PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy

PurposeAuto-contouring may reduce workload, interobserver variation, and time associated with manual contouring of organs at risk. Manual contouring remains the standard due in part to uncertainty around the time and workload savings after accounting for the review and editing of auto-contours. This preliminary study compares a standard manual contouring workflow with 2 auto-contouring workflows (atlas and deep learning) for contouring the bladder and rectum in patients with prostate cancer.Methods and MaterialsThree contouring workflows were defined based on the initial contour-generation method including manual (MAN), atlas-based auto-contour (ATLAS), and deep-learning auto-contour (DEEP). For each workflow, initial contour generation was retrospectively performed on 15 patients with prostate cancer. Then, radiation oncologists (ROs) edited each contour while blinded to the manner in which the initial contour was generated. Workflows were compared by time (both in initial contour generation and in RO editing), contour similarity, and dosimetric evaluation.ResultsMean durations for initial contour generation were 10.9 min, 1.4 min, and 1.2 min for MAN, DEEP, and ATLAS, respectively. Initial DEEP contours were more geometrically similar to initial MAN contours. Mean durations of the RO editing steps for MAN, DEEP, and ATLAS contours were 4.1 min, 4.7 min, and 10.2 min, respectively. The geometric extent of RO edits was consistently larger for ATLAS contours compared with MAN and DEEP. No differences in clinically relevant dose-volume metrics were observed between workflows.ConclusionAuto-contouring software affords time savings for initial contour generation; however, it is important to also quantify workload changes at the RO editing step. Using deep-learning auto-contouring for bladder and rectum contour generation reduced contouring time without negatively affecting RO editing times, contour geometry, or clinically relevant dose–volume metrics. This work contributes to growing evidence that deep-learning methods are a clinically viable solution for organ-at-risk contouring in radiation therapy.     

Metastatic adult-type non-rhabdomyosarcoma soft tissue sarcomas in children and adolescents: A cohort study from the European paediatric Soft tissue sarcoma Study Group

Background

Limited data exist on the clinical behavior of pediatric non-rhabdomyosarcoma soft tissue sarcomas (NRSTS) with distant metastases at onset, and a clear standard of care has not yet been defined.

Methods

This cohort study reports on pediatric adult-type metastatic NRSTS enrolled in two concurrent prospective European studies, i.e., the randomized BERNIE study and the single-arm MTS 2008 study developed by the European paediatric Soft tissue sarcoma Study Group. Treatment programs were originally designed for patients with metastatic rhabdomyosarcoma, i.e., nine courses of multidrug chemotherapy (with or without bevacizumab in the BERNIE study), followed by 12 cycles of maintenance therapy, whereas radiotherapy and/or surgery (on primary tumor and/or metastases) were delayed until after seven courses of chemotherapy had been administered.

Results

The study included 61 patients <21 years old treated from July 2008 to December 2016. The lung was the site of metastases in 75% of the cases. All patients received multi-agent chemotherapy, 44% had local therapy to primary tumor, and 18% had treatment of metastases. Median time to progression/relapse was 6 months. A high rate of tumor progression was observed during the initial part of the chemotherapy program. With a median follow-up of 41.5 months (range, 2–111 months), 3-year event-free survival and overall survival were 15.4% (95% confidence interval [CI], 7.6–25.7) and 34.9% (95% CI, 22.7–47.5), respectively. There were no statistically significant differences in outcome depending on the type of treatment administered.

Conclusions

The study confirmed the overall poor outcome for patients with metastatic NRSTS, whose treatment remains a challenge.

Plain Language Summary

• Pediatric non-rhabdomyosarcoma soft tissue sarcomas form a heterogeneous group of rare tumors.
• Although recent international studies have defined the standard of care for patients with localized disease, limited data are available on the clinical behavior of patients with distant metastases.
• This study on 61 metastatic cases treated on two prospective European protocols confirms that the chances of survival of such patients are often dismal and a standard treatment is still lacking.

     

Left ventricular mass in offspring of diabetic mothers: at 5–7 years old

International Journal of Diabetes in Developing Countries - Newborns of mothers with diabetes have increased risk for cardiac left ventricular (LV) hypertrophy. Diabetic pregnancy is also...