Citations

Background: Due to lacking evidence on surveillance for gastric cancer (GC), this study aimed to determine the optimal postsurgical surveillance strategy for pathological stage (pStage) II/III GC patients and compare its cost-effectiveness with traditional surveillance strategies. Methods: Prospectively collected data from stage II/III GC patients (n=1661) who underwent upfront surgery at a large-volume tertiary cancer center in China (FJMUUH cohort) between January 2010 and October 2015. For external validation, two independent cohorts were included, which were composed of 380 stage II/III GC patients at an tertiary cancer center in U.S.A (Mayo cohort) between July 1991 and July 2012 and 270 stage II/III GC patients at another tertiary cancer center in China (QUAH cohort) between May 2010 and October 2014. Random forest models were used to predict dynamic recurrence hazards and to construct individual surveillance strategies for stage II/III GC. Cost-effectiveness was assessed by the Markov model. Results: The median follow-up period of the FJMUUH, the Mayo, and QUAH cohorts were 55, 158, and 70 months, respectively. In the FJMUUH cohort, the 5-year recurrence risk was higher in pStage III compared with pStage II GC patients (P<0.001). Our novel individual surveillance strategy achieved optimal cost-effectiveness for pStage II GC patients (ICER =$490/QALY). The most intensive NCCN surveillance guideline was more cost-effective (ICER =$983/QALY) for pStage III GC patients. The external validations confirmed our results. Conclusion: For patients with pStage II GC, individualized risk-based surveillance outperformed the JGCTG and NCCN surveillance guidelines. However, the NCCN surveillance guideline may be more suitable for patients with pStage III GC. Even though our results are limited by the retrospective study design, the authors believe that our findings should be considered when recommending postoperative surveillance for stage II/III GC with upfront surgery in the absence of a randomized clinical trial.

AbstractBackgroundAccurate and efficient dose calculation is essential for on‐line adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results in photon therapy. However, there is a scarcity of DL‐based dose prediction methods specifically designed for proton therapy. Successful dose prediction method for proton therapy should account for more challenging dose prediction problems in pencil beam scanning proton therapy (PBSPT) due to its sensitivity to heterogeneities.PurposeTo develop a DL‐based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on‐line adaptive proton therapy clinical decision and subsequent replanning.MethodsPBSPT plans of 103 prostate cancer patients (93 for training and the other 10 for independent testing) and 83 lung cancer patients (73 for training and the other 10 for independent testing) previously treated at our institution were included in the study, each with computed tomography scans (CTs), structure sets, and plan doses calculated by the in‐house developed Monte‐Carlo dose engine (considered as the ground truth in the model training and testing). For the ablation study, we designed three experiments corresponding to the following three methods: (1) Experiment 1, the conventional region of interest (ROI) (composed of targets and organs‐at‐risk [OARs]) method. (2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. (3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D‐Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates with a criterion of 3%/3 mm/10%, and dice coefficients for the structures enclosed by the iso‐dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency.ResultsCompared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices (for lung cancer, CTV D98 absolute deviation: 0.74 ± 0.18 vs. 0.57 ± 0.21 vs. 0.54 ± 0.15 Gy[RBE], ROI vs. beam mask vs. sliding window methods, respectively). For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method improved the passing rates in these regions and the sliding window method further improved them (for prostate cancer, targets: 96.93% ± 0.53% vs. 98.88% ± 0.49% vs. 99.97% ± 0.07%, BODY: 86.88% ± 0.74% vs. 93.21% ± 0.56% vs. 95.17% ± 0.59%). A similar trend was also observed for the dice coefficients. This trend was especially remarkable for relatively low prescription isodose lines (for lung cancer, 10% isodose line dice: 0.871 ± 0.027 vs. 0.911 ± 0.023 vs. 0.927 ± 0.017). The dose predictions for all the testing cases were completed within 0.25 s.ConclusionsAn accurate and efficient deep learning‐augmented proton dose prediction framework has been developed for PBSPT, which can predict accurate dose distributions not only inside but also outside ROI efficiently. The framework can potentially further reduce the initial planning and adaptive replanning workload in PBSPT.

ImportancePatients should have an active role in decisions about pursuing or forgoing specific therapies in treatment de-escalation trials.ObjectiveTo evaluate longitudinal patient-reported outcomes (PROs) encompassing decisional comfort and health-related quality of life (HRQOL) among patients who elected to enroll in a clinical trial evaluating radiotherapy alone, without breast surgery, for invasive breast cancers with exceptional response to neoadjuvant systemic therapy (NST).Design, Setting, and ParticipantsProspective, single-group, phase 2 clinical trial at 7 US medical centers. Women aged 40 years or older with invasive cT1-2 N0-1 M0 triple-negative or human epidermal growth factor receptor 2 (ERBB2)–positive breast cancer with no pathologic evidence of residual disease following standard NST enrolled from March 6, 2017, to November 9, 2021. Validated PRO measures were administered at baseline and 6, 12, and 36 months post-radiotherapy. Data were analyzed from January to February 2023.InterventionsPRO measures included the Decision Regret Scale (DRS), Functional Assessment of Cancer Therapy—Lymphedema (FACT-B+4), and Breast Cancer Treatment Outcomes Scale (BCTOS).Main Outcomes and MeasuresChanges in PRO measure scores and subscores over time.ResultsAmong 31 patients, the median (IQR) age was 61 (56-66) years, 26 (84%) were White, and 26 (84%) were non-Hispanic. A total of 15 (48%) had triple-negative disease and 16 (52%) had ERBB2-positive disease. Decisional comfort was high at baseline (median [IQR] DRS score 10 [0-25] on a 0-100 scale, with higher scores indicating higher decisional regret) and significantly increased over time (median [IQR] DRS score at 36 months, 0 [0-20]; P &amp;lt; .001). HRQOL was relatively high at baseline (median [IQR] FACT-B composite score 121 [111-134] on a 0-148 scale, with higher scores indicating higher HRQOL) and significantly increased over time (median [IQR] FACT-B score at 36 months, 128 [116-137]; P = .04). Perceived differences between the affected breast and contralateral breast were minimal at baseline (median [IQR] BCTOS score 1.05 [1.00-1.23] on a 1-4 scale, with higher scores indicating greater differences) and increased significantly over time (median [IQR] BCTOS score at 36 months, 1.36 [1.18-1.64]; P &amp;lt; .001). At 36 months postradiotherapy, the cosmetic subscore was 0.45 points higher than baseline (95% CI, 0.16-0.74; P = .001), whereas function, pain, and edema subscores were not significantly different than baseline.Conclusions and RelevanceIn this nonrandomized phase 2 clinical trial, analysis of PROs demonstrated an overall positive experience for trial participants, with longitudinal improvements in decisional comfort and overall HRQOL over time and minimal lasting adverse effects of therapy.Trial RegistrationClinicalTrials.gov Identifier: NCT02945579

Abstract Objective . To investigate the impact of scan path optimization on the dose accuracy and beam delivery time (BDT) of proton pencil beam scanning in the dose-driven continuous scanning (DDCS). Approach . A diverse set of six clinical plans, representing various spot patterns and treatment sites, was used to evaluate the effectiveness of scan time optimization and scan length optimization. The DDCS dose discrepancy and BDT with optimized scan paths was compared to the default serpentine scan path. Main results . Both scan time optimization and scan path optimization were able to reduce the DDCS dose discrepancy compared to the default serpentine scan path. All plans, except for the layer repainting lung plan, achieved a 2%/2 mm gamma pass rate of over 99% and less than 1% PTV DVH root mean square error (RMSE) through scan path optimization. In the case of the layer repainting lung plan, when compared to the default serpentine scan path, the 2%/2 mm gamma pass rate showed improvements from 91.3% to 93.1% and 95.8%, while the PTV DVH RMSE decreased from 2.1% to 1.7% and 1.1% for scan time optimization and scan length optimization, respectively. Although scan time optimization resulted in shorter total scan times for all plans compared to the default scan path and scan length optimization tended to have longer total scan times. However, due to the short total scan times and their minimal contribution to the total BDT, the impact of scan path optimization on the total BDT was practically negligible. Significance . Both scan time optimization and scan length optimization proved to be effective in minimizing DDCS dose discrepancy. No definitive winner can be determined between these two optimization approaches. Both scan time and scan length optimization had minimal effect on the total BDT.

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

AbstractIntroductionIncreasingly, early‐stage non–small cell lung cancer (NSCLC) is treated with stereotactic body radiation therapy (SBRT). Although treatment is generally effective, a small subset of tumors will recur because of radioresistance. Preclinical studies suggested PI3K‐AKT‐mTOR activation mediates radioresistance. This study sought to validate this finding in tumor samples from patients who underwent SBRT for NSCLC.MethodsPatients with T1‐3N0 NSCLC treated with SBRT at our institution were included. Total RNA of formalin‐fixed paraffin‐embedded tumor biopsy specimens (pretherapy) was isolated and analyzed using the Clariom D assay. Risk scores from a PI3K activity signature and four published NSCLC signatures were generated and dichotomized by the median. Kaplan–Meier curves and Cox regressions were used to analyze their association with recurrence and overall survival (OS). The PI3K signature was also tested in a data set of resected NSCLC for additional validation.ResultsA total of 92 patients were included, with a median follow‐up of 18.3 months for living patients. There was no association of any of the four published gene expression signatures with recurrence or OS. However, high PI3K risk score was associated with higher local recurrence (hazard ratio [HR], 11.72; 95% CI, 1.40–98.0; p = .023) and worse disease‐free survival (DFS) (HR, 3.98; 95% CI, 1.57–10.09; p = .0035), but not OS (p = .49), regional recurrence (p = .15), or distant recurrence (p = .85). In the resected NSCLC data set (n = 361), high PI3K risk score was associated with decreased OS (log‐rank p = .013) but not DFS (p = 0.54).ConclusionsThis study validates that higher PI3K activity, measured by gene expression, is associated with local recurrence and worse DFS in early‐stage NSCLC patients treated with SBRT. This may be useful in prognostication and/or tailoring treatment, and merits further validation.

Abstract An efficient 2-D continuum finite element method (FEM), including the rigid body algorithm and our previously developed contact element, was formulated for the contact stress analysis of articular joints. This FEM can calculate the contact pressure distribution on articular surfaces and stress distribution inside of cartilage. This method can model geometric and material nonlinearities for both the static and dynamic situations. The major advantage of this method is that only the soft cartilage requires finite element (FE) mesh, while the bony structure can be modeled as a rigid body due to its relatively rigid nature. Since much less degrees of freedom are now required in FEM, much faster computing speed can be achieved.

Ampullary cancers refer to tumors originating from the ampulla of Vater (the ampulla, the intraduodenal portion of the bile duct, and the intraduodenal portion of the pancreatic duct), while periampullary cancers may arise from locations encompassing the head of the pancreas, distal bile duct, duodenum, or ampulla of Vater. Ampullary cancers are rare gastrointestinal malignancies, and prognosis varies greatly based on factors such as patient age, TNM classification, differentiation grade, and treatment modality received. Systemic therapy is used in all stages of ampullary cancer, including neoadjuvant therapy, adjuvant therapy, and first-line or subsequent-line therapy for locally advanced, metastatic, and recurrent disease. Radiation therapy may be used in localized ampullary cancer, sometimes in combination with chemotherapy, but there is no high-level evidence to support its utility. Select tumors may be treated surgically. This article describes NCCN recommendations regarding management of ampullary adenocarcinoma.