Multivariate prediction of diabetes according to CDP and biomarker risk score.

<p>WC, waist circumference; FG, fasting glucose; HT, hypertension; TNF-α R2: tumor neurosis factor-alpha receptor 2.</p

Comparisons of AUCs of different diabetes prediction models.

<p>AUC, Area under the curve; All biomarker levels were sex-specific except for hsCRP;</p><p>CDP: Sex, Age, Waist circumference, fasting glucose, hypertension, dyslipidaemia, family history of diabetes, physical activity and smoking status.</p><p>TNF-α R2: tumor neurosis factor-alpha receptor 2; hsCRP, high sensitivity C-reactive protein; IL-6, Interleukin-6; A-FABP, adipocyte-fatty acid-binding protein.</p

Log-likelihood ratio tests comparing the change before and after addition of biomarkers.

<p>-2LL, -2log-likelihood; p-value (χ², df = 1);</p><p>All biomarker levels were sex specific (except for hsCRP).</p><p>CDP: Sex, Age, Waist circumference, fasting glucose, hypertension, dyslipidaemia, family history of diabetes, physical activity and smoking status.</p><p>TNF-α R2: tumor neurosis factor-alpha receptor 2; hsCRP, high sensitivity C-reactive protein; IL-6, Interleukin-6; A-FABP, adipocyte-fatty acid-binding protein.</p

Baseline clinical and biochemical characteristics of subjects with and without incident type 2 DM in 5.3 years.

<p>Mean ± SD, median (interquartile-range), or percentage as appropriate.</p>a<p>Physical activity: active if having moderate intensity exercise for at least 30 minutes in one month. ^bSex-adjusted; ^cAdjusted for hypertensive treatment; ^dLog transformed before analysis. ^eExcluded subjects on lipid treatment;</p><p>Central obesity: waist circumference ≥90 cm (M)/80 cm (F).</p><p>Hypertension: systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or on hypertensive treatment.</p><p>Dyslipidaemia: triglycerides ≥1.7 mmol/L, HDL cholesterol <1.0 mmol/L (M)/1.3 mmol/L (F), LDL cholesterol ≥3.4 mmol/L, or on lipid treatment.</p

Association of baseline factors with incident fracture.

<p>Association of baseline factors with incident fracture.</p

Association of different types of androgen deprivation therapy with bone health.

<p>Association of different types of androgen deprivation therapy with bone health.</p

Baseline characteristics of patients.

<p>Baseline characteristics of patients.</p

Kaplan Meier analysis of fracture-free survival among patients prescribed various types of ADT.

<p>Kaplan Meier analysis of fracture-free survival among patients prescribed various types of ADT.</p

DataSheet_1_A clinicopathological study of non-functioning pituitary neuroendocrine tumours using the World Health Organization 2022 classification.docx

BackgroundThe 2022 World Health Organization (WHO) classification of pituitary neuroendocrine tumour (PitNET) supersedes the previous one in 2017 and further consolidates the role of transcription factors (TF) in the diagnosis of PitNET. Here, we investigated the clinical utility of the 2022 WHO classification, as compared to that of 2017, in a cohort of patients with non-functioning PitNET (NF-PitNET).MethodsA total of 113 NF-PitNET patients who underwent resection between 2010 and 2021, and had follow-up at Queen Mary Hospital, Hong Kong, were recruited. Surgical specimens were re-stained for the three TF: steroidogenic factor (SF-1), T-box family member TBX19 (TPIT) and POU class 1 homeobox 1 (Pit-1). The associations of different NF-PitNET subtypes with tumour-related outcomes were evaluated by logistic and Cox regression analyses.ResultsBased on the 2022 WHO classification, the majority of NF-PitNET was SF-1-lineage tumours (58.4%), followed by TPIT-lineage tumours (18.6%), tumours with no distinct lineage (16.8%) and Pit-1-lineage tumours (6.2%). Despite fewer entities than the 2017 classification, significant differences in disease-free survival were present amongst these four subtypes (Log-rank test p=0.003), specifically between SF-1-lineage PitNET and PitNET without distinct lineage (Log-rank test pConclusionThe 2022 WHO classification of PitNET is a clinically useful TF and lineage-based system for subtyping NF-PitNET with different tumour behaviour and prognosis.</p