Data_Sheet_1_Development and validation of a risk prediction model for incident liver cancer.docx

ObjectiveWe aimed to develop and validate a risk prediction model for liver cancer based on routinely available risk factors using the data from UK Biobank prospective cohort study.MethodsThis analysis included 359,489 participants (2,894,807 person-years) without a previous diagnosis of cancer. We used the Fine-Gray regression model to predict the incident risk of liver cancer, accounting for the competing risk of all-cause death. Model discrimination and calibration were validated internally. Decision curve analysis was conducted to quantify the clinical utility of the model. Nomogram was built based on regression coefficients.ResultsGood discrimination performance of the model was observed in both development and validation datasets, with an area under the curve (95% confidence interval) for 5-year risk of 0.782 (0.748–0.816) and 0.771 (0.702–0.840) respectively. The calibration showed fine agreement between observed and predicted risks. The model yielded higher positive net benefits in the decision curve analysis than considering either all participants as being at high or low risk, which indicated good clinical utility.ConclusionA new risk prediction model for liver cancer composed of routinely available risk factors was developed. The model had good discrimination, calibration and clinical utility, which may help with the screening and management of liver cancer for general population in the public health field.</p

Pre and post operative NCVs of DPN patients (±S).

<p>All variables were expressed in mean ± SD.</p><p>NCV: nerve conduction velocity.</p><p>Nerve decompression increases NCV in operated cases by 15–20%.</p><p>Pre and post operative NCVs of DPN patients (±S).</p

Pre and post operative CSA of DPN patients (±s).

<p>All variables were expressed in mean ± SD.</p><p>CSA: cross-sectional area.</p><p>Pre and post operative CSA of DPN patients (±s).</p

Longitudinal sonograms showing difference of morphological changes after surgical decompression between two patients with focal and diffuse painful DPN.

<p>A and B represent the preoperative (Da: 4.4 mm, Dt: 7.6 mm) and postoperative (Da: 2.9 mm, Dt: 6.3 mm) sonograms of the common peroneal nerve at the level of knee joint of patient with focal painful DPN. C and D represent the preoperative (Da: 4.2 mm, Dt: 7.0 mm) and postoperative (Da: 3.7 mm, Dt: 6.8 mm) sonograms of the common peroneal nerve at the level of knee joint of patient with diffuse painful DPN.</p

Baseline of characteristics of patients.

<p>All variables were expressed in mean ± SD.</p><p>DM = Diabetes Mellitus.</p><p>*a: control group vs. focal & diffuse (surgical group), b: focal group vs. diffuse group.</p><p>Baseline of characteristics of patients.</p

The figure displays the records of VAS levels at different time points.

<p>The VAS scores in both surgical groups showed notable decline with the time course while no changes occurred in control group during the follow-up. The overall postoperative VAS levels of focal pain group were much lower than that of diffuse pain group (<i>P</i><0.01).</p

Baseline characteristics of study participants and comparison between robust, pre-frail and frail women according to the PF classification¹.

<p>¹ Mean follow-up = 3.01 years;</p><p>² One-way analysis of variance (ANOVA) test;</p><p>³ Mantel-Haenszel Chi-square test;</p><p>⁴ Chi-square test;</p><p>PF: phenotypic frailty; SD: standard deviation; BMI: body mass index</p><p>Baseline characteristics of study participants and comparison between robust, pre-frail and frail women according to the PF classification<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0120144#t001fn001" target="_blank">¹</a>.</p

Additional file 1 of Twenty-year trends in racial and ethnic enrollment in large diabetes randomized controlled trials

Additional file 1: Supplemental Figure 1. Flow diagram showing the trial selection process. Supplemental Table 1. Search strategy used in MEDLINE. Supplemental Table 2. Country or region of trial coordination office for the multi-country trials. Supplemental Table 3. Results from univariable logistic regression analysis for the relationship between trial characteristics and high-enrollment of BIPOC groups. Supplemental Table 4. Results from univariable linear regression analysis for the relationship between trial characteristics and enrollment rate of BIPOC groups. Supplemental Table 5. Results from multivariable linear regression analysis for the relationship between trial characteristics and enrollment rate of BIPOC group

Additional file 1 of Relationship between trajectories of dietary iron intake and risk of type 2 diabetes mellitus: evidence from a prospective cohort study

Supplementary Material

Model performance of PLR model for stroke and major bleeding and Cox model for death in KPCO-I and KPCO-II cohorts.

<p>Model performance of PLR model for stroke and major bleeding and Cox model for death in KPCO-I and KPCO-II cohorts.</p