The Helicobacter pylori Genome Project : insights into H. pylori population structure from analysis of a worldwide collection of complete genomes

Helicobacter pylori, a dominant member of the gastric microbiota, shares co-evolutionary history with humans. This has led to the development of genetically distinct H. pylori subpopulations associated with the geographic origin of the host and with differential gastric disease risk. Here, we provide insights into H. pylori population structure as a part of the Helicobacter pylori Genome Project (HpGP), a multi-disciplinary initiative aimed at elucidating H. pylori pathogenesis and identifying new therapeutic targets. We collected 1011 well-characterized clinical strains from 50 countries and generated high-quality genome sequences. We analysed core genome diversity and population structure of the HpGP dataset and 255 worldwide reference genomes to outline the ancestral contribution to Eurasian, African, and American populations. We found evidence of substantial contribution of population hpNorthAsia and subpopulation hspUral in Northern European H. pylori. The genomes of H. pylori isolated from northern and southern Indigenous Americans differed in that bacteria isolated in northern Indigenous communities were more similar to North Asian H. pylori while the southern had higher relatedness to hpEastAsia. Notably, we also found a highly clonal yet geographically dispersed North American subpopulation, which is negative for the cag pathogenicity island, and present in 7% of sequenced US genomes. We expect the HpGP dataset and the corresponding strains to become a major asset for H. pylori genomics

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Local recurrence following resection of intermediate-high risk nonmetastatic renal ell arcinoma: an anatomical lassification and analysis of the ASSURE (ECOG-ACRIN E2805) adjuvant trial

PURPOSE: We describe what is to our knowledge a novel classification system for local recurrence after surgery of renal cell carcinoma. We assessed its prognostic implications using prospective, randomized controlled data. MATERIALS AND METHODS: We queried the ASSURE (Sunitinib Malate or Sorafenib Tosylate in Treating Patients With Kidney Cancer That Was Removed By Surgery) (ECOG-ACRIN [Eastern Cooperative Oncology Group-American College of Radiology Imaging Network] E2805) trial data for patients with fully resected, intermediate-high risk, nonmetastatic renal cell carcinoma with local recurrence. We used certain definitions, including type I-single recurrence in a remnant kidney or ipsilateral renal fossa, type II-single recurrence in the ipsilateral vasculature, the ipsilateral adrenal gland or a lymph node, type III-single recurrence in other intra-abdominal soft tissues or organs and type IV-any combination of types I-III or multiple recurrences of a single type. Multivariable logistic regression and the log rank test were performed to identify clinicopathological predictors and compare survival, respectively. RESULTS: Of the 1,943 patients 300 (15.4%) had local recurrence, which was type I, II, III and IV in 66 (22.0%), 97 (32.3%), 87 (29.0%) and 50 (16.7%), respectively. Surgical modality (minimally invasive vs open) and type of surgery (partial vs radical) did not predict any local recurrence. Five-year cancer specific survival and overall survival were worse in patients with type IV recurrence (each p CONCLUSIONS: In patients with intermediate-high risk nonmetastatic renal cell carcinoma local recurrence appears to be a function of biology more than of surgical modality or surgery type. The prognosis for solitary intra-abdominal local recurrences appear similar regardless of location (types I-III). Local recurrences involving multiple sites and/or subdivisions are associated with worse survival (type IV)

Development and validation of a questionnaire to assess the doctors and nurses knowledge of acute oxygen therapy.

BACKGROUND:Prescription and administration of oxygen in emergencies by healthcare providers are reported to be inappropriate in most settings. There is a huge gap in the knowledge of health care providers on various aspects of oxygen therapy, and this may be a barrier to optimal oxygen administration. Hence, it is essential to ascertain providers' knowledge of acute oxygen therapy so that appropriate educational interventions are instituted for better delivery. There is no available validated instrument to assess knowledge of acute oxygen therapy. The study aimed to develop, validate and evaluate the test-retest reliability of a questionnaire to determine the doctors and nurses understanding of acute oxygen therapy. METHODS:This study involved the development of the questionnaire contents by a literature review, assessment of face validity (n = 5), content validity, using a panel of experts (n = 10), item analysis and test-retest reliability among a sample (n = 121) of doctors and nurses. RESULTS:Face validity indicated that the questionnaire was quick to complete (10-15 min), most items were easy to follow and comprehensible. The global content validity index (S-CVI) was 0.85. The test-retest reliability statistics showed a kappa coefficient of 0.546-0.897 (all P<0.001) and percentage agreement of 80-98.3% indicating high temporal stability in the target population. In total, 90% of the items fulfilled the reliability acceptance criteria. Item discrimination analysis showed that most questions were at an acceptable level. The final questionnaire included 37 item questions and eight sections. CONCLUSION:The designed questionnaire is a reliable and valid tool for assessing knowledge of acute oxygen therapy among doctors and nurses

Local Recurrence Following Resection of Intermediate-High Risk Nonmetastatic Renal Cell Carcinoma: An Anatomical Classification and Analysis of the ASSURE (ECOG-ACRIN E2805) Adjuvant Trial.

PurposeWe describe what is to our knowledge a novel classification system for local recurrence after surgery of renal cell carcinoma. We assessed its prognostic implications using prospective, randomized controlled data.Materials and methodsWe queried the ASSURE (Sunitinib Malate or Sorafenib Tosylate in Treating Patients With Kidney Cancer That Was Removed By Surgery) (ECOG-ACRIN [Eastern Cooperative Oncology Group-American College of Radiology Imaging Network] E2805) trial data for patients with fully resected, intermediate-high risk, nonmetastatic renal cell carcinoma with local recurrence. We used certain definitions, including type I-single recurrence in a remnant kidney or ipsilateral renal fossa, type II-single recurrence in the ipsilateral vasculature, the ipsilateral adrenal gland or a lymph node, type III-single recurrence in other intra-abdominal soft tissues or organs and type IV-any combination of types I-III or multiple recurrences of a single type. Multivariable logistic regression and the log rank test were performed to identify clinicopathological predictors and compare survival, respectively.ResultsOf the 1,943 patients 300 (15.4%) had local recurrence, which was type I, II, III and IV in 66 (22.0%), 97 (32.3%), 87 (29.0%) and 50 (16.7%), respectively. Surgical modality (minimally invasive vs open) and type of surgery (partial vs radical) did not predict any local recurrence. Five-year cancer specific survival and overall survival were worse in patients with type IV recurrence (each p &lt;0.001). There was no difference in survival among patients with types I to III recurrence.ConclusionsIn patients with intermediate-high risk nonmetastatic renal cell carcinoma local recurrence appears to be a function of biology more than of surgical modality or surgery type. The prognosis for solitary intra-abdominal local recurrences appear similar regardless of location (types I-III). Local recurrences involving multiple sites and/or subdivisions are associated with worse survival (type IV)

Predicting Renal Cancer Recurrence: Defining Limitations of Existing Prognostic Models With Prospective Trial-Based Validation.

PurposeTo validate currently used recurrence prediction models for renal cell carcinoma (RCC) by using prospective data from the ASSURE (ECOG-ACRIN E2805; Adjuvant Sorafenib or Sunitinib for Unfavorable Renal Carcinoma) adjuvant trial.Patients and methodsEight RCC recurrence models (University of California at Los Angeles Integrated Staging System [UISS]; Stage, Size, Grade, and Necrosis [SSIGN]; Leibovich; Kattan; Memorial Sloan Kettering Cancer Center [MSKCC]; Yaycioglu; Karakiewicz; and Cindolo) were selected on the basis of their use in clinical practice and clinical trial designs. These models along with the TNM staging system were validated using 1,647 patients with resected localized high-grade or locally advanced disease (≥ pT1b grade 3 and 4/pTanyN1Mo) from the ASSURE cohort. The predictive performance of the model was quantified by assessing its discriminatory and calibration abilities.ResultsProspective validation of predictive and prognostic models for localized RCC showed a substantial decrease in each of the predictive abilities of the model compared with their original and externally validated discriminatory estimates. Among the models, the SSIGN score performed best (0.688; 95% CI, 0.686 to 0.689), and the UISS model performed worst (0.556; 95% CI, 0.555 to 0.557). Compared with the 2002 TNM staging system (C-index, 0.60), most models only marginally outperformed standard staging. Importantly, all models, including TNM, demonstrated statistically significant variability in their predictive ability over time and were most useful within the first 2 years after diagnosis.ConclusionIn RCC, as in many other solid malignancies, clinicians rely on retrospective prediction tools to guide patient care and clinical trial selection and largely overestimate their predictive abilities. We used prospective collected adjuvant trial data to validate existing RCC prediction models and demonstrate a sharp decrease in the predictive ability of all models compared with their previous retrospective validations. Accordingly, we recommend prospective validation of any predictive model before implementing it into clinical practice and clinical trial design

Predicting Disease Recurrence, Early Progression, and Overall Survival Following Surgical Resection for High-risk Localized and Locally Advanced Renal Cell Carcinoma

BackgroundRisk stratification for localized renal cell carcinoma (RCC) relies heavily on retrospective models, limiting their generalizability to contemporary cohorts.ObjectiveTo introduce a contemporary RCC prognostic model, developed using prospective, highly annotated data from a phase III adjuvant trial.Design, setting, and participantsThe model utilizes outcome data from the ECOG-ACRIN 2805 (ASSURE) RCC trial.Outcome measurements and statistical analysisThe primary outcome for the model is disease-free survival (DFS), with overall survival (OS) and early disease progression (EDP) as secondary outcomes. Model performance was assessed using discrimination and calibration tests.Results and limitationsA total of 1735 patients were included in the analysis, with 887 DFS events occurring over a median follow-up of 9.6 yr. Five common tumor variables (histology, size, grade, tumor necrosis, and nodal involvement) were included in each model. Tumor histology was the single most powerful predictor for each model outcome. The C-statistics at 1 yr were 78.4% and 81.9% for DFS and OS, respectively. Degradation of the DFS, DFS validation set, and OS model's discriminatory ability was seen over time, with a global c-index of 68.0% (95% confidence interval or CI [65.5, 70.4]), 68.6% [65.1%, 72.2%], and 69.4% (95% CI [66.9%, 71.9%], respectively. The EDP model had a c-index of 75.1% (95% CI [71.3, 79.0]).ConclusionsWe introduce a contemporary RCC recurrence model built and internally validated using prospective and highly annotated data from a clinical trial. Performance characteristics of the current model exceed available prognostic models with the added benefit of being histology inclusive and TNM agnostic.Patient summaryImportant decisions, including treatment protocols, clinical trial eligibility, and life planning, rest on our ability to predict cancer outcomes accurately. Here, we introduce a contemporary renal cell carcinoma prognostic model leveraging high-quality data from a clinical trial. The current model predicts three outcome measures commonly utilized in clinical practice and exceeds the predictive ability of available prognostic models

Predicting disease recurrence, early progression, and overall survival following surgical resection for high-risk localized and locally advanced renal cell carcinoma

BACKGROUND: Risk stratification for localized renal cell carcinoma (RCC) relies heavily on retrospective models, limiting their generalizability to contemporary cohorts. OBJECTIVE: To introduce a contemporary RCC prognostic model, developed using prospective, highly annotated data from a phase III adjuvant trial. DESIGN, SETTING, AND PARTICIPANTS: The model utilizes outcome data from the ECOG-ACRIN 2805 (ASSURE) RCC trial. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome for the model is disease-free survival (DFS), with overall survival (OS) and early disease progression (EDP) as secondary outcomes. Model performance was assessed using discrimination and calibration tests. RESULTS AND LIMITATIONS: A total of 1735 patients were included in the analysis, with 887 DFS events occurring over a median follow-up of 9.6 yr. Five common tumor variables (histology, size, grade, tumor necrosis, and nodal involvement) were included in each model. Tumor histology was the single most powerful predictor for each model outcome. The C-statistics at 1 yr were 78.4% and 81.9% for DFS and OS, respectively. Degradation of the DFS, DFS validation set, and OS model\u27s discriminatory ability was seen over time, with a global c-index of 68.0% (95% confidence interval or CI [65.5, 70.4]), 68.6% [65.1%, 72.2%], and 69.4% (95% CI [66.9%, 71.9%], respectively. The EDP model had a c-index of 75.1% (95% CI [71.3, 79.0]). CONCLUSIONS: We introduce a contemporary RCC recurrence model built and internally validated using prospective and highly annotated data from a clinical trial. Performance characteristics of the current model exceed available prognostic models with the added benefit of being histology inclusive and TNM agnostic. PATIENT SUMMARY: Important decisions, including treatment protocols, clinical trial eligibility, and life planning, rest on our ability to predict cancer outcomes accurately. Here, we introduce a contemporary renal cell carcinoma prognostic model leveraging high-quality data from a clinical trial. The current model predicts three outcome measures commonly utilized in clinical practice and exceeds the predictive ability of available prognostic models

Transferability of genetic risk scores in African populations.

The poor transferability of genetic risk scores (GRSs) derived from European ancestry data in diverse populations is a cause of concern. We set out to evaluate whether GRSs derived from data of African American individuals and multiancestry data perform better in sub-Saharan Africa (SSA) compared to European ancestry-derived scores. Using summary statistics from the Million Veteran Program (MVP), we showed that GRSs derived from data of African American individuals enhance polygenic prediction of lipid traits in SSA compared to European and multiancestry scores. However, our GRS prediction varied greatly within SSA between the South African Zulu (low-density lipoprotein cholesterol (LDL-C), R2 = 8.14%) and Ugandan cohorts (LDL-C, R2 = 0.026%). We postulate that differences in the genetic and environmental factors between these population groups might lead to the poor transferability of GRSs within SSA. More effort is required to optimize polygenic prediction in Africa