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.     

Investigation of Bimetallic Nickel Catalysts in Catalyst‐Transfer Polymerization of π‐Conjugated Polymers

A comparative study involving bimetallic nickel catalysts designed from disubstituted N,N,N′,N′‐tetra(diphenylphosphanylmethyl)benzene diamine bridging ligands is reported. Catalyst behavior is explored in the Kumada catalyst‐transfer polymerization (KCTP) using poly(3‐hexylthiophene) (P3HT) as the model system. The success of a controlled polymerization is monitored by analyzing monomer conversion, degree of polymerization, end‐group identity, and molecular weight distribution. The characterization of P3HT obtained from KCTP initiated with the bimetallic catalysts shows chain‐growth behavior; however, the presence of Br/Br end‐groups and broader molecular weight distribution reveals a reduced controlled polymerization compared to the commonly employed Ni(dppp)Cl₂. The observed increase in intermolecular chain transfer and termination processes in KCTP initiation with the bimetallic catalysts can be attributed to a weaker Ni(0)‐π‐aryl complex interaction, which is caused by increased steric crowding of the coordination sphere.