The Use of Wearable Devices in Oncology Patients: A Systematic Review.

INTRODUCTION: The aim of this systematic review was to summarize the current literature on wearable technologies in oncology patients for the purpose of prognostication, treatment monitoring, and rehabilitation planning. METHODS: A search was conducted in Medline ALL, Cochrane Central Register of Controlled Trials, Embase, Emcare, CINAHL, Scopus, and Web of Science, up until February 2022. Articles were included if they reported on consumer grade and/or non-commercial wearable devices in the setting of either prognostication, treatment monitoring or rehabilitation. RESULTS: We found 199 studies reporting on 18 513 patients suitable for inclusion. One hundred and eleven studies used wearable device data primarily for the purposes of rehabilitation, 68 for treatment monitoring, and 20 for prognostication. The most commonly-reported brands of wearable devices were ActiGraph (71 studies; 36%), Fitbit (37 studies; 19%), Garmin (13 studies; 7%), and ActivPAL (11 studies; 6%). Daily minutes of physical activity were measured in 121 studies (61%), and daily step counts were measured in 93 studies (47%). Adherence was reported in 86 studies, and ranged from 40% to 100%; of these, 63 (74%) reported adherence in excess of 80%. CONCLUSION: Wearable devices may provide valuable data for the purposes of treatment monitoring, prognostication, and rehabilitation. Future studies should investigate live-time monitoring of collected data, which may facilitate directed interventions.

Radiation-induced nausea and vomiting: a comparison between MASCC/ESMO, ASCO, and NCCN antiemetic guidelines.

PURPOSE: Radiation-induced nausea and vomiting (RINV) can affect 50-80% of patients undergoing radiotherapy and negatively impacts quality of life. This review aimed to compare the most recent RINV antiemetic guidelines produced by the Multinational Association for Supportive Care in Cancer (MASCC), the European Society of Clinical Oncology (ESMO), the American Society of Clinical Oncology (ASCO), and the National Comprehensive Cancer Network (NCCN). Future improvements to the guidelines and the need for further research in RINV were also discussed. METHODS: Antiemetic guidelines produced by MASCC/ESMO, ASCO, and NCCN were examined to identify similarities, differences, and inadequacies within the guidelines. RESULTS: Areas of dissension within the guidelines include the addition of dexamethasone to moderate-risk antiemetic regimens, the prophylactic treatment of RINV in the low-risk categories, and the appropriate treatment for breakthrough emesis. The guidelines are in accordance that high-risk radiotherapy regimens should be treated prophylactically with a serotonin receptor antagonist and for those undergoing concurrent chemotherapy and radiotherapy, antiemetic treatment should be prescribed according to the emetic risk associated with their respective chemotherapy regimen. Low- and minimal-risk recommendations are based on low-level evidence and informal consensus. CONCLUSION: RINV is a frequent and distressing side effect of radiotherapy and requires further research to establish effective antiemetic guidelines and ensure optimal treatment outcomes.

Funding source, conflict of interest and positive conclusions in neuro-oncology clinical trials.

We aimed to test any association between authors' conclusions and self-reported COI or funding sources in central nervous system (CNS) studies. A review was performed for CNS malignancy clinical trials published in the last 5 years. Two investigators independently classified study conclusions according to authors' endorsement of the experimental therapy. Statistical models were used to test for associations between positive conclusions and trials characteristics. From February 2010 to February 2015, 1256 articles were retrieved; 319 were considered eligible trials. Positive conclusions were reported in 56.8% of trials with industry-only, 55.6% with academia-only, 44.1% with academia and industry, 77.8% with none, and 76.4% with not described funding source (p = 0.011). Positive conclusions were reported in 60.4% of trials with unrelated COI, 60% with related COI, and 60% with no COI reported (p = 0.997). Factors that were significantly associated with the presence of positive conclusion included trials design (phase 1) [OR 11.64 (95 CI 4.66-29.09), p < 0.001], geographic location (outside North America or Europe) [OR 1.96 (95 CI 1.05-3.79), P = 0.025], primary outcomes (non-overall or progression free survival) [OR 3.74 (95 CI 2.27-6.18), p < 0.001], and failure to disclose funding source [OR 2.45 (95 CI 1.22-5.22), p = 0.011]. In a multivariable regression model, all these factors remained significantly associated with trial's positive conclusion. Funding source and self-reported COI did not appear to influence the CNS trials conclusion. Funding source information and COI disclosure were under-reported in 14.1 and 17.2% of the CNS trials. Continued efforts are needed to increase rates of both COI and funding source reporting.

The relationship of study and authorship characteristics on trial sponsorship and self-reported conflicts of interest among neuro-oncology clinical trials.

PROPOSE: To examine the association between trial sponsorship sources, self-reported conflicts of interest (COI), and study and author characteristics in central nervous system (CNS) oncology clinical trials (CT). METHODS: MEDLINE search was performed for original CT on "Central Nervous System Neoplasms"[Mesh]. The investigators assessed for relationships between funding source (industry, academic or cooperative, none, not described), COI (presented, none, or not reported), CT, and author characteristics. RESULTS: From 2010 to 2015, 319 CT were considered eligible. The majority of the studies involved primary gliomas (55.2%) and were Phase II CT (59.2%). Drug therapy was investigated in 83.0% of the CT. The remaining studies investigated surgery or radiotherapy. A minority of papers were published in journals with impact factor (IF) higher than > 10 (16%) or in regions other than North America and Europe (20.4%). Overall, 83.1% of studies disclosed funding sources: 32.6% from industry alone, 33.9% from an academic or cooperative group, and 10.7% from a mixed funding model. COI data was reported by 85.9% of trials, of which 56.2% reported no COI and 43.8% reported a related COI. Significant predictors for sponsorship (industry and/or academia) on univariate analysis were study design, type of intervention, journal impact factor, study conclusion, transparency of COI and presence of COI. On multivariate analysis, type of intervention, (P < 0.001), journal impact factor (IF) (P = 0.003), presence of COI (P < 0.001) and study conclusion (P = 0.003) remained significant predictors of sponsorship. For predicting COI, significant variables on univariate analysis were disease type, type of intervention, journal IF, funding source, and intervention arm being related to sponsor. On multivariate analysis, disease type (P = 0.003), journal IF (P < 0.001), type of intervention (P = 0.001), and funding source (P = 0.008) remained significant. CONCLUSIONS: The majority of CNS CT reported some external funding sources and non-related COI. We identified that drug trials, higher IF, presence of COI, and a neutral or negative study conclusion are associated with external funding. Likewise drug trials, higher IF, and glioma trials are associated with presence of COI.

Minimal clinically important differences in the EORTC QLQ-C30 and brief pain inventory in patients undergoing re-irradiation for painful bone metastases.

PURPOSE: The EORTC QLQ-C30 and the Brief Pain Inventory (BPI) are validated tools for measuring quality of life (QOL) and the impact of pain in patients with advanced cancer. Interpretation of these instrument scores can be challenging and it is difficult to know what numerical changes translate to clinically significant impact in patients' lives. To address this issue, our study sought to establish the minimal clinically important differences (MCID) for these two instruments in a prospective cohort of patients with advanced cancer and painful bone metastases. METHODS: Both anchor-based and distribution-based methods were used to estimate the MCID scores from patients enrolled in a randomized phase III trial evaluating two different re-irradiation treatment schedules. For the anchor-based method, the global QOL item from the QLQ-C30 was chosen as the anchor. Spearman correlation coefficients were calculated for all items and only those items with moderate or better correlation (|r| ≥ 0.30) with the anchor were used for subsequent analysis. A 10-point difference in the global QOL score was used to classify improvement and deterioration, and the MCID scores were calculated for each of these categories. These results were compared with scores obtained by the distribution-method, which estimates the MCID purely from the statistical characteristics of the sample population. RESULTS: A total of 375 patients were included in this study with documented pain responses and completed QOL questionnaires at 2 months. 9/14 items in the QLQ-C30 and 6/10 items in the BPI were found to have moderate or better correlation with the anchor. For deterioration, statistically significant MCID scores were found in all items of the QLQ-C30 and BPI. For improvement, statistically significant MCID scores were found in 7/9 items of the QLQ-C30 and 2/6 items of the BPI. The MCID scores for deterioration were uniformly higher than the MCIDs for improvement. Using the distribution-based method, there was good agreement between the 0.5 standard deviation (SD) values and anchor-based scores for deterioration. For improvement, there was less agreement and the anchor-based scores were lower than the 0.5 SD values obtained from the distribution-based method. CONCLUSION: We present MCID scores for the QLQ-C30 and BPI instruments obtained from a large cohort of patients with advanced cancer undergoing re-irradiation for painful bone metastases. The results from this study were compared to other similar studies which showed larger MCID scores for improvement compared to deterioration. We hypothesize that disease trajectory and patient expectations are important factors in understanding the contrasting results. The results of this study can guide clinicians and researchers in the interpretation of these instruments.

Minimal clinically important differences in the EORTC QLQ-BM22 and EORTC QLQ-C15-PAL modules in patients with bone metastases undergoing palliative radiotherapy.

PURPOSE: Validated tools for evaluating quality of life (QOL) in patients with bone metastases include the EORTC QLQ-BM22 and QLQ-C15-PAL modules. A statistically significant difference in metric scores may not be clinically significant. To aid in their interpretation, we performed analyses to determine the minimal clinically important differences (MCID) for these QOL instruments. METHODS: Both anchor-based and distribution-based methods were used to determine the MCID among patients with bone metastases enrolled in a randomized phase III trial. For the anchor-based approach, overall QOL as measured by the QLQ-C15-PAL module was used as the anchor and only the subscales with moderate or better correlation were used for subsequent MCID analysis. In the anchor-based approach, patients were classified as improved, stable or deteriorated by the change in the overall QOL score from baseline to follow-up after 42 days. The MCID and confidence interval was then calculated for all subscales. In the distribution-based approach, the MCID was expressed as a proportion of the standard deviation and standard error measurement from the subscale score distribution. RESULTS: A total of 204 patients completed the questionnaires at baseline and follow-up. Only the dyspnea and insomnia subscales did not have at least moderate correlation with the overall QOL anchor. Using the anchor-based approach, 10/11 subscales had an MCID score significantly different than 0 for improvement and 3/11 subscales had a significant MCID score for deterioration. The magnitude of MCID scores was higher for improvement in comparison with deterioration. For improvement, the anchor-based approach showed good agreement with the distribution-based approach when using 0.5 SD as the MCID. However, there was greater lack of agreement between these approaches for deterioration. CONCLUSION: We present the MCID scores for the EORTC QLQ-BM22 and QLQ-C15-PAL QOL instruments. The results of this study can guide clinicians in the interpretation of these instruments. CLINICAL TRIALS REGISTRY: NCT01248585.

Impact of technological advances in treatment planning, image guidance, and treatment delivery on target margin design for prostate cancer radiotherapy: an updated review.

Recent innovations in image guidance, treatment delivery, and adaptive radiotherapy (RT) have created a new paradigm for planning target volume (PTV) margin design for patients with prostate cancer. We performed a review of the recent literature on PTV margin selection and design for intact prostate RT, excluding post-operative RT, brachytherapy, and proton therapy. Our review describes the increased focus on prostate and seminal vesicles as heterogenous deforming structures with further emergence of intra-prostatic GTV boost and concurrent pelvic lymph node treatment. To capture recent innovations, we highlight the evolution in cone beam CT guidance, and increasing use of MRI for improved target delineation and image registration and supporting online adaptive RT. Moreover, we summarize new and evolving image-guidance treatment platforms as well as recent reports of novel immobilization strategies and motion tracking. Our report also captures recent implementations of artificial intelligence to support image guidance and adaptive RT. To characterize the clinical impact of PTV margin changes via model-based risk estimates and clinical trials, we highlight recent high impact reports. Our report focusses on topics in the context of PTV margins but also showcase studies attempting to move beyond the PTV margin recipes with robust optimization and probabilistic planning approaches. Although guidelines exist for target margins conventional using CT-based image guidance, further validation is required to understand the optimal margins for online adaptation either alone or combined with real-time motion compensation to minimize systematic and random uncertainties in the treatment of patients with prostate cancer.

Review of brachytherapy clinical trials: a cross-sectional analysis of ClinicalTrials.gov.

INTRODUCTION: Characterizing the landscape of clinical trials including brachytherapy can provide an overview of the current status and research trends which may guide further areas of investigation. METHOD: We queried 449,849 clinical trials from the ClinicalTrials.gov registry using brachytherapy-related keywords from 1980 to 2023, yielding 245 multi-arm and 201 single-arm, brachytherapy trials. Multi-arm and single-arm brachytherapy trials were compared using 12 trial protocol elements. RESULTS: The number of trials including brachytherapy has increased over time, with over 60% of trials registered in 2010 onwards. The majority of clinical trials were Phase 2 or 3, evaluated both safety and efficacy, and were funded by academic sponsors. The most common tumor sites evaluated in brachytherapy clinical trials include prostate, cervix, liver, endometrium, and breast. CONCLUSION: There remains continued interest in clinical trials including brachytherapy focused on evaluation of novel delivery systems, treatment planning, and new indications. More brachytherapy clinical trials are needed to define the optimal clinical utilization and advance prospective research in this field.

The impact of multidisciplinary cancer conferences on overall survival: a meta-analysis.

BACKGROUND: Multidisciplinary cancer conferences consist of regular meetings between diverse specialists working together to share clinical decision making in cancer care. The aim of this study was to systematically review and meta-analyze the effect of multidisciplinary cancer conference intervention on the overall survival of patients with cancer. METHODS: A systematic literature search was conducted on Ovid MEDLINE, EMBASE, and the Cochrane Controlled Register of Trials for studies published up to July 2023. Studies reporting on the impact of multidisciplinary cancer conferences on patient overall survival were included. A standard random-effects model with the inverse variance-weighted approach was used to estimate the pooled hazard ratio of mortality (multidisciplinary cancer conference vs non-multidisciplinary cancer conference) across studies, and the heterogeneity was assessed by I2. Publication bias was examined using funnel plots and the Egger test. RESULTS: A total of 134 287 patients with cancer from 59 studies were included in our analysis, with 48 467 managed by multidisciplinary cancer conferences and 85 820 in the control arm. Across all cancer types, patients managed by multidisciplinary cancer conferences had an increased overall survival compared with control patients (hazard ratio = 0.67, 95% confidence interval = 0.62 to 0.71, I2 = 84%). Median survival time was 30.2 months in the multidisciplinary cancer conference group and 19.0 months in the control group. In subgroup analysis, a positive effect of the multidisciplinary cancer conference intervention on overall survival was found in breast, colorectal, esophageal, hematologic, hepatocellular, lung, pancreatic, and head and neck cancer. CONCLUSIONS: Overall, our meta-analysis found a significant positive effect of multidisciplinary cancer conferences compared with controls. Further studies are needed to establish nuanced guidelines when optimizing multidisciplinary cancer conference integration for treating diverse patient populations.

Rapid multi-catheter segmentation for magnetic resonance image-guided catheter-based interventions.

BACKGROUND: Magnetic resonance imaging (MRI) is the gold standard for delineating cancerous lesions in soft tissue. Catheter-based interventions require the accurate placement of multiple long, flexible catheters at the target site. The manual segmentation of catheters in MR images is a challenging and time-consuming task. There is a need for automated catheter segmentation to improve the efficiency of MR-guided procedures. PURPOSE: To develop and assess a machine learning algorithm for the detection of multiple catheters in magnetic resonance images used during catheter-based interventions. METHODS: In this work, a 3D U-Net was trained to retrospectively segment catheters in scans acquired during clinical MR-guided high dose rate (HDR) prostate brachytherapy cases. To assess confidence in segmentation, multiple AI models were trained. On clinical test cases, average segmentation results were used to plan the brachytherapy delivery. Dosimetric parameters were compared to the original clinical plan. Data was obtained from 35 patients who underwent HDR prostate brachytherapy for focal disease with a total of 214 image volumes. 185 image volumes from 30 patients were used for training using a five-fold cross validation split to divide the data for training and validation. To generate confidence measures of segmentation accuracy, five trained models were generated. The remaining five patients (29 volumes) were used to test the performance of the trained model by comparison to manual segmentations of three independent observers and assessment of dosimetric impact on the final clinical brachytherapy plans. RESULTS: The network successfully identified 95% of catheters in the test set at a rate of 0.89 s per volume. The multi-model method identified the small number of cases where AI segmentation of individual catheters was poor, flagging the need for user input. AI-based segmentation performed as well as segmentations by independent observers. Plan dosimetry using AI-segmented catheters was comparable to the original plan. CONCLUSION: The vast majority of catheters were accurately identified by AI segmentation, with minimal impact on plan outcomes. The use of multiple AI models provided confidence in the segmentation accuracy and identified catheter segmentations that required further manual assessment. Real-time AI catheter segmentation can be used during MR-guided insertions to assess deflections and for rapid planning of prostate brachytherapy.

Dose-response of localized renal cell carcinoma after stereotactic body radiation therapy: A meta-analysis.

BACKGROUND: Stereotactic ablative radiation therapy (SBRT) is an emerging treatment option for primary renal cell carcinoma (RCC), particularly in patients who are unsuitable for surgery. The aim of this review is to assess the effect of increasing the biologically equivalent dose (BED) via various radiation fractionation regimens on clinical outcomes. METHODS: A literature search was conducted in PubMed (Medline), EMBASE, and the Cochrane Library for studies published up to October 2023. Studies reporting on patients with localized RCC receiving SBRT were included to determine its effectiveness on local control, progression-free survival, and overall survival. A random effects model was used to meta-regress clinical outcomes relative to the BED for each study and heterogeneity was assessed by I2. RESULTS: A total of 724 patients with RCC from 22 studies were included, with a mean age of 72.7 years (range: 44.0-81.0). Local control was excellent with an estimate of 99 % (95 %CI: 97-100 %, I2 = 19 %), 98 % (95 %CI: 96-99 %, I2 = 8 %), and 94 % (95 %CI: 90-97 %, I2 = 11 %) at one year, two years, and five years respectively. No definitive association between increasing BED and local control, progression-free survival and overall survival was observed. No publication bias was observed. CONCLUSIONS: A significant dose response relationship between oncological outcomes and was not identified, and excellent local control outcomes were observed at the full range of doses. Until new evidence points otherwise, we support current recommendations against routine dose escalation beyond 25-26 Gy in one fraction or 42-48 Gy in three fractions, and to consider de-escalation or compromising target coverage if required to achieve safe organ at risk doses.

Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis.

Our purpose was to provide an understanding of current functional lung imaging (FLI) techniques and their potential to improve dosimetry and outcomes for patients with lung cancer receiving radiation therapy (RT). Excerpta Medica dataBASE (EMBASE), PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, or quantification of RT-related outcomes for patients with lung cancer. Studies involving all RT modalities, including stereotactic body RT and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomic and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP). One hundred seventy-eight studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more, 3.52% to the fraction of well-perfused lung receiving 20 Gy or more, 1.3 Gy to the mean dose to the well-ventilated lung, and 2.41 Gy to the mean dose to the well-perfused lung. Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity modulated RT and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which is reduced compared with results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information but was not statistically significant. FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the effect of FL avoidance planning on toxicity reduction and patient outcomes.

Physician and Artificial Intelligence Chatbot Responses to Cancer Questions From Social Media.

Importance: Artificial intelligence (AI) chatbots pose the opportunity to draft template responses to patient questions. However, the ability of chatbots to generate responses based on domain-specific knowledge of cancer remains to be tested. Objective: To evaluate the competency of AI chatbots (GPT-3.5 [chatbot 1], GPT-4 [chatbot 2], and Claude AI [chatbot 3]) to generate high-quality, empathetic, and readable responses to patient questions about cancer. Design, Setting, and Participants: This equivalence study compared the AI chatbot responses and responses by 6 verified oncologists to 200 patient questions about cancer from a public online forum. Data were collected on May 31, 2023. Exposures: Random sample of 200 patient questions related to cancer from a public online forum (Reddit r/AskDocs) spanning from January 1, 2018, to May 31, 2023, was posed to 3 AI chatbots. Main Outcomes and Measures: The primary outcomes were pilot ratings of the quality, empathy, and readability on a Likert scale from 1 (very poor) to 5 (very good). Two teams of attending oncology specialists evaluated each response based on pilot measures of quality, empathy, and readability in triplicate. The secondary outcome was readability assessed using Flesch-Kincaid Grade Level. Results: Responses to 200 questions generated by chatbot 3, the best-performing AI chatbot, were rated consistently higher in overall measures of quality (mean, 3.56 [95% CI, 3.48-3.63] vs 3.00 [95% CI, 2.91-3.09]; P < .001), empathy (mean, 3.62 [95% CI, 3.53-3.70] vs 2.43 [95% CI, 2.32-2.53]; P < .001), and readability (mean, 3.79 [95% CI, 3.72-3.87] vs 3.07 [95% CI, 3.00-3.15]; P < .001) compared with physician responses. The mean Flesch-Kincaid Grade Level of physician responses (mean, 10.11 [95% CI, 9.21-11.03]) was not significantly different from chatbot 3 responses (mean, 10.31 [95% CI, 9.89-10.72]; P > .99) but was lower than those from chatbot 1 (mean, 12.33 [95% CI, 11.84-12.83]; P < .001) and chatbot 2 (mean, 11.32 [95% CI, 11.05-11.79]; P = .01). Conclusions and Relevance: The findings of this study suggest that chatbots can generate quality, empathetic, and readable responses to patient questions comparable to physician responses sourced from an online forum. Further research is required to assess the scope, process integration, and patient and physician outcomes of chatbot-facilitated interactions.

Stereotactic Radiation Therapy in Early Non-Small Cell Lung Cancer and Interstitial Lung Disease: A Nonrandomized Clinical Trial.

Importance: Patients with interstitial lung disease (ILD) and early-stage non-small cell lung cancer (NSCLC) have been reported to be at high risk of toxic effects after stereotactic ablative radiotherapy (SABR), but for many patients, there are limited alternative treatment options. Objective: To prospectively assess the benefits and toxic effects of SABR in this patient population. Design, Setting, and Participants: This prospective cohort study was conducted at 6 academic radiation oncology institutions, 5 in Canada and 1 in Scotland, with accrual between March 7, 2019, and January 12, 2022. Patients aged 18 years or older with fibrotic ILD and a diagnosis of T1-2N0 NSCLC who were not candidates for surgical resection were enrolled. Intervention: Patients were treated with SABR to a dose of 50 Gy in 5 fractions every other day. Main Outcomes and Measures: The study prespecified that SABR would be considered worthwhile if median overall survival-the primary end point-was longer than 1 year, with a grade 3 to 4 risk of toxic effects less than 35% and a grade 5 risk of toxic effects less than 15%. Secondary end points included toxic effects, progression-free survival (PFS), local control (LC), quality-of-life outcomes, and changes in pulmonary function. Intention-to-treat analysis was conducted. Results: Thirty-nine patients enrolled and received SABR. Median age was 78 (IQR, 67-83) years and 59% (n = 23) were male. At baseline, 70% (26 of 37) of patients reported dyspnea, median forced expiratory volume in first second of expiration was 80% (IQR, 66%-90%) predicted, median forced vital capacity was 84% (IQR, 69%-94%) predicted, and median diffusion capacity of the lung for carbon monoxide was 49% (IQR, 38%-61%) predicted. Median follow-up was 19 (IQR, 14-25) months. Overall survival at 1 year was 79% (95%, CI 62%-89%; P < .001 vs the unacceptable rate), and median overall survival was 25 months (95% CI, 14 months to not reached). Median PFS was 19 months (95% CI, 13-28 months), and 2-year LC was 92% (95% CI, 69%-98%). Adverse event rates (highest grade per patient) were grade 1 to 2: n = 12 (31%), grade 3: n = 4 (10%), grade 4: n = 0, and grade 5: n = 3 (7.7%, all due to respiratory deterioration). Conclusions and Relevance: In this trial, use of SABR in patients with fibrotic ILD met the prespecified acceptability thresholds for both toxicity and efficacy, supporting the use of SABR for curative-intent treatment after a careful discussion of risks and benefits. Trial Registration: ClinicalTrials.gov Identifier: NCT03485378.

Stereotactic Radiation for Ultra-Central Non-Small Cell Lung Cancer: A Safety and Efficacy Trial (SUNSET).

PURPOSE: The use of stereotactic body radiation therapy for tumors in close proximity to the central mediastinal structures has been associated with a high risk of toxicity. This study (NCT03306680) aimed to determine the maximally tolerated dose of stereotactic body radiation therapy for ultracentral non-small cell lung carcinoma, using a time-to-event continual reassessment methodology. METHODS AND MATERIALS: Patients with T1-3N0M0 (≤6 cm) non-small cell lung carcinoma were eligible. The maximally tolerated dose was defined as the dose of radiation therapy associated with a ≤30% rate of grade (G) 3 to 5 prespecified treatment-related toxicity occurring within 2 years of treatment. The starting dose level was 60 Gy in 8 daily fractions. The dose-maximum hotspot was limited to 120% and within the planning tumor volume; tumors with endobronchial invasion were excluded. This primary analysis occurred 2 years after completion of accrual. RESULTS: Between March 2018 and April 2021, 30 patients were enrolled at 5 institutions. The median age was 73 years (range, 65-87) and 17 (57%) were female. Planning tumor volume was abutting proximal bronchial tree in 19 (63%), esophagus 5 (17%), pulmonary vein 1 (3.3%), and pulmonary artery 14 (47%). All patients received 60 Gy in 8 fractions. The median follow-up was 37 months (range, 8.9-51). Two patients (6.7%) experienced G3-5 adverse events related to treatment: 1 patient with G3 dyspnea and 1 G5 pneumonia. The latter had computed tomography findings consistent with a background of interstitial lung disease. Three-year overall survival was 72.5% (95% CI, 52.3%-85.3%), progression-free survival 66.1% (95% CI, 46.1%-80.2%), local control 89.6% (95% CI, 71.2%-96.5%), regional control 96.4% (95% CI, 77.2%-99.5%), and distant control 85.9% (95% CI, 66.7%-94.5%). Quality-of-life scores declined numerically over time, but the decreases were not clinically or statistically significant. CONCLUSIONS: Sixty Gy in 8 fractions, planned and delivered with only a moderate hotspot, has a favorable adverse event rate within the prespecified acceptability criteria and results in excellent control for ultracentral tumors.

Recent advances in artificial intelligence applications for supportive and palliative care in cancer patients.

PURPOSE OF REVIEW: Artificial intelligence (AI) is a transformative technology that has the potential to improve and augment the clinical workflow in supportive and palliative care (SPC). The objective of this study was to provide an overview of the recent studies applying AI to SPC in cancer patients. RECENT FINDINGS: Between 2020 and 2022, 29 relevant studies were identified and categorized into two applications: predictive modeling and text screening. Predictive modeling uses machine learning and/or deep learning algorithms to make predictions regarding clinical outcomes. Most studies focused on predicting short-term mortality risk or survival within 6 months, while others used models to predict complications in patients receiving treatment and forecast the need for SPC services. Text screening typically uses natural language processing (NLP) to identify specific keywords, phrases, or documents from patient notes. Various applications of NLP were found, including the classification of symptom severity, identifying patients without documentation related to advance care planning, and monitoring online support group chat data. SUMMARY: This literature review indicates that AI tools can be used to support SPC clinicians in decision-making and reduce manual workload, leading to potentially improved care and outcomes for cancer patients. Emerging data from prospective studies supports the clinical benefit of these tools; however, more rigorous clinical validation is required before AI is routinely adopted in the SPC clinical workflow.

Utilizing clinical, pathological and radiological information to guide postoperative radiotherapy in prostate cancer.

INTRODUCTION: A detectable and rising PSA following radical prostatectomy is indicative of recurrent prostate cancer. Salvage radiotherapy (SRT) with/without androgen deprivation therapy represents the main treatment option for these patients and has been historically associated with a biochemical control rate of ~70%. To determine the optimal timing, diagnostic workup, radiotherapy dosefractionation, treatment volume, and use of systemic therapy, several informative studies have been conducted in the last decade. AREAS COVERED: This review examines the recent evidence to guide radiotherapy decision making in the SRT setting. Key topics include adjuvant vs salvage RT, utilization of molecular imaging and genomic classifiers, length of androgen deprivation therapy, inclusion of elective pelvic volume, and emerging role for hypofractionation. EXPERT OPINION: Recently reported trials, conducted in an era prior to the routine use of molecular imaging and genomic classifiers, have been pivotal in establishing the current standard of care for SRT in prostate cancer. However, decisions about radiation treatment and systemic therapy may be tailored based on available prognostic and predictive biomarkers. Data from contemporary clinical trials are awaited to define and establish individualized, biomarker-driven approaches for SRT.

Evaluation of clinical decision support systems in oncology: An updated systematic review.

With increasing reliance on technology in oncology, the impact of digital clinical decision support (CDS) tools needs to be examined. A systematic review update was conducted and peer-reviewed literature from 2016 to 2022 were included if CDS tools were used for live decision making and comparatively assessed quantitative outcomes. 3369 studies were screened and 19 were included in this updated review. Combined with a previous review of 24 studies, a total of 43 studies were analyzed. Improvements in outcomes were observed in 42 studies, and 34 of these were of statistical significance. Computerized physician order entry and clinical practice guideline systems comprise the greatest number of evaluated CDS tools (13 and 10 respectively), followed by those that utilize patient-reported outcomes (8), clinical pathway systems (8) and prescriber alerts for best-practice advisories (4). Our review indicates that CDS can improve guideline adherence, patient-centered care, and care delivery processes in oncology.

Artificial intelligence applications in brachytherapy: A literature review.

PURPOSE: Artificial intelligence (AI) has the potential to simplify and optimize various steps of the brachytherapy workflow, and this literature review aims to provide an overview of the work done in this field. METHODS AND MATERIALS: We conducted a literature search in June 2022 on PubMed, Embase, and Cochrane for papers that proposed AI applications in brachytherapy. RESULTS: A total of 80 papers satisfied inclusion/exclusion criteria. These papers were categorized as follows: segmentation (24), registration and image processing (6), preplanning (13), dose prediction and treatment planning (11), applicator/catheter/needle reconstruction (16), and quality assurance (10). AI techniques ranged from classical models such as support vector machines and decision tree-based learning to newer techniques such as U-Net and deep reinforcement learning, and were applied to facilitate small steps of a process (e.g., optimizing applicator selection) or even automate the entire step of the workflow (e.g., end-to-end preplanning). Many of these algorithms demonstrated human-level performance and offer significant improvements in speed. CONCLUSIONS: AI has potential to augment, automate, and/or accelerate many steps of the brachytherapy workflow. We recommend that future studies adhere to standard reporting guidelines. We also stress the importance of using larger sample sizes and reporting results using clinically interpretable measures.

Use of artificial intelligence for cancer clinical trial enrollment: a systematic review and meta-analysis.

BACKGROUND: The aim of this study is to provide a comprehensive understanding of the current landscape of artificial intelligence (AI) for cancer clinical trial enrollment and its predictive accuracy in identifying eligible patients for inclusion in such trials. METHODS: Databases of PubMed, Embase, and Cochrane CENTRAL were searched until June 2022. Articles were included if they reported on AI actively being used in the clinical trial enrollment process. Narrative synthesis was conducted among all extracted data: accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. For studies where the 2x2 contingency table could be calculated or supplied by authors, a meta-analysis to calculate summary statistics was conducted using the hierarchical summary receiver operating characteristics curve model. RESULTS: Ten articles reporting on more than 50 000 patients in 19 datasets were included. Accuracy, sensitivity, and specificity exceeded 80% in all but 1 dataset. Positive predictive value exceeded 80% in 5 of 17 datasets. Negative predictive value exceeded 80% in all datasets. Summary sensitivity was 90.5% (95% confidence interval [CI] = 70.9% to 97.4%); summary specificity was 99.3% (95% CI = 81.8% to 99.9%). CONCLUSIONS: AI demonstrated comparable, if not superior, performance to manual screening for patient enrollment into cancer clinical trials. As well, AI is highly efficient, requiring less time and human resources to screen patients. AI should be further investigated and implemented for patient recruitment into cancer clinical trials. Future research should validate the use of AI for clinical trials enrollment in less resource-rich regions and ensure broad inclusion for generalizability to all sexes, ages, and ethnicities.