Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan. [Abstract copyright: © 2022 The Authors.

20-Year Risks of Breast-Cancer Recurrence after Stopping Endocrine Therapy at 5 Years

The administration of endocrine therapy for 5 years substantially reduces recurrence rates during and after treatment in women with early-stage, estrogen-receptor (ER)-positive breast cancer. Extending such therapy beyond 5 years offers further protection but has additional side effects. Obtaining data on the absolute risk of subsequent distant recurrence if therapy stops at 5 years could help determine whether to extend treatment

Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials

Background Neoadjuvant chemotherapy (NACT) for early breast cancer can make breast-conserving surgery more feasible and might be more likely to eradicate micrometastatic disease than might the same chemotherapy given after surgery. We investigated the long-term benefits and risks of NACT and the influence of tumour characteristics on outcome with a collaborative meta-analysis of individual patient data from relevant randomised trials. Methods We obtained information about prerandomisation tumour characteristics, clinical tumour response, surgery, recurrence, and mortality for 4756 women in ten randomised trials in early breast cancer that began before 2005 and compared NACT with the same chemotherapy given postoperatively. Primary outcomes were tumour response, extent of local therapy, local and distant recurrence, breast cancer death, and overall mortality. Analyses by intention-to-treat used standard regression (for response and frequency of breast-conserving therapy) and log-rank methods (for recurrence and mortality). Findings Patients entered the trials from 1983 to 2002 and median follow-up was 9 years (IQR 5–14), with the last follow-up in 2013. Most chemotherapy was anthracycline based (3838 [81%] of 4756 women). More than two thirds (1349 [69%] of 1947) of women allocated NACT had a complete or partial clinical response. Patients allocated NACT had an increased frequency of breast-conserving therapy (1504 [65%] of 2320 treated with NACT vs 1135 [49%] of 2318 treated with adjuvant chemotherapy). NACT was associated with more frequent local recurrence than was adjuvant chemotherapy: the 15 year local recurrence was 21·4% for NACT versus 15·9% for adjuvant chemotherapy (5·5% increase [95% CI 2·4–8·6]; rate ratio 1·37 [95% CI 1·17–1·61]; p=0·0001). No significant difference between NACT and adjuvant chemotherapy was noted for distant recurrence (15 year risk 38·2% for NACT vs 38·0% for adjuvant chemotherapy; rate ratio 1·02 [95% CI 0·92–1·14]; p=0·66), breast cancer mortality (34·4% vs 33·7%; 1·06 [0·95–1·18]; p=0·31), or death from any cause (40·9% vs 41·2%; 1·04 [0·94–1·15]; p=0·45). Interpretation Tumours downsized by NACT might have higher local recurrence after breast-conserving therapy than might tumours of the same dimensions in women who have not received NACT. Strategies to mitigate the increased local recurrence after breast-conserving therapy in tumours downsized by NACT should be considered—eg, careful tumour localisation, detailed pathological assessment, and appropriate radiotherapy

CubeSat constellation deployment strategies

CubeSat based constellations are limited by launch opportunities, manoeuvring, and reliability. In this paper, an approach is proposed to determine the performance of a constellation, using different deployment strategies. Due to low maneuverability and limited launch options, CubeSats require deployment strategies that determine the optimal launch method and maneuvers to ensure rapid deployment, and replacement in case of failure. To do so, a model is developed that applies a Monte Carlo method through repeated sampling of the satellite lifetimes. By simulating discrete realizations of the constellation, over the mission lifetime, the probability distribution of the strategies performance is derived. By comparing deployment strategies, the model can be used to design for the optimal deployment strategy.</p

CubeSat constellation deployment strategies

CubeSat based constellations are limited by launch opportunities, manoeuvring, and reliability. In this paper, an approach is proposed to determine the performance of a constellation, using different deployment strategies. Due to low maneuverability and limited launch options, CubeSats require deployment strategies that determine the optimal launch method and maneuvers to ensure rapid deployment, and replacement in case of failure. To do so, a model is developed that applies a Monte Carlo method through repeated sampling of the satellite lifetimes. By simulating discrete realizations of the constellation, over the mission lifetime, the probability distribution of the strategies performance is derived. By comparing deployment strategies, the model can be used to design for the optimal deployment strategy.Space Systems Egineerin

Systemic treatment of early breast-cancer by hormonal, cytotoxic, or immune therapy: 133 randomized trials involving 31000 recurrences and 24000 deaths among 75000 women: 1

In a worldwide collaboration, information was sought and centrally checked on mortality and recurrence for each woman in any randomised trial that began before 1985 of any aspect of systemic adjuvant therapy for early breast cancer. Checked data were available for 75 000 women (about 90% of those ever randomised), of whom 32% had died and another 10% had experienced recurrence. The parts now reviewed include 30 000 women in tamoxifen trials, 3000 in ovarian ablation trials, 11 000 in polychemotherapy trials, 15 000 in other chemotherapy comparisons, and 6000 in immunotherapy trials. Highly significant reductions in the annual rates both of recurrence and of death are produced by tamoxifen (25% SD 2 recurrence and 17% SD 2 mortality: 2p < 0.00001 ), by ablation below age 50 (26% SD 6 recurrence and 25% SD 7 mortality: 2p = 0.0004),and by polychemotherapy (28% SD 3 recurrence and 16% SD 3 mortality: 2p < 0.00001), but not by ablation at older ages or by immunotherapy. (Tamoxifen also reduced the risk of development of contralateral breast cancer by 39% SD 9: lp < 0-00001.) For tamoxifen and for polychemotherapy the avoidance of recurrence is chiefly during years 0-4 (this difference being maintained but not increased afterwards), but the avoidance of mortality is highly significant both during and after years 0-4, so the cumulative differences in survival produced by these relatively brief treatments (median: 2 years tamoxifen, 1 year polychemotherapy) are larger at 10 than at 5 years. There is little information beyond year 10 (except for ovarian ablation, which produces separately significant mortality reductions both during and after years 0-9). Both direct and indirect randomised comparisons show long-term polychemotherapy (eg, 12 months) to be no better than shorter (eg, 6 months) regimens, but do show polychemotherapy to be significantly better than single-agent chemotherapy. Indirect randomised comparisons do not reveal significant differences between different forms of polychemotherapy, or differences between different tamoxifen doses, but do show that long-term tamoxifen (eg, 2 years, Gr even 5 years) is significantly more effective than shorter tamoxifen regimens. In old age (70+) tamoxifen is of demonstrated efficacy, but chemotherapy has not been evaluated. Between ages 50 and 69 direct comparisons show that chemotherapy plus tamoxifen is better (1 p < 0.00001) than chemotherapy alone both for recurrence and for mortality, and better (1 p < 0.00001) than tamoxifen alone for recurrence. in women aged under 50 chemotherapy and ovarian ablation appear, by an indirect comparison, to be of comparable efficacy, and the combination may be still better. The 30-40% proportional risk reductions that can be produced by combined chemo-endocrine therapy in middle age are similar for node-positive and for node-negative patients, but the absolute improvement in 10-year survival is about twice as great for the former (at least 12 deaths avoided per 100 women treated) as for the latter