a European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 fatigue symptom score of 50% or greater. Survival was compared according to CSF using Kaplan-Meier estimates and Cox regression models. Differences in AE rates by CSF were assessed via chi-squared tests, and QOL changes from baseline to 3 months via linear regression.

RESULTS

Of 1,994 participants, 1,907 (median age 69 years, range: 32-91) had complete baseline QOL survey data, with 52% reporting CSF at baseline. For the two hormone-refractory prostate cancer studies, baseline CSF was associated with higher mortality rates, with adjusted hazard ratios of (95% CI, P value) 1.32 (1.13 to 1.55, P < .001) and 1.31 (1.02 to 1.67, P = .03) and with increased incidence of grade 3-5 constitutional (16.5% v 9.4%, P = .002; 13.9% v 6.3%, P = .002) and neurologic (11.7% v 6.1%, P = .006; 9.0% v 3.9%, P = .01) AEs, respectively. Baseline CSF was associated with a higher mortality rate in one non-small-cell lung cancer study: hazard ratio 1.44 and 1.04 to 2.00, P = .03.

CONCLUSION

Oncology trial participants with baseline CSF had poorer survival and experienced more AEs than participants without CSF. This indicates fatigue as an important baseline prognostic factor in oncology treatment trials.

Genetic Predictors of Chemotherapy-Induced Peripheral Neuropathy from Paclitaxel, Carboplatin and Oxaliplatin: NCCTG/Alliance N08C1, N08CA and N08CB Study

Chemotherapy-induced peripheral neuropathy (CIPN) is a common and potentially permanent adverse effect of chemotherapeutic agents including taxanes such as paclitaxel and platinum-based compounds such as oxaliplatin and carboplatin. Previous studies have suggested that genetics may impact the risk of CIPN. We conducted genome-wide association studies (GWASs) for CIPN in two independent populations who had completed European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ)-CIPN20 assessments (a CIPN-specific 20-item questionnaire which includes three scales that evaluate sensory, autonomic, and motor symptoms). The study population N08Cx included 692 participants from three clinical trials (North Central Cancer Treatment Group (NCCTG) N08C1, N08CA, and N08CB) who had been treated with paclitaxel, paclitaxel plus carboplatin, or oxaliplatin. The primary endpoint for the GWAS was the change from pre-chemotherapy CIPN20 sensory score to the worse score over the following 18 weeks. Study population The Mayo Clinic Breast Disease Registry (MCBDR) consisted of 381 Mayo Clinic Breast Disease Registry enrollees who had been treated with taxane or platinum-based chemotherapy. The primary endpoint for the GWAS assessed was the earliest CIPN20 sensory score available after the completion of chemotherapy. In multivariate model analyses, chemotherapy regimen (p = 3.0 × 10-8) and genetic ancestry (p = 0.007) were significantly associated with CIPN in the N08Cx population. Only age (p = 0.0004) was significantly associated with CIPN in the MCBDR population. The SNP most associated with CIPN was rs56360211 near PDE6C (p =7.92 × 10-8) in N08Cx and rs113807868 near TMEM150C in the MCBDR (p = 1.27 × 10-8). Due to a lack of replication, we cannot conclude that we identified any genetic predictors of CIPN.

An evaluation of the spread and scale of PatientToc™ from primary care to community pharmacy practice for the collection of patient-reported outcomes: A study protocol

BACKGROUND

Medication non-adherence is a problem of critical importance, affecting approximately 50% of all persons taking at least one regularly scheduled prescription medication and costing the United States more than $100 billion annually. Traditional data sources for identifying and resolving medication non-adherence in community pharmacies include prescription fill histories. However, medication possession does not necessarily mean patients are taking their medications as prescribed. Patient-reported outcomes (PROs), measuring adherence challenges pertaining to both remembering and intention to take medication, offer a rich data source for pharmacists and prescribers to use to resolve medication non-adherence. PatientToc™ is a PROs collection software developed to facilitate collection of PROs data from low-literacy and non-English speaking patients in Los Angeles.

OBJECTIVES

This study will evaluate the spread and scale of PatientToc™ from primary care to community pharmacies for the collection and use of PROs data pertaining to medication adherence.

METHODS

The following implementation and evaluation steps will be conducted: 1) a pre-implementation developmental formative evaluation to determine community pharmacy workflow and current practices for identifying and resolving medication non-adherence, potential barriers and facilitators to PatientToc™ implementation, and to create a draft implementation toolkit, 2) two plan-do-study-act cycles to refine an implementation toolkit for spreading and scaling implementation of PatientToc™ in community pharmacies, and 3) a comprehensive, theory-driven evaluation of the quality of care, implementation, and patient health outcomes of spreading and scaling PatientToc™ to community pharmacies.

EXPECTED IMPACT

This research will inform long-term collection and use of PROs data pertaining to medication adherence in community pharmacies.

Patient-reported quality-of-life outcomes in relation to provider-assessed adverse events during head and neck radiotherapy

Purpose

To assess the relationship between patient-reported quality-of-life (QOL) outcomes and provider-assessed adverse events (AEs) during head-and-neck (H&N) radiotherapy (RT).

Methods

Sixty-five patients undergoing H&N RT prospectively completed 12-domain linear analogue self-assessments (LASA) at baseline, before biweekly appointments, and at last week of RT. At the same time points, provider-assessed AEs were graded using Common Terminology Criteria for Adverse Events v4.0. LASA scores were stratified by maximum-grade AE and analyzed using Kruskal-Wallis methodology. Agreement between LASA scores and maximum-grade AE was assessed using Bland-Altman analysis.

Results

Patient-reported QOL outcomes showed clinically meaningful decreases in most domains, predominantly fatigue (77.8% of patients), social activity (75.4%), and overall QOL (74.2%). Provider-assessed AEs showed 100% grade 2 AE, 35.4% grade 3 AE, and 3.1% grade 4 AE. At baseline, patients with higher grade AEs reported worse physical well-being (WB) (P = .04). At week 1, the following QOL domains were worse for patients with higher grade AEs: overall QOL (P = .03), mental WB (P = .02), and physical WB (P = .03). Bland-Altman analysis showed that QOL scores were relatively worse than AE burden at baseline and relatively better at RT completion.

Conclusions

Worse QOL was associated with higher-grade AEs at baseline and early in RT. The impact of AEs on QOL appears to lessen with time. Patient-reported QOL outcomes and provider-assessed AEs provide complementary information.

Cosmetic assessment in brachytherapy (interventional radiotherapy) for breast cancer: A multidisciplinary review

PURPOSE

This review was to focus on breast brachytherapy cosmetic assessment methods state of the art and to define the advantages and disadvantages related to.

METHODS AND MATERIALS

We conducted a literature review of the major experience on breast brachytherapy cosmetic assessment methods in several databases (PubMed, Scopus, and Google Scholar databases). To identify the relevant works, a task force screened citations at title and abstract level to identify potentially relevant paper. An expert board reviewed and approved the text. The assessment systems were classified into three main groups: (1) the Oncological Toxicity Scales, (2) the Independent Patients Perspective Measures, (3) the Patient-Related Outcome Measures. Each cosmetic assessment method was evaluated following six parameters: (1) anatomical site, (2) advantages, (3) disadvantages, (4) subjective/objective, (5) quantitative/qualitative, (6) computers or pictures needs.

RESULTS

Eleven assessment methods were selected. Three methods were classified as Oncological Toxicity Scale, six in the Independent Patients Perspective Measures classification, and two as Patient-Related Outcome Measures. Six methods are subjective, while eight are objective. Four systems are classified as quantitative, four as qualitative while three both. Five systems need informatics support. Moreover, each method was discussed individually reporting the main characteristics and peculiarities.

CONCLUSIONS

Cosmesis is one major end point for the patient who has a malignancy of low lethal potential. In modern personalized medicine, there is a need for standardized cosmetic outcome assessments to analyze and compare the results of treatments. No gold standard methods currently exist. The result of this review is to summarize the various cosmesis methods, defining the strengths and weaknesses of each one and giving a line in research and clinical practice.

Retrospective analysis of breast radiotherapy treatment plans: Curating the 'non-curated'

INTRODUCTION

This paper provides a demonstration of how non-curated data can be retrospectively cleaned, so that existing repositories of radiotherapy treatment planning data can be used to complete bulk retrospective analyses of dosimetric trends and other plan characteristics.

METHODS

A non curated archive of 1137 radiotherapy treatment plans accumulated over a 12-month period, from five radiotherapy centres operated by one institution, was used to investigate and demonstrate a process of clinical data cleansing, by: identifying and translating inconsistent structure names; correcting inconsistent lung contouring; excluding plans for treatments other than breast tangents and plans without identifiable PTV, lung and heart structures; and identifying but not excluding plans that deviated from the local planning protocol. PTV, heart and lung dose-volume metrics were evaluated, in addition to a sample of personnel and linac load indicators.

RESULTS

Data cleansing reduced the number of treatment plans in the sample by 35.7%. Inconsistent structure names were successfully identified and translated (e.g. 35 different names for lung). Automatically separating whole lung structures into left and right lung structures allowed the effect of contralateral and ipsilateral lung dose to be evaluated, while introducing some small uncertainties, compared to manual contouring. PTV doses were indicative of prescription doses. Breast treatment work was unevenly distributed between oncologists and between metropolitan and regional centres.

CONCLUSION

This paper exemplifies the data cleansing and data analysis steps that may be completed using existing treatment planning data, to provide individual radiation oncology departments with access to information on their own patient populations. Clearly, the well-planned and systematic recording of new, high quality data is the preferred solution, but the retrospective curation of non-curated data may be a useful interim solution, for radiation oncology departments where the systems for recording of new data have yet to be designed and agreed.

Evaluation of classification and regression tree (CART) model in weight loss prediction following head and neck cancer radiation therapy

OBJECTIVE

We explore whether a knowledge-discovery approach building a Classification and Regression Tree (CART) prediction model for weight loss (WL) in head and neck cancer (HNC) patients treated with radiation therapy (RT) is feasible.

METHODS AND MATERIALS

HNC patients from 2007 to 2015 were identified from a prospectively collected database Oncospace. Two prediction models at different time points were developed to predict weight loss ≥5 kg at 3 months post-RT by CART algorithm: (1) during RT planning using patient demographic, delineated dose data, planning target volume-organs at risk shape relationships data and (2) at the end of treatment (EOT) using additional on-treatment toxicities and quality of life data.

RESULTS

Among 391 patients identified, WL predictors during RT planning were International Classification of Diseases diagnosis; dose to masticatory and superior constrictor muscles, larynx, and parotid; and age. At EOT, patient-reported oral intake, diagnosis, N stage, nausea, pain, dose to larynx, parotid, and low-dose planning target volume-larynx distance were significant predictive factors. The area under the curve during RT and EOT was 0.773 and 0.821, respectively.

CONCLUSIONS

We demonstrate the feasibility and potential value of an informatics infrastructure that has facilitated insight into the prediction of WL using the CART algorithm. The prediction accuracy significantly improved with the inclusion of additional treatment-related data and has the potential to be leveraged as a strategy to develop a learning health system.

Decision analytic modeling for the economic analysis of proton radiotherapy for non-small cell lung cancer

Background

Although proton radiation treatments are more costly than photon/X-ray therapy, they may lower overall treatment costs through reducing rates of severe toxicities and the costly management of those toxicities. To study this issue, we created a decision-model comparing proton vs. X-ray radiotherapy for locally advanced non-small cell lung cancer patients.

Methods

An influence diagram was created to model for radiation delivery, associated 6-month pneumonitis/esophagitis rates, and overall costs (radiation plus toxicity costs). Pneumonitis (age, chemo type, V20, MLD) and esophagitis (V60) predictors were modeled to impact toxicity rates. We performed toxicity-adjusted, rate-adjusted, risk group-adjusted, and radiosensitivity analyses.

Results

Upfront proton treatment costs exceeded that of photons [$16,730.37 (3DCRT), $23,893.83 (IMRT), $41,061.80 (protons)]. Based upon expected population pneumonitis and esophagitis rates for each modality, protons would be expected to recover $1,065.62 and $1,139.63 of the cost difference compared to 3DCRT or IMRT. For patients treated with IMRT experiencing grade 4 pneumonitis or grade 4 esophagitis, costs exceeded patients treated with protons without this toxicity. 3DCRT patients with grade 4 esophagitis had higher costs than proton patients without this toxicity. For the risk group analysis, high risk patients (age >65, carboplatin/paclitaxel) benefited more from proton therapy. A biomarker may allow patient selection for proton therapy, although the AUC alone is not sufficient to determine if the biomarker is clinically useful.

Conclusions

The comparison between proton and photon/X-ray radiation therapy for NSCLC needs to consider both the up-front cost of treatment and the possible long term cost of complications. In our analysis, current costs favor X-ray therapy. However, relatively small reductions in the cost of proton therapy may result in a shift to the preference for proton therapy.

Personalising Prostate Radiotherapy in the Era of Precision Medicine: A Review

Prostate cancer continues to be the most commonly diagnosed cancer among Canadian men. The introduction of routine screening and advanced treatment options have allowed for a decrease in prostate cancer-related mortality, but outcomes following treatment continue to vary widely. In addition, the overtreatment of indolent prostate cancers causes unnecessary treatment toxicities and burdens health care systems. Accurate identification of patients who should undergo aggressive treatment, and those which should be managed more conservatively, needs to be implemented. More tumour and patient information is needed to stratify patients into low-, intermediate-, and high-risk groups to guide treatment options. This paper reviews the current literature on personalised prostate cancer management, including targeting tumour hypoxia, genomic and radiomic prognosticators, and radiobiological tumour targeting. A review of the current applications and future directions for the use of big data in radiation therapy is also presented. Prostate cancer management has a lot to gain from the implementation of personalised medicine into practice. Using specific tumour and patient characteristics to personalise prostate radiotherapy in the era of precision medicine will improve survival, decrease unnecessary toxicities, and minimise the heterogeneity of outcomes following treatment.

Data collection of patient outcomes: one institution's experience

Patient- and provider-reported outcomes are recognized as important in evaluating quality of care, guiding health care policy, comparative effectiveness research, and decision-making in radiation oncology. Combining patient and provider outcome data with a detailed description of disease and therapy is the basis for these analyses. We report on the combination of technical solutions and clinical process changes at our institution that were used in the collection and dissemination of this data. This initiative has resulted in the collection of treatment data for 23 541 patients, 20 465 patients with provider-based adverse event records, and patient-reported outcome surveys submitted by 5622 patients. All of the data is made accessible using a self-service web-based tool.

Big Data in Designing Clinical Trials: Opportunities and Challenges

Emergence of big data analytics resource systems (BDARSs) as a part of routine practice in Radiation Oncology is on the horizon. Gradually, individual researchers, vendors, and professional societies are leading initiatives to create and demonstrate use of automated systems. What are the implications for design of clinical trials, as these systems emerge? Gold standard, randomized controlled trials (RCTs) have high internal validity for the patients and settings fitting constraints of the trial, but also have limitations including: reproducibility, generalizability to routine practice, infrequent external validation, selection bias, characterization of confounding factors, ethics, and use for rare events. BDARS present opportunities to augment and extend RCTs. Preliminary modeling using single- and muti-institutional BDARS may lead to better design and less cost. Standardizations in data elements, clinical processes, and nomenclatures used to decrease variability and increase veracity needed for automation and multi-institutional data pooling in BDARS also support ability to add clinical validation phases to clinical trial design and increase participation. However, volume and variety in BDARS present other technical, policy, and conceptual challenges including applicable statistical concepts, cloud-based technologies. In this summary, we will examine both the opportunities and the challenges for use of big data in design of clinical trials.

[Big data and their perspectives in radiation therapy]

The concept of big data indicates a change of scale in the use of data and data aggregation into large databases through improved computer technology. One of the current challenges in the creation of big data in the context of radiation therapy is the transformation of routine care items into dark data, i.e. data not yet collected, and the fusion of databases collecting different types of information (dose-volume histograms and toxicity data for example). Processes and infrastructures devoted to big data collection should not impact negatively on the doctor-patient relationship, the general process of care or the quality of the data collected. The use of big data requires a collective effort of physicians, physicists, software manufacturers and health authorities to create, organize and exploit big data in radiotherapy and, beyond, oncology. Big data involve a new culture to build an appropriate infrastructure legally and ethically. Processes and issues are discussed in this article.

The big data effort in radiation oncology: Data mining or data farming?

Although large volumes of information are entered into our electronic health care records, radiation oncology information systems and treatment planning systems on a daily basis, the goal of extracting and using this big data has been slow to emerge. Development of strategies to meet this goal is aided by examining issues with a data farming instead of a data mining conceptualization. Using this model, a vision of key data elements, clinical process changes, technology issues and solutions, and role for professional societies is presented. With a better view of technology, process and standardization factors, definition and prioritization of efforts can be more effectively directed.