Neutropenic sepsis rates in patients receiving bleomycin, etoposide and cisplatin chemotherapy using olanzapine and reduced doses of dexamethasone compared to a standard antiemetic regimen.

OBJECTIVE: To investigate whether the use of a steroid-sparing antiemetic protocol (substituting dexamethasone with olanzapine) affects the incidence of neutropenia and associated hospital admissions in patients receiving bleomycin, etoposide and cisplatin (BEP) chemotherapy. PATIENTS AND METHODS: Records from 108 patients who received BEP at St Bartholomew's Hospital, London were divided into two groups according to antiemetic regimen. Group 1 (treated 2008-2013) were treated with a steroid-containing antiemetic protocol and group 2 (treated 2014-2017) were treated according to a steroid-sparing protocol, i.e. using olanzapine. Outcomes included incidence of neutropenia at nadir blood count, severity of neutropenia, hospital admissions attributable to febrile neutropenia (FN) and baseline risk factors associated with FN. Statistical analyses were performed using two-sided chi-squared tests. RESULTS: The baseline characteristics of the two groups were balanced with regard to age, gender, histology, and proportion of patients with International Germ Cell Cancer Collaborative Group poor-risk disease. The incidence of neutropenia of any grade (group 1, 96.2%; group 2, 98.1%) was similar, although group 2 had more patients with severe neutropenia than group 2 (77.7% vs 88.8%). There was a significant difference in FN incidence (group 1, 22%; group 2 7.5%; P = 0.030). Most cases of FN occurred in cycle 1. Two baseline characteristics were over-represented in patients who developed FN: female sex and age ≥50 years. CONCLUSION: By comparing two cohorts who received prophylactic antibiotics, our audit suggests that rates of FN-related admissions were lower in the cohort of patients in whom we employed a steroid-sparing antiemetic protocol.

Impact of secondary cytoreductive surgery on survival in patients with platinum sensitive recurrent ovarian cancer: analysis of the CALYPSO trial.

OBJECTIVE: The role of secondary cytoreductive surgery (SCR) in platinum-sensitive recurrent ovarian cancer (ROC) remains controversial. The overall survival (OS) benefits for surgery reported in observational studies may be due to the selection of patients with better prognosis. METHODS: Using data from the CALYPSO trial, OS of patients who had SCR was compared to those treated with chemotherapy alone. Multivariate analyses were performed to adjust for prognostic factors. We also tested for an interaction between baseline prognostic groupings and the benefit of surgery. RESULTS: Of the 975 patients randomised in CALYPSO, 19% had SCR and 80% had chemotherapy alone. OS was longer for the SCR group than for chemotherapy alone (median, 49.9 vs. 29.7 months; adjusted hazard ratio (HR), 0.68; P = 0.004). For patients with SCR, the 3-year OS was 72% for those with no measurable disease, and 28% if residual tumour was larger than 5 cm. Patients with good prognostic features benefited the most from SCR (HR 0.43; P < 0.001). The benefit of SCR was less in patients with poorer prognostic features (test of trend P < 0.001). CONCLUSION: SCR was associated with improved OS in platinum-sensitive ROC, particularly in patients with favourable prognostic characteristics. However, these findings may be due to selection bias, and hence randomised trials are still essential.

Self-supervised deep learning for highly efficient spatial immunophenotyping.

BACKGROUND: Efficient biomarker discovery and clinical translation depend on the fast and accurate analytical output from crucial technologies such as multiplex imaging. However, reliable cell classification often requires extensive annotations. Label-efficient strategies are urgently needed to reveal diverse cell distribution and spatial interactions in large-scale multiplex datasets. METHODS: This study proposed Self-supervised Learning for Antigen Detection (SANDI) for accurate cell phenotyping while mitigating the annotation burden. The model first learns intrinsic pairwise similarities in unlabelled cell images, followed by a classification step to map learnt features to cell labels using a small set of annotated references. We acquired four multiplex immunohistochemistry datasets and one imaging mass cytometry dataset, comprising 2825 to 15,258 single-cell images to train and test the model. FINDINGS: With 1% annotations (18-114 cells), SANDI achieved weighted F1-scores ranging from 0.82 to 0.98 across the five datasets, which was comparable to the fully supervised classifier trained on 1828-11,459 annotated cells (-0.002 to -0.053 of averaged weighted F1-score, Wilcoxon rank-sum test, P = 0.31). Leveraging the immune checkpoint markers stained in ovarian cancer slides, SANDI-based cell identification reveals spatial expulsion between PD1-expressing T helper cells and T regulatory cells, suggesting an interplay between PD1 expression and T regulatory cell-mediated immunosuppression. INTERPRETATION: By striking a fine balance between minimal expert guidance and the power of deep learning to learn similarity within abundant data, SANDI presents new opportunities for efficient, large-scale learning for histology multiplex imaging data. FUNDING: This study was funded by the Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre.

Targeted Therapies for Ovarian Cancer.

Epithelial ovarian cancer has the highest mortality rate of all gynaecological malignancies. Most women present with advanced disease and develop a recurrence after radical surgery and chemotherapy. Improving the results of first- or subsequent-line chemotherapy has been slow, and novel approaches to systemic treatment are needed. Ovarian cancer is a heterogeneous disease with complex molecular and genetic changes. Understanding these better will provide information on the mechanisms of resistance and opportunities to target therapy more rationally, exploiting specific changes in the tumour. Here we reviewed targeted approaches to therapy, focussing on targeting angiogenesis and inhibition of DNA repair, 2 areas that show promising activity. Additionally, we reviewed studies that are underway, targeting the cell cycle, signalling pathways and immunotherapeutic strategies. Many of these innovative approaches already demonstrate promising activity in ovarian cancer and have the potential to improve the outcome in women with ovarian cancer.