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Background and objective: Patients diagnosed with grade group (GG) 1 prostate cancer (PCa) following treatment for benign disease (“incidental” PCa) are typically managed with active surveillance (AS). It is not known how their outcomes compare with those observed in patients diagnosed with GG1 on biopsy. We aimed at determining whether long-term oncologic outcomes of AS for patients with GG1 PCa differ according to the type of diagnosis: incidental versus biopsy detected. Methods: A retrospective, multi-institutional analysis of PCa patients with GG1 on AS at eight institutions was conducted. Competing risk analyses estimated the incidence of metastases, PCa mortality, and conversion to treatment. As a secondary analysis, we estimated the risk of GG ≥2 on the first follow-up biopsy according to the type of initial diagnosis. Key findings and limitations: A total of 213 versus 1900 patients with incidental versus biopsy-diagnosed GG1 were identified. Patients with incidental cancers were followed with repeated biopsies and multiparametric magnetic resonance imaging less frequently than those diagnosed on biopsy. The 10-yr incidence of treatment was 22% for incidental cancers versus 53% for biopsy (subdistribution hazard ratio [sHR] 0.34, 95% confidence interval [CI] 0.26–0.46, p

Background: Frailty, rather than age, is associated with postoperative morbidity and mortality. We sought to determine whether preoperative frailty as defined by a novel scoring system could predict the outcomes among older patients undergoing esophagectomy. Methods: We identified patients 65 years or older who underwent esophagectomy between 2011 and 2021 at our institution. Frailty was assessed using the MSK-FI, which consists of 1 component related to functional status and 10 medical comorbidities. We used a multivariable logistic regression model to test for the associations between frailty and short-term outcomes, with continuous frailty score as the predictor and additionally adjusted for age and Eastern Cooperative Oncology Group performance status. Results: In total, 447 patients were included in the analysis (median age of 71 years [interquartile range, 68–75]). Most of the patients underwent neoadjuvant treatment (81%), an Ivor Lewis esophagectomy (86%), and minimally invasive surgery (55%). A total of 22 patients (4.9%) died within 90 days of surgery, 144 (32%) had a major complication, 81 (19%) were readmitted, and 31 (7.2%) were discharged to a facility. Of the patients who died within 90 days, 19 had a major complication, yielding a failure-to-rescue rate of 13%. The risk of 30-day major complications (OR, 1.24 [95% CI, 1.09–1.41]; p = 0.001), readmissions (OR, 1.31 [95% CI, 1.13–1.52]; p < 0.001), and discharge to a facility (OR, 1.86 [95% CI, 1.49–2.37]; p < 0.001) increased with increasing frailty. Frailty and 90-day mortality were not associated. Conclusions: Frailty assessment during surgery decision-making can identify patients with a high risk of morbidity.

Abstract Background A common method of pain assessment is the numerical rating scale, where patients are asked to rate their pain on a scale from 0 to 10, where 0 is “no pain” and 10 is “pain as bad as you can imagine”. We hypothesize such language is suboptimal as it involves a test of a cognitive skill, imagination, in the assessment of symptom severity. Methods We used a large-scale online research registry, ResearchMatch, to conduct a randomized controlled trial to compare the distributions of pain scores of two different pain scale anchors. We recruited adults located in the United States who reported a chronic pain problem (> 3 months) and were currently in pain. Participants were randomized in a 1:1 ratio to receive pain assessment based on a modified Brief Pain Inventory (BPI), where the anchor for a score of 10 was either “extremely severe pain”, or the original BPI, with the anchor “pain as bad as you can imagine”. Participants in both groups also answered additional questions about pain, other symptomatology and creativity. Results Data were obtained from 405 participants for the modified and 424 for the original BPI. Distribution of responses to pain questions were similar between groups (all p-values ≥ 0.12). We did not see evidence that the relationship between pain score and the anchor text differed based on self-perceived creativity (all interaction p-values ≥ 0.2). However, in the key analysis, correlations between current pain assessments and known correlates (fatigue, anxiety, depression, current pain compared to a typical day, pain compared to other people) were stronger for “extreme” vs. “imaginable” anchor text (p = 0.005). Conclusion Pain rating scales should utilize the modified anchor text “extremely severe pain” instead of “pain as bad as you can imagine”. Further research should explore the effects of anchors for other symptoms.

Abstract Background Verbal rating scales (VRS) are widely used in patient-reported outcome (PRO) measures. At our institution, patients complete an online instrument using VRSs with a five-point brief response scale to assess symptoms as part of routine follow-up after ambulatory cancer surgery. We received feedback from patients that the brief VRS descriptors such as “mild” or “somewhat” were vague. We added explicit descriptors to our VRSs, for instance, “Mild: I can generally ignore my pain” for pain severity or “Somewhat: I can do some things okay, but most of my daily activities are harder because of fatigue” for fatigue interference. We then compared responses before and after this change was made. Methods The symptoms investigated were pain, fatigue and nausea. Our hypothesis was that the explicit descriptors would reduce overall variance. We therefore compared the coefficient of variation of scores and tested the association between symptoms scores and known predictors thereof. We also compared time to completion between questionnaires with and without the additional descriptors. Results A total of 17,500 patients undergoing 21,497 operations were assigned questionnaires in the period before the descriptors were added; allowing for a short transition period, 1,417 patients having 1436 operations were assigned questionnaires with the additional descriptors. Symptom scores were about 10% lower with the additional descriptors but the coefficient of variation was slightly higher. Moreover, the only statistically significant difference between groups for association with a known predictor favored the item without the additional language for nausea severity (p = 0.004). Total completion time was longer when the instrument included the additional descriptors, particularly the first and second time that the questionnaire was completed. Conclusions Adding descriptors to a VRS of post-operative symptoms did not improve scale properties in patients undergoing ambulatory cancer surgery. We have removed the additional descriptors from our tool. We recommend further comparative psychometric research using data from PROs collected as part of routine clinical care.

The bacterial determinants that facilitate Mycobacterium tuberculosis (Mtb) adaptation to the human host environment are poorly characterized. We have sought to decipher the pressures facing the bacterium in vivo by assessing Mtb genes that are under positive selection in clinical isolates. One of the strongest targets of selection in the Mtb genome is lldD2, which encodes a quinone-dependent L-lactate dehydrogenase (LldD2) that catalyzes the oxidation of lactate to pyruvate. Lactate accumulation is a salient feature of the intracellular environment during infection and lldD2 is essential for Mtb growth in macrophages. We determined the extent of lldD2 variation across a set of global clinical isolates and defined how prevalent mutations modulate Mtb fitness. We show the stepwise nature of lldD2 evolution that occurs as a result of ongoing lldD2 selection in the background of ancestral lineage-defining mutations and demonstrate that the genetic evolution of lldD2 additively augments Mtb growth in lactate. Using quinone-dependent antibiotic susceptibility as a functional reporter, we also find that the evolved lldD2 mutations functionally increase the quinone-dependent activity of LldD2. Using 13C-lactate metabolic flux tracing, we find that lldD2 is necessary for robust incorporation of lactate into central carbon metabolism. In the absence of lldD2, label preferentially accumulates in dihydroxyacetone phosphate (DHAP) and glyceraldehyde-3-phosphate (G3P) and is associated with a discernible growth defect, providing experimental evidence for accrued lactate toxicity via the deleterious buildup of sugar phosphates. The evolved lldD2 variants increase lactate incorporation to pyruvate while altering triose phosphate flux, suggesting both an anaplerotic and detoxification benefit to lldD2 evolution. We further show that the mycobacterial cell is transcriptionally sensitive to the changes associated with altered lldD2 activity which affect the expression of genes involved in cell wall lipid metabolism and the ESX- 1 virulence system. Together, these data illustrate a multifunctional role of LldD2 that provides context for the selective advantage of lldD2 mutations in adapting to host stress.

Abstract Background A number of recent papers have proposed methods to calculate confidence intervals and p values for net benefit used in decision curve analysis. These papers are sparse on the rationale for doing so. We aim to assess the relation between sampling variability, inference, and decision-analytic concepts. Methods and results We review the underlying theory of decision analysis. When we are forced into a decision, we should choose the option with the highest expected utility, irrespective of p values or uncertainty. This is in some distinction to traditional hypothesis testing, where a decision such as whether to reject a given hypothesis can be postponed. Application of inference for net benefit would generally be harmful. In particular, insisting that differences in net benefit be statistically significant would dramatically change the criteria by which we consider a prediction model to be of value. We argue instead that uncertainty related to sampling variation for net benefit should be thought of in terms of the value of further research. Decision analysis tells us which decision to make for now, but we may also want to know how much confidence we should have in that decision. If we are insufficiently confident that we are right, further research is warranted. Conclusion Null hypothesis testing or simple consideration of confidence intervals are of questionable value for decision curve analysis, and methods such as value of information analysis or approaches to assess the probability of benefit should be considered instead.

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org. This article is the translation in to Russian by Dr. Ruslan Saygitov (ORCID: https://orcid.org/0000-0002-8915-6153) from the original published in [Ann Intern Med. 2015;162:W1-W73. doi: https://doi.org/10.7326/M14-0698].

Prostate cancer screening using prostate-specific antigen (PSA) reduces prostate cancer mortality at the cost of unnecessary prostate biopsy, overdiagnosis, and overtreatment. Several secondary tests have been developed to restrict biopsy to men at the greatest risk of high-grade disease. 4Kscore is a widely used secondary test that has been shown to reduce biopsy rates by approximately two-thirds in routine clinical practice. We estimated how 4Kscore implementation has affected cancer trends in the US population. We combined data from the US validation study of 4Kscore with data from the diagnostic test impact study, using a basis of 70 000 on-label 4Kscore tests performed annually. We estimate that each year, 4Kscore leads to 45 200 fewer biopsies and 9400 fewer overdiagnoses of low-grade cancer, at the cost of delayed diagnosis of high-grade prostate cancer for 3450 patients, of whom two-thirds have International Society of Urological Pathology grade group 2 disease. These findings need to be taken into consideration when studying epidemiologic trends in prostate cancer. They also suggest that high levels of overdiagnosis and overtreatment are not inevitable characteristics of PSA screening, but can be mitigated by additional tests. Patient summary: We estimate that use of a test called 4Kscore to predict the probability that a patient has high-grade prostate cancer has significantly reduced the number of unnecessary biopsies and overdiagnosis of low-grade cancer in the USA. These decisions may result in delayed diagnosis of high-grade cancer in some patients. 4Kscore is a useful additional test in the management of prostate cancer.

Enterotoxigenic Escherichia coli infections have been linked to non-diarrheal sequelae however, the reasons for this are unclear. Here, the authors present an additional role of heat-labile toxin in disrupting the structure and function of intestinal epithelial cells.

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org. For members of the TRIPOD Group, see the Appendix. This article is the translation in to Russian by Dr. Ruslan Saygitov (ORCID: 0000-0002-8915-6153) from the original published in [Ann Intern Med. 2015; 162:W1-W73. doi: 10.7326/M14-0698 ].

Purpose: The International Prostate Symptom Score (IPSS) is a widely used tool for evaluating patient-reported lower urinary tract symptoms. In this study, we assessed patients with prostate cancer and their understanding of IPSS questions. Methods and Materials: Consecutive patients with prostate cancer (N = 144) self-completed an online IPSS questionnaire within 1 week before their visit at our radiation oncology clinic. At the visit, a nurse reviewed each IPSS question to ensure the patient understood it and then verified the patient's answer. Preverified and nurse-verified scores were recorded and analyzed for discrepancies. Results: Complete concordance between preverified and nurse-verified responses to individual IPSS questions existed for 70 men (49%). In terms of overall IPSS score, 61 men (42%) had a lower or improved IPSS after nurse verification, and 9 men (6%) had a higher or worse IPSS. Before verification, patients overstated their symptoms of frequency, intermittency, and incomplete emptying. As a result of the nurse verification, 4 of 7 patients with IPSS in the severe range (20-35) were recategorized to the moderate range (8-19). Sixteen percent of patients whose preverified IPSS were in the moderate range were recategorized after nurse verification to the mild range (0-7). Treatment option eligibility changed for 10% of patients after nurse verification. Conclusions: Patients frequently misunderstand the IPSS questionnaire, leading them to respond in ways that do not accurately reflect their symptoms. Clinicians should verify patient understanding of the IPSS questions, particularly when using the score to determine eligibility for treatments.

Abstract Elevated prostate-specific antigen (PSA) levels often lead to unnecessary and possibly harmful transrectal ultrasound guided biopsy, e.g. when the biopsy is negative or contains only low-grade insignificant cancer, unlikely to become symptomatic in the man’s normal lifespan. A model based on four-kallikrein markers in blood (commercialized as 4Kscore) predicts risk of Grade group 2 or higher prostate cancer at biopsy, reducing unnecessary biopsies. We assessed whether these results extend to a single institution prostate biopsy cohort of Danish men and are enhanced by three microRNAs from urine (referred to as uCaP). The 4Kscore measured in cryopreserved blood from 234 men referred for 10+ core biopsy to Aarhus University Hospital, 29 with PSA > 25 ng/ml. We explored uCaP in urine from 157 of these men. Combined with age and DRE findings, both 4Kscore and uCaP could accurately predict Grade group 2 or higher prostate cancer (all patients: AUC = 0.802 and 0.797; PSA ≤ 25: AUC = 0.763 and 0.759). There was no additive effect when combining the 4Kscore and uCaP. Limitations include a study cohort with higher risk than commonly reported for biopsy cohorts. Our findings further support the clinical use of the 4Kscore to predict Grade group 2 or higher cancers in men being considered for biopsy.

Abstract Background We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user. Methods Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate cancer, defined as Gleason grade group ≥ 2 on standard TRUS prostate biopsy. One large European PBCG cohort was withheld for external validation, where calibration-in-the-large (CIL), calibration curves, and area-underneath-the-receiver-operating characteristic curve (AUC) were evaluated. Ten-fold leave-one-cohort-internal validation further validated the optimal missing data approach. Results Among 12,703 biopsies from 10 training cohorts, 3,597 (28%) had clinically significant prostate cancer, compared to 1,757 of 5,540 (32%) in the external validation cohort. In external validation, the available cases method that pooled individual patient data containing all risk factors input by an end-user had best CIL, under-predicting risks as percentages by 2.9% on average, and obtained an AUC of 75.7%. Imputation had the worst CIL (-13.3%). The available cases method was further validated as optimal in internal cross-validation and thus used for development of an online risk tool. For end-users of the risk tool, two risk factors were mandatory: serum prostate-specific antigen (PSA) and age, and ten were optional: digital rectal exam, prostate volume, prior negative biopsy, 5-alpha-reductase-inhibitor use, prior PSA screen, African ancestry, Hispanic ethnicity, first-degree prostate-, breast-, and second-degree prostate-cancer family history. Conclusion Developers of clinical risk prediction tools should optimize use of available data and sources even in the presence of high amounts of missing data and offer options for users with missing risk factors.

Abstract Population-based cancer screening programs such as mammography or colonscopy generally directed at all healthy individuals in a given age stratum. It has recently been proposed that cancer screening could be restricted to a high-risk subgroup based on polygenic risk scores (PRSs) using panels of single-nucleotide polymorphisms (SNPs). These PRSs were, however, generated to predict cancer incidence rather than cancer mortality and will not necessarily address overdiagnosis, a major problem associated with cancer screening programs. We develop a simple net-benefit framework for evaluating screening approaches that incorporates overdiagnosis. We use this methodology to demonstrate that if a PRS does not differentially discriminate between incident and lethal cancer, restricting screening to a subgroup with high scores will only improve screening outcomes in a small number of scenarios. In contrast, restricting screening to a subgroup defined as high-risk based on a marker that is more strongly predictive of mortality than incidence will often afford greater net benefit than screening all eligible individuals. If PRS-based cancer screening is to be effective, research needs to focus on identifying PRSs associated with cancer mortality, an unchartered and clinically-relevant area of research, with a much higher potential to improve screening outcomes.

Purpose. To evaluate patient perceptions of a Web-based decision aid for the treatment of localized prostate cancer. Methods. We assessed patient perceptions of a multicomponent, Web-based decision aid with a preference elicitation/values clarification exercise using adaptive conjoint analysis, the generation of a summary report, and provision of information about localized prostate cancer treatment options. Using a think-aloud approach, we conducted 21 cognitive interviews with prostate cancer patients presented with the decision aid prior to seeing their urologist. Thematic content analysis was used to examine patient perceptions of the tool’s components and content prior to engaging in shared decision making with their clinician. Results. Five themes were identified: 1) patients had some negative emotional reactions to the tool, pointing out what they perceived to be unnecessarily negative framing and language used; 2) patients were forced to stop and think about preferences while going through the tool and found this deliberation to be useful; 3) patients were confused by the tool; 4) patients tried to discern the intent of the conjoint analysis questions; and 5) there was a disconnect between patients’ negative reactions while using the tool and a contrasting general satisfaction with the final “values profile” created by the tool. Conclusions. Studies are needed to explore the disconnect between patients’ expressing negative reactions while going through some components of decision aids but satisfaction with the final output. In particular, we hypothesize that this effect might be explained by cognitive biases such as choice-supportive bias, hindsight bias, and the “IKEA effect.” This is one of the first projects to elicit patient reactions while they were completing a decision aid, and we recommend further similar, qualitative postprocess evaluation studies. Highlights We explored perceptions of a decision aid with education about localized prostate cancer treatment and preference elicitation using adaptive conjoint analysis. Patients found the tool useful but were also confused by it, tried to discern the intent of the questions, and expressed negative emotional reactions. In particular, there was a disconnect between patients’ negative reactions while using the tool and general satisfaction with the final values profile generated by the tool, which is an area for future research.

Enterotoxigenic Escherichia coli (ETEC) are common causes of infectious diarrhea among young children of low-and middle-income countries (LMICs) and travelers to these regions. Despite their significant contributions to the morbidity and mortality associated with childhood and traveler’s diarrhea, no licensed vaccines are available. Current vaccine strategies may benefit from the inclusion of additional conserved antigens, which may contribute to broader coverage and enhanced efficacy, given their key roles in facilitating intestinal colonization and effective enterotoxin delivery. EatA and EtpA are widely conserved in diverse populations of ETEC, but their immunogenicity has only been studied in controlled human infection models and a population of children in Bangladesh. Here, we compared serologic responses to EatA, EtpA and heat-labile toxin in populations from endemic regions including Haitian children and subjects residing in Egypt, Cameroon, and Peru to US children and adults where ETEC infections are sporadic. We observed elevated IgG and IgA responses in individuals from endemic regions to each of the antigens studied. In a cohort of Haitian children, we observed increased immune responses following exposure to each of the profiled antigens. These findings reflect the wide distribution of ETEC infections across multiple endemic regions and support further evaluation of EatA and EtpA as candidate ETEC vaccine antigens.

Microbial sulfatases are important biocatalysts in the marine environment where they play a key role in the catabolic biotransformation of abundant sulphated algal polysaccharides. The sulphate esters decorating algal polysaccharides, such as carrageenan, fucoidan and ulvan, can constitute up to 40% of the biopolymer dry weight. The use of this plentiful carbon and energy source by heterotrophic microbes is enabled in part by the sulfatases encoded in their genomes. Sulfatase catalysed hydrolytic removal of sulphate esters is a key reaction at various stages of the enzymatic cascade that depolymerises sulphated polysaccharides into monosaccharides that can enter energy yielding metabolic pathways. As the critical roles of sulfatases in the metabolism of sulphated polysaccharides from marine algae is increasingly revealed, the structural and functional analysis of these enzymes becomes an important component of understanding these metabolic pathways. The S1 family of formylglycine-dependent sulfatases is the largest and most functionally diverse sulfatase family that is frequently active on polysaccharides. Here, we review this important sulfatase family with emphasis on recent developments in studying the structural and functional relationship between sulfatases and their sulphated algal polysaccharide substrates. This analysis utilises the recently proposed active site nomenclature for sulfatases. We will highlight the key role of sulfatases, not only in marine carbon cycling, but also as potential biocatalysts for the production of a variety of novel tailor made sulphated oligomers, which are useful products in, for example, pharmaceutical or cosmetic applications.

Prostate-specific antigen (PSA) density is an established prognostic marker for prostate cancer. We investigated whether the inclusion of PSA density or prostate volume in the Memorial Sloan Kettering Cancer Center nomograms improves the prediction of biochemical recurrence (BCR) after radical prostatectomy (RP). Among the 11 725 men included, 2140 developed BCR. Neither PSA density nor prostate volume was associated with BCR when added to either the pre-RP or post-RP model (all p values ≥0.10) and changes in the C index were very small (largest change, 0.002). The results were robust to exclusion of outlying prostate volumes and restriction to patients treated after 2005. There is no justification for adding prostate volume or PSA density to BCR nomograms. Patient summary: Addition of prostate volume or prostate-specific antigen density to Memorial Sloan Kettering Cancer Center prediction schemes did not improve the prediction of recurrence of prostate cancer after removal of the prostate.

Abstract Background Malnutrition is a problem in advanced cancer, particularly ovarian cancer where malignant bowel obstruction (MBO) is a frequent complication. Parenteral nutrition is the only way these patients can received adequate nutrition and is a principal indication for palliative home parenteral nutrition (HPN). Giving HPN is contentious as it may increase the burden on patients. This study investigates patients’ and family caregivers’ experiences of HPN, alongside nutritional status and survival in patients with ovarian cancer and MBO. Methods This mixed methods study collected data on participant characteristics, clinical details and body composition using computed tomography (CT) combined with longitudinal in-depth interviews underpinned by phenomenological principles. The cohort comprised 38 women with ovarian cancer and inoperable MBO admitted (10/2016 to 12/ 2017) to a tertiary referral hospital. Longitudinal interviews (n = 57) were carried out with 20 women considered for HPN and 13 of their family caregivers. Results Of the 38 women, 32 received parenteral nutrition (PN) in hospital and 17 were discharged on HPN. Nutritional status was poor with 31 of 33 women who had a CT scan having low muscle mass, although 10 were obese. Median overall survival from admission with MBO for all 38 women was 70 days (range 8–506) and for those 17 on HPN was 156 days (range 46–506). Women experienced HPN as one facet of their illness, but viewed it as a “lifeline” that allowed them to live outside hospital. Nevertheless, HPN treatment came with losses including erosion of normality through an impact on activities of daily living and dealing with the bureaucracy surrounding the process. Family caregivers coped but were often left in an emotionally vulnerable state. Conclusions Women and family caregivers reported that the inconvenience and disruption caused by HPN was worth the extended time they had at home.

Abstract Background Online clinical risk prediction tools built on data from multiple cohorts are increasingly being utilized for contemporary doctor-patient decision-making and validation. This report outlines a comprehensive data science strategy for building such tools with application to the Prostate Biopsy Collaborative Group prostate cancer risk prediction tool. Methods We created models for high-grade prostate cancer risk using six established risk factors. The data comprised 8492 prostate biopsies collected from ten institutions, 2 in Europe and 8 across North America. We calculated area under the receiver operating characteristic curve (AUC) for discrimination, the Hosmer-Lemeshow test statistic (HLS) for calibration and the clinical net benefit at risk threshold 15%. We implemented several internal cross-validation schemes to assess the influence of modeling method and individual cohort on validation performance. Results High-grade disease prevalence ranged from 18% in Zurich (1863 biopsies) to 39% in UT Health San Antonio (899 biopsies). Visualization revealed outliers in terms of risk factors, including San Juan VA (51% abnormal digital rectal exam), Durham VA (63% African American), and Zurich (2.8% family history). Exclusion of any cohort did not significantly affect the AUC or HLS, nor did the choice of prediction model (pooled, random-effects, meta-analysis). Excluding the lowest-prevalence Zurich cohort from training sets did not statistically significantly change the validation metrics for any of the individual cohorts, except for Sunnybrook, where the effect on the AUC was minimal. Therefore the final multivariable logistic model was built by pooling the data from all cohorts using logistic regression. Higher prostate-specific antigen and age, abnormal digital rectal exam, African ancestry and a family history of prostate cancer increased risk of high-grade prostate cancer, while a history of a prior negative prostate biopsy decreased risk (all p-values

Abstract Background Decision curve analysis is a method to evaluate prediction models and diagnostic tests that was introduced in a 2006 publication. Decision curves are now commonly reported in the literature, but there remains widespread misunderstanding of and confusion about what they mean. Summary of commentary In this paper, we present a didactic, step-by-step introduction to interpreting a decision curve analysis and answer some common questions about the method. We argue that many of the difficulties with interpreting decision curves can be solved by relabeling the y-axis as “benefit” and the x-axis as “preference.” A model or test can be recommended for clinical use if it has the highest level of benefit across a range of clinically reasonable preferences. Conclusion Decision curves are readily interpretable if readers and authors follow a few simple guidelines.

Magnitude-based inference (MBI) is a controversial statistical method that has been used in hundreds of papers in sports science despite criticism from statisticians. To better understand how this method has been applied in practice, we systematically reviewed 232 papers that used MBI. We extracted data on study design, sample size, and choice of MBI settings and parameters. Median sample size was 10 per group (interquartile range, IQR: 8-15) for multi-group studies and 14 (IQR: 10-24) for single-group studies; few studies reported a priori sample size calculations (15%). Authors predominantly applied MBI's default settings and chose "mechanistic/non-clinical" rather than "clinical" MBI even when testing clinical interventions (only 16 studies out of 232 used clinical MBI). Using these data, we can estimate the Type I error rates for the typical MBI study. Authors frequently made dichotomous claims about effects based on the MBI criterion of a "likely" effect and sometimes based on the MBI criterion of a "possible" effect. When the sample size is n = 8 to 15 per group, these inferences have Type I error rates of 12%-22% and 22%-45%, respectively. High Type I error rates were compounded by multiple testing: Authors reported results from a median of 30 tests related to outcomes; and few studies specified a primary outcome (14%). We conclude that MBI has promoted small studies, promulgated a "black box" approach to statistics, and led to numerous papers where the conclusions are not supported by the data. Amidst debates over the role of p-values and significance testing in science, MBI also provides an important natural experiment: we find no evidence that moving researchers away from p-values or null hypothesis significance testing makes them less prone to dichotomization or over-interpretation of findings.

Abstract Background A variety of statistics have been proposed as tools to help investigators assess the value of diagnostic tests or prediction models. The Brier score has been recommended on the grounds that it is a proper scoring rule that is affected by both discrimination and calibration. However, the Brier score is prevalence dependent in such a way that the rank ordering of tests or models may inappropriately vary by prevalence. Methods We explored four common clinical scenarios: comparison of a highly accurate binary test with a continuous prediction model of moderate predictiveness; comparison of two binary tests where the importance of sensitivity versus specificity is inversely associated with prevalence; comparison of models and tests to default strategies of assuming that all or no patients are positive; and comparison of two models with miscalibration in opposite directions. Results In each case, we found that the Brier score gave an inappropriate rank ordering of the tests and models. Conversely, net benefit, a decision-analytic measure, gave results that always favored the preferable test or model. Conclusions Brier score does not evaluate clinical value of diagnostic tests or prediction models. We advocate, as an alternative, the use of decision-analytic measures such as net benefit. Trial registration Not applicable.

Abstract Background New technologies to collect patient - reported outcomes have substantially solved the challenge of integrating a questionnaire in a busy clinical practice. At Memorial Sloan Kettering, we have been collecting patient reported outcomes electronically for many years. Our experience confirms the predicted benefits of obtaining patient reported outcomes but has also raised serious concerns about whether instruments developed for the research setting are appropriate for routine clinical use. Discussion We summarize four principles for a clinically - relevant psychometrics. First, minimize patient burden: the use of a large number of items for a single domain may be of interest for research but additional items have little clinical utility. Secondly, use simplified language: patients who do not have good language skills are typically excluded from research studies but will nonetheless present in clinical practice. Third, avoid dumb questions: many questionnaire items are inappropriate when applied to a more general population. Fourth, what works for the group may not work for the individual: group level statistics used to validate survey instruments can obscure problems when applied to a subgroup of patients. Conclusion There is a need for a clinically-oriented psychometrics to help design, test, and evaluate questionnaires that would be used in routine practice. Developing statistical methods to optimize questionnaires will be highly challenging but needed to bring the potential of patient reported outcomes into widespread clinical use.

BackgroundEnterotoxigenic Escherichia coli (ETEC) cause significant diarrheal morbidity and mortality in children of resource-limited regions, warranting development of effective vaccine strategies. Genetic diversity of the ETEC pathovar has impeded development of broadly protective vaccines centered on the classical canonical antigens, the colonization factors and heat-labile toxin. Two non-canonical ETEC antigens, the EtpA adhesin, and the EatA mucinase are immunogenic in humans and protective in animal models. To foster rational vaccine design that complements existing strategies, we examined the distribution and molecular conservation of these antigens in a diverse population of ETEC isolates.MethodsGeographically diverse ETEC isolates (n = 1159) were interrogated by PCR, immunoblotting, and/or whole genome sequencing (n = 46) to examine antigen conservation. The most divergent proteins were purified and their core functions assessed in vitro.ResultsEatA and EtpA or their coding sequences were present in 57.0% and 51.5% of the ETEC isolates overall, respectively; and were globally dispersed without significant regional differences in antigen distribution. These antigens also exhibited >93% amino acid sequence identity with even the most divergent proteins retaining the core adhesin and mucinase activity assigned to the prototype molecules.ConclusionsEtpA and EatA are well-conserved molecules in the ETEC pathovar, suggesting that they serve important roles in virulence and that they could be exploited for rational vaccine design.

Abstract Background Network meta-analysis methods, which are an extension of the standard pair-wise synthesis framework, allow for the simultaneous comparison of multiple interventions and consideration of the entire body of evidence in a single statistical model. There are well-established advantages to using individual patient data to perform network meta-analysis and methods for network meta-analysis of individual patient data have already been developed for dichotomous and time-to-event data. This paper describes appropriate methods for the network meta-analysis of individual patient data on continuous outcomes. Methods This paper introduces and describes network meta-analysis of individual patient data models for continuous outcomes using the analysis of covariance framework. Comparisons are made between this approach and change score and final score only approaches, which are frequently used and have been proposed in the methodological literature. A motivating example on the effectiveness of acupuncture for chronic pain is used to demonstrate the methods. Individual patient data on 28 randomised controlled trials were synthesised. Consistency of endpoints across the evidence base was obtained through standardisation and mapping exercises. Results Individual patient data availability avoided the use of non-baseline-adjusted models, allowing instead for analysis of covariance models to be applied and thus improving the precision of treatment effect estimates while adjusting for baseline imbalance. Conclusions The network meta-analysis of individual patient data using the analysis of covariance approach is advocated to be the most appropriate modelling approach for network meta-analysis of continuous outcomes, particularly in the presence of baseline imbalance. Further methods developments are required to address the challenge of analysing aggregate level data in the presence of baseline imbalance.

Ridinilazole, a novel targeted antibacterial being developed for the treatment of C. difficile infection (CDI) and prevention of recurrence, was shown in a recent Phase 2 study to be superior to vancomycin with regard to the primary efficacy measure, sustained clinical response (SCR), with the superiority being driven primarily by marked reductions in the rates of CDI recurrence within 30 days. Tolerability of ridinilazole was comparable to that of vancomycin. The current nested cohort study compared the effects of ridinilazole and vancomycin on fecal microbiota during and after treatment among participants in the Phase 2 study. Changes in the microbiota were assessed using qPCR and high-throughput sequencing on participants' stools collected at multiple time-points (baseline [Day 1], Day 5, end-of-treatment [EOT; Day 10], Day 25, end-of-study [EOS; Day 40], and at CDI recurrence). qPCR analyses showed profound losses of Bacteroides, C. coccoides, C. leptum, and Prevotella groups at EOT with vancomycin treatment, while ridinilazole-treated participants had a modest decrease in C. leptum group levels at EOT, with levels recovering by Day 25. Vancomycin-treated participants had a significant increase in the Enterobacteriaceae group, with this increase persisting beyond EOT. At EOT, alpha diversity decreased with both antibiotics, though to a significantly lesser extent with ridinilazole (p

Behavioral responses to odors rely first upon their accurate detection by peripheral sensory organs followed by subsequent processing within the brain's olfactory system and higher centers. These processes allow the animal to form a unified impression of the odor environment and recognize combinations of odorants as single entities. To investigate how interactions between peripheral and central olfactory pathways shape odor perception, we transplanted antennal imaginal discs between larval males of two species of moth Heliothis virescens and Heliothis subflexa that utilize distinct pheromone blends. During metamorphic development olfactory receptor neurons originating from transplanted discs formed connections with host brain neurons within olfactory glomeruli of the adult antennal lobe. The normal antennal receptor repertoire exhibited by males of each species reflects the differences in the pheromone blends that these species employ. Behavioral assays of adult transplant males revealed high response levels to two odor blends that were dissimilar from those that attract normal males of either species. Neurophysiological analyses of peripheral receptor neurons and central olfactory neurons revealed that these behavioral responses were a result of: 1. the specificity of H. virescens donor olfactory receptor neurons for odorants unique to the donor pheromone blend and, 2. central odor recognition by the H. subflexa host brain, which typically requires peripheral receptor input across 3 distinct odor channels in order to elicit behavioral responses.