Optimising inter-patient image registration for image-based data mining in breast radiotherapy.

Background and purpose: Image-based data mining (IBDM) requires spatial normalisation to reference anatomy, which is challenging in breast radiotherapy due to variations in the treatment position, breast shape and volume. We aim to optimise spatial normalisation for breast IBDM. Materials and methods: Data from 996 patients treated with radiotherapy for early-stage breast cancer, recruited in the REQUITE study, were included. Patients were treated supine (n = 811), with either bilateral or ipsilateral arm(s) raised (551/260, respectively) or in prone position (n = 185). Four deformable image registration (DIR) configurations for extrathoracic spatial normalisation were tested. We selected the best-performing DIR configuration and further investigated two pathways: i) registering prone/supine cohorts independently and ii) registering all patients to a supine reference. The impact of arm positioning in the supine cohort was quantified. DIR accuracy was estimated using Normalised Cross Correlation (NCC), Dice Similarity Coefficient (DSC), mean Distance to Agreement (MDA), 95 % Hausdorff Distance (95 %HD), and inter-patient landmark registration uncertainty (ILRU). Results: DIR using B-spline and normalised mutual information (NMI) performed the best across all evaluation metrics. Supine-supine registrations yielded highest accuracy (0.98 ± 0.01, 0.91 ± 0.04, 0.23 ± 0.19 cm, 1.17 ± 1.18 cm, 0.51 ± 0.26 cm for NCC, DSC, MDA, 95 %HD, and ILRU), followed by prone-prone and supine-prone registrations. Arm positioning had no significant impact on registration performance. For the best DIR strategy, uncertainty of 0.44 and 0.81 cm in the breast and shoulder regions was found. Conclusions: B-spline algorithm using NMI and registered supine and prone cohorts independently provides the most optimal spatial normalisation strategy for breast IBDM.

Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy.

BACKGROUND: Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis. MATERIALS AND METHODS: 280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression. RESULTS: There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (-3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from "skin" contours showed higher agreement with observed events. CONCLUSION: Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models.

Comparing symptom reporting by prostate cancer patients and healthcare professionals in the international multicentre REQUITE study.

INTRODUCTION: Previous studies showed that healthcare professionals and patients had only moderate to low agreement on their assessment of treatment-related symptoms. We aimed to determine the levels of agreement in a large cohort of prostate cancer patients. METHODS: Analyses were made of data from 1,756 prostate cancer patients treated with external beam radiotherapy (RT) and/or brachytherapy in Europe and the USA and recruited into the prospective multicentre observational REQUITE study. Eleven pelvic symptoms at the end of RT were compared after translating patient-reported outcomes (PROs) into CTCAE-based healthcare professional ratings. Gwet's AC2 agreement coefficient and 95% confidence intervals were calculated for each symptom. To compare severity of grading between patients and healthcare professionals, percent agreement and deviations for each symptom were graphically depicted. Stratified and sensitivity analyses were conducted to identify potential influencing factors and to assess heterogeneity and robustness of results. RESULTS: The agreement for the 11 pelvic symptoms varied from very good (AC2 > 0.8: haematuria, rectal bleeding, management of sphincter control) to poor agreement (AC2 ≤ 0.2: proctitis and urinary urgency). Fatigue had a negative impact on the agreement. Patients tended to grade symptoms more severely than healthcare professionals. Information on sexual dysfunction was missing more frequently in healthcare professional assessment than PROs. CONCLUSION: Agreement was better for observable than subjective symptoms, with patients usually grading symptoms more severely than healthcare professionals. Our findings emphasize that PROs should complement symptom assessment by healthcare professionals and be taken into consideration for clinical decision-making to incorporate the patient perspective.

Estimating the percentage of patients who might benefit from proton beam therapy instead of X-ray radiotherapy.

OBJECTIVES: High-energy Proton Beam Therapy (PBT) commenced in England in 2018 and NHS England commissions PBT for 1.5% of patients receiving radical radiotherapy. We sought expert opinion on the level of provision. METHODS: Invitations were sent to 41 colleagues working in PBT, most at one UK centre, to contribute by completing a spreadsheet. 39 responded: 23 (59%) completed the spreadsheet; 16 (41%) declined, arguing that clinical outcome data are lacking, but joined six additional site-specialist oncologists for two consensus meetings. The spreadsheet was pre-populated with incidence data from Cancer Research UK and radiotherapy use data from the National Cancer Registration and Analysis Service. 'Mechanisms of Benefit' of reduced growth impairment, reduced toxicity, dose escalation and reduced second cancer risk were examined. RESULTS: The most reliable figure for percentage of radical radiotherapy patients likely to benefit from PBT was that agreed by 95% of the 23 respondents at 4.3%, slightly larger than current provision. The median was 15% (range 4-92%) and consensus median 13%. The biggest estimated potential benefit was from reducing toxicity, median benefit to 15% (range 4-92%), followed by dose escalation median 3% (range 0 to 47%); consensus values were 12 and 3%. Reduced growth impairment and reduced second cancer risk were calculated to benefit 0.5% and 0.1%. CONCLUSIONS: The most secure estimate of percentage benefit was 4.3% but insufficient clinical outcome data exist for confident estimates. The study supports the NHS approach of using the evidence base and developing it through randomised trials, non-randomised studies and outcomes tracking. ADVANCES IN KNOWLEDGE: Less is known about the percentage of patients who may benefit from PBT than is generally acknowledged. Expert opinion varies widely. Insufficient clinical outcome data exist to provide robust estimates. Considerable further work is needed to address this, including international collaboration; much is already underway but will take time to provide mature data.

Cost-Utility Analysis of Routine Anxiety and Depression Screening in Patients Consulting for Osteoarthritis: Results From a Clinical, Randomized Controlled Trial.

OBJECTIVE: To investigate the cost-effectiveness (cost-utility) of introducing general practitioner screening for anxiety and depression in patients consulting for osteoarthritis (OA). METHODS: A cluster-randomized trial-based economic evaluation to assess general practitioners screening for anxiety and depression symptoms in patients consulting for OA compared to usual care (screening for pain intensity) was undertaken over a 12-month period from a UK National Health Service and societal perspective. Patient-level mean costs and mean quality-adjusted life years (QALYs) were estimated, and cost-effectiveness acceptability curves controlling for cluster-level data were constructed. The base-case analysis used the net benefit regressions approach. The 2-stage nonparametric sampling technique was explored in a sensitivity analysis. RESULTS: The base-case analysis demonstrated that the intervention was as costly as, and less effective than, the control (QALY differential -0.029 [95% confidence interval -0.062, 0.003]). In the base-case analyses, general practitioner screening for anxiety and depression was unlikely to be a cost-effective option (probability <5% at £20,000/QALY). Similar results were observed in all sensitivity analyses. CONCLUSION: Prompting general practitioners to routinely screen and manage comorbid anxiety and depression in patients presenting with OA is unlikely to be cost-effective. Further research is needed to explore clinically effective and cost-effective models of managing anxiety and depression in patients presenting with clinical OA.

The effects of implementing a point-of-care electronic template to prompt routine anxiety and depression screening in patients consulting for osteoarthritis (the Primary Care Osteoarthritis Trial): A cluster randomised trial in primary care.

BACKGROUND: This study aimed to evaluate whether prompting general practitioners (GPs) to routinely assess and manage anxiety and depression in patients consulting with osteoarthritis (OA) improves pain outcomes. METHODS AND FINDINGS: We conducted a cluster randomised controlled trial involving 45 English general practices. In intervention practices, patients aged ≥45 y consulting with OA received point-of-care anxiety and depression screening by the GP, prompted by an automated electronic template comprising five questions (a two-item Patient Health Questionnaire-2 for depression, a two-item Generalized Anxiety Disorder-2 questionnaire for anxiety, and a question about current pain intensity [0-10 numerical rating scale]). The template signposted GPs to follow National Institute for Health and Care Excellence clinical guidelines for anxiety, depression, and OA and was supported by a brief training package. The template in control practices prompted GPs to ask the pain intensity question only. The primary outcome was patient-reported current pain intensity post-consultation and at 3-, 6-, and 12-mo follow-up. Secondary outcomes included pain-related disability, anxiety, depression, and general health. During the trial period, 7,279 patients aged ≥45 y consulted with a relevant OA-related code, and 4,240 patients were deemed potentially eligible by participating GPs. Templates were completed for 2,042 patients (1,339 [31.6%] in the control arm and 703 [23.1%] in the intervention arm). Of these 2,042 patients, 1,412 returned questionnaires (501 [71.3%] from 20 intervention practices, 911 [68.0%] from 24 control practices). Follow-up rates were similar in both arms, totalling 1,093 (77.4%) at 3 mo, 1,064 (75.4%) at 6 mo, and 1,017 (72.0%) at 12 mo. For the primary endpoint, multilevel modelling yielded significantly higher average pain intensity across follow-up to 12 mo in the intervention group than the control group (adjusted mean difference 0.31; 95% CI 0.04, 0.59). Secondary outcomes were consistent with the primary outcome measure in reflecting better outcomes as a whole for the control group than the intervention group. Anxiety and depression scores did not reduce following the intervention. The main limitations of this study are two potential sources of bias: an imbalance in cluster size (mean practice size 7,397 [intervention] versus 5,850 [control]) and a difference in the proportion of patients for whom the GP deactivated the template (33.6% [intervention] versus 27.8% [control]). CONCLUSIONS: In this study, we observed no beneficial effect on pain outcomes of prompting GPs to routinely screen for and manage comorbid anxiety and depression in patients presenting with symptoms due to OA, with those in the intervention group reporting statistically significantly higher average pain scores over the four follow-up time points than those in the control group. TRIAL REGISTRATION: ISRCTN registry ISRCTN40721988.