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Background  Reduction mammoplasty is a commonly performed cosmetic procedure in the UK. Wound breakdown and infection are damaging complications both for patient experience and for cosmetic outcome. The questions we as investigators wanted to answer were: according to the best available scientific data, firstly which patients are at greatest risk of developing complications following reduction mammaplasty, and secondly what strategies are being employed by surgeons to reduce the incidence of these complications? Methods A review was carried out according to PRISMA guidelines across multiple electronic databases The key words used were a combination of “reduction”, “mammaplasty”, “mammoplasty” or “infection”. The inclusion criteria for the searches related to studies published in English, and no time-frame limit was set. Studies which specifically compared outcomes between cancer and non-cancer resections were excluded. Following review of the literature, key risk factors for the development of wound breakdown or infection following reduction mammaplasty were identified, and the available evidence for each appraised. Subsequently, methods employed by surgeons to reduce the incidence of such complications were collated, and again the evidence behind each was summarised Results Smoking status, BMI and steroid use appear to be the patient risk factors with the greatest evidence to suggest they pose an increased risk of wound complication following RM. In terms of strategies to reduce wound complications, a single dose of preoperative antibiotics appears to have a beneficial effect on wound complications and infections notably. Conclusions Reduction mammoplasty is an important plastic surgery procedure, and further research is required to understand how to minimise expensive, and cosmetically detrimental wound complications. Patient selection, counselling and risk stratification are key. Future research focussing on methods or techniques to reduce complication rates such as novel ways to protect the T junction and the utilisation of newer skin closure devices may prove valuable. Level of evidence: Not ratable

The 2013 Breast Cancer Campaign gap analysis established breast cancer research priorities without a specific focus on surgical research or the role of surgeons on breast cancer research. This Review aims to identify opportunities and priorities for research in breast surgery to complement the 2013 gap analysis. To identify these goals, research-active breast surgeons met and identified areas for breast surgery research that mapped to the patient pathway. Areas included diagnosis, neoadjuvant treatment, surgery, adjuvant therapy, and attention to special groups (eg, those receiving risk-reducing surgery). Section leads were identified based on research interests, with invited input from experts in specific areas, supported by consultation with members of the Association of Breast Surgery and Independent Cancer Patients' Voice groups. The document was iteratively modified until participants were satisfied that key priorities for surgical research were clear. Key research gaps included issues surrounding overdiagnosis and treatment; optimising treatment options and their selection for neoadjuvant therapies and subsequent surgery; reducing rates of re-operations for breast-conserving surgery; generating evidence for clinical effectiveness and cost-effectiveness of breast reconstruction, and mechanisms for assessing novel interventions; establishing optimal axillary management, especially post-neoadjuvant treatment; and defining and standardising indications for risk-reducing surgery. We propose strategies for resolving these knowledge gaps. Surgeons are ideally placed for a central role in breast cancer research and should foster a culture of engagement and participation in research to benefit patients and health-care systems. Development of infrastructure and surgical research capacity, together with appropriate allocation of research funding, is needed to successfully address the key clinical and translational research gaps that are highlighted in this Review within the next two decades.

Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a rare cancer, and few studies have comprehensively investigated the immune microenvironment and rare lymphocyte-predominant (LP) cells. Here we develop a NLPHL specific lymphocyte-predominant ecotype (LPE) model to identify 34 distinct cell states across 14 cell types that co-occur within 3 LPEs for 171 cases. LPE1 and LPE2 were characterized by immunosuppressive microenvironments with high expression of B2M on LP cells, CD8 T-cell exhaustion, immune checkpoint genes expressed by follicular T-cells, and an improved freedom from progression compared to LPE3 in training ( n  = 109, with 65% LPE1/2) and validation cohorts ( n  = 62, with 61% LPE1/2). We validate the co-occurrence and co-localization of cell states using spatial transcriptomics. Protein expression of HLA-I and HLA-II on LP cells and SSTR2 on dendritic cells was predictive of LPE1 (C-statistic=0.69), LPE2 (C-statistic=0.79), and LPE3 (C-statistic=0.60). This study establishes a clinically relevant biologic categorization for NLPHL. Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a rare cancer. Here, the authors develop a NLPHL specific model to identify 34 distinct cell states across 14 cell types that co-occur within 3 lymphocyte predominant ecotypes (LPEs) for 171 cases.

Added to this mix is the global push to use modelled estimates (predictions) for programme monitoring when real data in real time is better fit for purpose.4 The various data platforms need to be rationalised, core indicator sets contextualised, and the culture of data use for decision making strengthened at different levels of health systems. Realising the gains available from the proliferation of guidance needs actors at multiple levels to have the capacity, motivation, incentive and confidence to use data and not be overwhelmed by its complexity. [...]making data more relevant will need more investment in institutions and people. Taking the example of effective coverage measurement, multiple dimensions of healthcare quality have been integrated in mainstream measurement guidance,6 digital tools have been developed, methods tested for linking relevant data sources and some engagement in countries undertaken to pressure test these innovations. [...]the coverage of healthcare for women and children is increasing and disparities are narrowing in many settings.7 But despite wide-spread description, the same types of inequalities often persist.