Poor handling of continuous predictors in clinical prediction models using logistic regression: a systematic review

Background and Objectives When developing a clinical prediction model, assuming a linear relationship between the continuous predictors and outcome is not recommended. Incorrect specification of the functional form of continuous predictors could reduce predictive accuracy. We examine how continuous predictors are handled in studies developing a clinical prediction model. Methods We searched PubMed for clinical prediction model studies developing a logistic regression model for a binary outcome, published between July 01, 2020, and July 30, 2020. Results In total, 118 studies were included in the review (18 studies (15%) assessed the linearity assumption or used methods to handle nonlinearity, and 100 studies (85%) did not). Transformation and splines were commonly used to handle nonlinearity, used in 7 (n = 7/18, 39%) and 6 (n = 6/18, 33%) studies, respectively. Categorization was most often used method to handle continuous predictors (n = 67/118, 56.8%) where most studies used dichotomization (n = 40/67, 60%). Only ten models included nonlinear terms in the final model (n = 10/18, 56%). Conclusion Though widely recommended not to categorize continuous predictors or assume a linear relationship between outcome and continuous predictors, most studies categorize continuous predictors, few studies assess the linearity assumption, and even fewer use methodology to account for nonlinearity. Methodological guidance is provided to guide researchers on how to handle continuous predictors when developing a clinical prediction model

Poor handling of continuous predictors in clinical prediction models using logistic regression:a systematic review

Background and Objectives When developing a clinical prediction model, assuming a linear relationship between the continuous predictors and outcome is not recommended. Incorrect specification of the functional form of continuous predictors could reduce predictive accuracy. We examine how continuous predictors are handled in studies developing a clinical prediction model. Methods We searched PubMed for clinical prediction model studies developing a logistic regression model for a binary outcome, published between July 01, 2020, and July 30, 2020. Results In total, 118 studies were included in the review (18 studies (15%) assessed the linearity assumption or used methods to handle nonlinearity, and 100 studies (85%) did not). Transformation and splines were commonly used to handle nonlinearity, used in 7 (n = 7/18, 39%) and 6 (n = 6/18, 33%) studies, respectively. Categorization was most often used method to handle continuous predictors (n = 67/118, 56.8%) where most studies used dichotomization (n = 40/67, 60%). Only ten models included nonlinear terms in the final model (n = 10/18, 56%). Conclusion Though widely recommended not to categorize continuous predictors or assume a linear relationship between outcome and continuous predictors, most studies categorize continuous predictors, few studies assess the linearity assumption, and even fewer use methodology to account for nonlinearity. Methodological guidance is provided to guide researchers on how to handle continuous predictors when developing a clinical prediction model

Sample size requirements are not being considered in studies developing prediction models for binary outcomes: a systematic review

Background Having an appropriate sample size is important when developing a clinical prediction model. We aimed to review how sample size is considered in studies developing a prediction model for a binary outcome. Methods We searched PubMed for studies published between 01/07/2020 and 30/07/2020 and reviewed the sample size calculations used to develop the prediction models. Using the available information, we calculated the minimum sample size that would be needed to estimate overall risk and minimise overfitting in each study and summarised the difference between the calculated and used sample size. Results A total of 119 studies were included, of which nine studies provided sample size justification (8%). The recommended minimum sample size could be calculated for 94 studies: 73% (95% CI: 63–82%) used sample sizes lower than required to estimate overall risk and minimise overfitting including 26% studies that used sample sizes lower than required to estimate overall risk only. A similar number of studies did not meet the ≥ 10EPV criteria (75%, 95% CI: 66–84%). The median deficit of the number of events used to develop a model was 75 [IQR: 234 lower to 7 higher]) which reduced to 63 if the total available data (before any data splitting) was used [IQR:225 lower to 7 higher]. Studies that met the minimum required sample size had a median c-statistic of 0.84 (IQR:0.80 to 0.9) and studies where the minimum sample size was not met had a median c-statistic of 0.83 (IQR: 0.75 to 0.9). Studies that met the ≥ 10 EPP criteria had a median c-statistic of 0.80 (IQR: 0.73 to 0.84). Conclusions Prediction models are often developed with no sample size calculation, as a consequence many are too small to precisely estimate the overall risk. We encourage researchers to justify, perform and report sample size calculations when developing a prediction model

Transport of Artificial Virus-like Nanocarriers (AVN) through intestinal monolayer via Microfold cells

Compared with subcutaneous or intramuscular routes for vaccination, vaccine delivery via gastrointestinal mucosa has tremendous potential as it is easy to administer and pain free. Robust immune responses can be triggered successfully once vaccine carried antigen reaches the mucosal associated lymphoid sites (e.g., Peyer’s patches). However, the absence of an efficient delivery method has always been an issue for successful oral vaccine development. In our study, inspired by mammalian orthoreovirus (MRV) transport into gut mucosal lymphoid tissue via Microfold cells (M cells), artificial virus-like nanocarriers (AVN), consisting of gold nanocages functionalized with the 1 protein from mammalian reovirus (MRV), were tested as an effective oral vaccine delivery vehicle targeting M cells. AVN was shown to have a significantly higher transport compared to other experimental groups across mouse organoid monolayers containing M cells. These findings suggest that AVN has the potential to be an M cell-specific oral vaccine/drug delivery vehicle

Symptom burden and unmet needs in MPM:exploratory analyses from the RESPECT-Meso study

© The Author(s) 2020. Objective: Malignant Pleural Mesothelioma (MPM) has a poor prognosis and high symptom burden. RESPECT-Meso was a multicenter randomized study examining the role of early specialist palliative care (SPC) on quality of life (QoL) with MPM. This is a post-hoc exploratory analysis of the symptom burden and unmet needs identified from RESPECT-Meso participants. Methods: Exploratory analysis from 174 participants using the General Health Status (GHS) measure (from the EORTC QLQ-C30 QoL questionnaire) and 87 participants using validated assessment questionnaires in those randomized to SPC. Eligibility for the study included confirmed MPM with diagnosis \u3c 6 weeks prior, performance score (PS) 0 or 1, no significant physical or psychological comorbidity. Cox proportional hazards models were derived to examine for relationships with survival. Free text was assessed using content analysis, looking for common themes and words. Results: Participants were predominantly male (79.9%), mean age 72.8 years, PS was 0 in 38%, 78% of MPM was epithelioid. At least 3 symptoms were reported in 69.8% of participants, including fatigue (81%), dyspnea (73.3%), pain (61.2%), weight loss (59.3%). Anxiety was reported by 54.7% of participants, 52.3% low mood and 48.8% anhedonia symptoms. After multivariable adjustment, only pain remained statistically significant with a hazard ratio (HR) 2.9 (95% CI 1.3-6.7; p = 0.01). For each 1 unit increase in GHS score, the HR for death was 0.987 (0.978-0.996; p = 0.006), indicating a worse reported QoL is related to shorter survival. Unmet needs were common: 25.9% wanted more information about their condition, 24.7% about their care and 21.2% about their treatment. 79.1% were concerned about the effect of their illness on family. Conclusion: There is a high symptom burden in mesothelioma despite good baseline performance status. A worse QoL is associated with a worse survival. Unmet needs are common, perhaps highlighting a need for improved communication and information sharing

Impact of COVID-19 pandemic on incidence of long-term conditions in Wales: a population data linkage study

Background The COVID-19 pandemic has directly and indirectly had an impact on health service provision owing to surges and sustained pressures on the system. The effects of these pressures on the management of long-term or chronic conditions are not fully understood. Aim To explore the effects of COVID-19 on the recorded incidence of 17 long-term conditions. Design and setting This was an observational retrospective population data linkage study on the population of Wales using primary and secondary care data within the Secure Anonymised Information Linkage (SAIL) Databank. Method Monthly rates of new diagnosis between 2000 and 2021 are presented for each long-term condition. Incidence rates post-2020 were compared with expected rates predicted using time series modelling of pre-2020 trends. The proportion of annual incidence is presented by sociodemographic factors: age, sex, social deprivation, ethnicity, frailty, and learning disability. Results A total of 5 476 012 diagnoses from 2 257 992 individuals are included. Incidence rates from 2020 to 2021 were lower than mean expected rates across all conditions. The largest relative deficit in incidence was in chronic obstructive pulmonary disease corresponding to 343 (95% confidence interval = 230 to 456) undiagnosed patients per 100 000 population, followed by depression, type 2 diabetes, hypertension, anxiety disorders, and asthma. A GP practice of 10 000 patients might have over 400 undiagnosed long-term conditions. No notable differences between sociodemographic profiles of post- and pre-2020 incidences were observed. Conclusion There is a potential backlog of undiagnosed patients with multiple long-term conditions. Resources are required to tackle anticipated workload as part of COVID-19 recovery, particularly in primary care

Poor handling of continuous predictors in clinical prediction models using logistic regression: a systematic review

Background and Objectives: When developing a clinical prediction model, assuming a linear relationship between the continuous predictors and outcome is not recommended. Incorrect specification of the functional form of continuous predictors could reduce predictive accuracy. We examine how continuous predictors are handled in studies developing a clinical prediction model. Methods: We searched PubMed for clinical prediction model studies developing a logistic regression model for a binary outcome, published between July 01, 2020, and July 30, 2020. Results: In total, 118 studies were included in the review (18 studies (15%) assessed the linearity assumption or used methods to handle nonlinearity, and 100 studies (85%) did not). Transformation and splines were commonly used to handle nonlinearity, used in 7 (n = 7/18, 39%) and 6 (n = 6/18, 33%) studies, respectively. Categorization was most often used method to handle continuous predictors (n = 67/118, 56.8%) where most studies used dichotomization (n = 40/67, 60%). Only ten models included nonlinear terms in the final model (n = 10/18, 56%). Conclusion: Though widely recommended not to categorize continuous predictors or assume a linear relationship between outcome and continuous predictors, most studies categorize continuous predictors, few studies assess the linearity assumption, and even fewer use methodology to account for nonlinearity. Methodological guidance is provided to guide researchers on how to handle continuous predictors when developing a clinical prediction model

A Genome-Wide association Study Discovers 46 Loci of the Human Metabolome in the Hispanic Community Health Study/Study of Latinos

Variation in levels of the human metabolome reflect changes in homeostasis, providing a window into health and disease. The genetic impact on circulating metabolites in Hispanics, a population with high cardiometabolic disease burden, is largely unknown. We conducted genome-wide association analyses on 640 circulating metabolites in 3,926 Hispanic Community Health Study/Study of Latinos participants. The estimated heritability for 640 metabolites ranged between 0%-54% with a median at 2.5%. We discovered 46 variant-metabolite pairs (p value \u3c 1.2 × 1

A phase I open-label, dose-escalation study of NUC-3373, a targeted thymidylate synthase inhibitor, in patients with advanced cancer (NuTide:301)

The study was funded and the investigational drug NUC-3373 was supplied by NuCana plc. The centres that conducted this study are National Institute for Health and Care Research (NIHR) Biomedical Research Centres that also receive institutional funding as Cancer Research UK (CRUK) and Experimental Cancer Medicine Centres (ECMC). The Glasgow Experimental Cancer Medicine Centre (ECMC) is funded by Cancer Research UK and The Chief Scientist’s Office, Scotland (grant award A25174).Purpose 5-fluorouracil (5-FU) is inefficiently converted to the active anti-cancer metabolite, fluorodeoxyuridine-monophosphate (FUDR-MP), is associated with dose-limiting toxicities and challenging administration schedules. NUC-3373 is a phosphoramidate nucleotide analog of fluorodeoxyuridine (FUDR) designed to overcome these limitations and replace fluoropyrimidines such as 5-FU. Patients and methods NUC-3373 was administered as monotherapy to patients with advanced solid tumors refractory to standard therapy via intravenous infusion either on Days 1, 8, 15 and 22 (Part 1) or on Days 1 and 15 (Part 2) of 28-day cycles until disease progression or unacceptable toxicity. Primary objectives were maximum tolerated dose (MTD) and recommended Phase II dose (RP2D) and schedule of NUC-3373. Secondary objectives included pharmacokinetics (PK), and anti-tumor activity. Results Fifty-nine patients received weekly NUC-3373 in 9 cohorts in Part 1 (n = 43) and 3 alternate-weekly dosing cohorts in Part 2 (n = 16). They had received a median of 3 prior lines of treatment (range: 0–11) and 74% were exposed to prior fluoropyrimidines. Four experienced dose-limiting toxicities: two Grade (G) 3 transaminitis; one G2 headache; and one G3 transient hypotension. Commonest treatment-related G3 adverse event of raised transaminases occurred in < 10% of patients. NUC-3373 showed a favorable PK profile, with dose-proportionality and a prolonged half-life compared to 5-FU. A best overall response of stable disease was observed, with prolonged progression-free survival. Conclusion NUC-3373 was well-tolerated in a heavily pre-treated solid tumor patient population, including those who had relapsed on prior 5-FU. The MTD and RP2D was defined as 2500 mg/m2 NUC-3373 weekly. NUC-3373 is currently in combination treatment studies. Trial registration Clinicaltrials.gov registry number NCT02723240. Trial registered on 8th December 2015. https://clinicaltrials.gov/study/NCT02723240.Peer reviewe