Characterisation, identification, clustering, and classification of disease.

The importance of quantifying the distribution and determinants of multimorbidity has prompted novel data-driven classifications of disease. Applications have included improved statistical power and refined prognoses for a range of respiratory, infectious, autoimmune, and neurological diseases, with studies using molecular information, age of disease incidence, and sequences of disease onset ("disease trajectories") to classify disease clusters. Here we consider whether easily measured risk factors such as height and BMI can effectively characterise diseases in UK Biobank data, combining established statistical methods in new but rigorous ways to provide clinically relevant comparisons and clusters of disease. Over 400 common diseases were selected for analysis using clinical and epidemiological criteria, and conventional proportional hazards models were used to estimate associations with 12 established risk factors. Several diseases had strongly sex-dependent associations of disease risk with BMI. Importantly, a large proportion of diseases affecting both sexes could be identified by their risk factors, and equivalent diseases tended to cluster adjacently. These included 10 diseases presently classified as "Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified". Many clusters are associated with a shared, known pathogenesis, others suggest likely but presently unconfirmed causes. The specificity of associations and shared pathogenesis of many clustered diseases provide a new perspective on the interactions between biological pathways, risk factors, and patterns of disease such as multimorbidity.

Merkel cell carcinoma with divergent differentiation.

Merkel cell carcinoma (MCC) is a rare primary neuroendocrine carcinoma of the skin, usually occurring at sun-exposed sites in elderly people. Divergent differentiation in MCC, although rare, has been reported in previous case series. We describe two new cases of MCC with divergent differentiation. Patient 1 was a 96-year-old man with a scalp lesion; on biopsy, the morphology and immunoprofile suggested MCC with divergent squamous differentiation. Patient 2 was an 87-year-old woman with a lesion on her leg, originally reported as squamous cell carcinoma, later showing extensive local recurrence. On review, primary histology showed an MCC with divergent differentiation, most likely trichilemmal carcinoma; the recurrence showed only MCC. These cases illustrate that MCC is capable of divergent differentiation, including squamous and adnexal morphologies. Correct diagnosis is essential for appropriate prognosis and management, as later recurrence or metastases may only show the Merkel cell component.

Serous tubal intraepithelial carcinomas associated with high-grade serous ovarian carcinomas: a systematic review.

BACKGROUND: Serous tubal intraepithelial carcinomas (STICs) have been documented in high-grade serous ovarian carcinomas (HGSOCs). However, the rate of association between STICs and HGSOCs and, therefore, the fraction of HGSOCs that are likely to have originated from the fallopian tube (FT), has remained unclear. OBJECTIVE: To appraise the literature describing the association between STICs and established HGSOCs. SEARCH STRATEGY: Ovid MEDLINE and EMBASE were searched. SELECTION CRITERIA: Studies were included if they evaluated the frequency of STICs in HGSOCs, and were published in an English peer-reviewed journal. DATA COLLECTION AND ANALYSIS: Appropriate studies were evaluated for their compliance with the 'Strengthening and Reporting of Observational Studies in Epidemiology (STROBE)' criteria. MAIN RESULTS: Ten articles met the study selection criteria. The reported coexistence between STICs and HGSOCs ranged from 11% to 61% (mean: 31%, 95% CI: 17-46%). STICs were rarely found in other gynaecological cancers. Small sample size, lack of objective criteria to identify STICs and the retrospective nature of the studies contributed to the variability in reporting the rate of the association. CONCLUSIONS: STICs were identified commonly in the FTs of women with HGSOC. Finding the true rate of association between STICs and HGSOCs will require further investigations. While there is evidence that a fraction of HGSOCs arise from the FTs, an accurate estimate of that fraction remains to be determined. The lack of an accurate estimate of the association makes it difficult to evaluate the potential magnitude of reduction of HGSOCs following prophylactic salpingectomy. TWEETABLE ABSTRACT: A systematic review of the incidence of STICs in HGSOCs identifies significant methodological inconsistencies.

Menopausal hormone use and ovarian cancer risk: individual participant meta-analysis of 52 epidemiological studies.

BACKGROUND: Half the epidemiological studies with information about menopausal hormone therapy and ovarian cancer risk remain unpublished, and some retrospective studies could have been biased by selective participation or recall. We aimed to assess with minimal bias the effects of hormone therapy on ovarian cancer risk. METHODS: Individual participant datasets from 52 epidemiological studies were analysed centrally. The principal analyses involved the prospective studies (with last hormone therapy use extrapolated forwards for up to 4 years). Sensitivity analyses included the retrospective studies. Adjusted Poisson regressions yielded relative risks (RRs) versus never-use. FINDINGS: During prospective follow-up, 12 110 postmenopausal women, 55% (6601) of whom had used hormone therapy, developed ovarian cancer. Among women last recorded as current users, risk was increased even with <5 years of use (RR 1·43, 95% CI 1·31-1·56; p<0·0001). Combining current-or-recent use (any duration, but stopped <5 years before diagnosis) resulted in an RR of 1·37 (95% CI 1·29-1·46; p<0·0001); this risk was similar in European and American prospective studies and for oestrogen-only and oestrogen-progestagen preparations, but differed across the four main tumour types (heterogeneity p<0·0001), being definitely increased only for the two most common types, serous (RR 1·53, 95% CI 1·40-1·66; p<0·0001) and endometrioid (1·42, 1·20-1·67; p<0·0001). Risk declined the longer ago use had ceased, although about 10 years after stopping long-duration hormone therapy use there was still an excess of serous or endometrioid tumours (RR 1·25, 95% CI 1·07-1·46, p=0·005). INTERPRETATION: The increased risk may well be largely or wholly causal; if it is, women who use hormone therapy for 5 years from around age 50 years have about one extra ovarian cancer per 1000 users and, if its prognosis is typical, about one extra ovarian cancer death per 1700 users. FUNDING: Medical Research Council, Cancer Research UK.

Ovarian cancer and smoking: individual participant meta-analysis including 28,114 women with ovarian cancer from 51 epidemiological studies.

BACKGROUND: Smoking has been linked to mucinous ovarian cancer, but its effects on other ovarian cancer subtypes and on overall ovarian cancer risk are unclear, and the findings from most studies with relevant data are unpublished. To assess these associations, we review the published and unpublished evidence. METHODS: Eligible epidemiological studies were identified by electronic searches, review articles, and discussions with colleagues. Individual participant data for 28,114 women with and 94,942 without ovarian cancer from 51 epidemiological studies were analysed centrally, yielding adjusted relative risks (RRs) of ovarian cancer in smokers compared with never smokers. FINDINGS: After exclusion of studies with hospital controls, in which smoking could have affected recruitment, overall ovarian cancer incidence was only slightly increased in current smokers compared with women who had never smoked (RR 1·06, 95% CI 1·01-1·11, p=0·01). Of 17,641 epithelial cancers with specified histology, 2314 (13%) were mucinous, 2360 (13%) endometrioid, 969 (5%) clear-cell, and 9086 (52%) serous. Smoking-related risks varied substantially across these subtypes (p(heterogeneity)<0·0001). For mucinous cancers, incidence was increased in current versus never smokers (1·79, 95% CI 1·60-2·00, p<0·0001), but the increase was mainly in borderline malignant rather than in fully malignant tumours (2·25, 95% CI 1·91-2·65 vs 1·49, 1·28-1·73; p(heterogeneity)=0·01; almost half the mucinous tumours were only borderline malignant). Both endometrioid (0·81, 95% CI 0·72-0·92, p=0·001) and clear-cell ovarian cancer risks (0·80, 95% CI 0·65-0·97, p=0·03) were reduced in current smokers, and there was no significant association for serous ovarian cancers (0·99, 95% CI 0·93-1·06, p=0·8). These associations did not vary significantly by 13 sociodemographic and personal characteristics of women including their body-mass index, parity, and use of alcohol, oral contraceptives, and menopausal hormone therapy. INTERPRETATION: The excess of mucinous ovarian cancers in smokers, which is mainly of tumours of borderline malignancy, is roughly counterbalanced by the deficit of endometrioid and clear-cell ovarian cancers. The substantial variation in smoking-related risks by tumour subtype is important for understanding ovarian carcinogenesis. FUNDING: Cancer Research UK and MRC.

Establishing an evidence base for frequency of monitoring glycated haemoglobin levels in patients with Type 2 diabetes: projections of effectiveness from a regression model.

AIMS: Glycated haemoglobin (HbA1c) is monitored to guide treatment decisions in relation to glycaemic goals over time. Changes between two consecutive HbA1c tests result not only from deterioration or improvement in glycaemic control, but also from biovariability and measurement error. We model how this short-term variability impacts on HbA1c monitoring. METHODS: Using data from a randomized trial of non-insulin treated patients with Type 2 diabetes we fitted a random-effects model for progression and variability of HbA1c. We estimated how many tests where HbA1c ≥ 7.5% (58.5 mmol/mol) would be false-positive (underlying HbA1c < 7.5% but test ≥ 7.5% owing to variability) vs. true-positive, in people with initial HbA1c between 6.5% and 7.3% (48 mmol/mol and 56 mmol/mol). RESULTS: Participants (n = 320) had mean (SD) age 66 (10) years, BMI 31.3 (6.0) kg/m2 and median HbA1c was 7.1% (54 mmol/mol) with interquartile range 6.6% (49 mmol/mol) to 7.7% (61 mmol/mol). Mean (95% CI) change in HbA1c was 0.1% (1 mmol/mol) with 95% confidence interval 0.05% (0.5 mmol/mol) to 0.15% (2 mmol/mol) per 6 months. The minimum interval at which a true-positive test is more likely than a false positive test is 270 days for a starting HbA1c of 6.9% (52 mmol/mol) and 360 days at a starting value of 6.5% (48 mmol/mol). CONCLUSION: In patients with initial HbA1c close to treatment goal, retesting at 6 months would yield more true-positive than false-positive tests. For patients with lower initial HbA1c, retesting at 6 months would yield more false than true-positive tests. In all patients, retesting at 12 months yields more true than false-positive tests. In very few patients would retesting at 3 months be justified.