Dataset Information

Prioritising primary care patients with unexpected weight loss for cancer investigation: diagnostic accuracy study.

ABSTRACT: OBJECTIVE:To quantify the predictive value of unexpected weight loss (WL) for cancer according to patient's age, sex, smoking status, and concurrent clinical features (symptoms, signs, and abnormal blood test results). DESIGN:Diagnostic accuracy study. SETTING:Clinical Practice Research Datalink electronic health records data linked to the National Cancer Registration and Analysis Service in primary care, England. PARTICIPANTS:63?973 adults (?18 years) with a code for unexpected WL from 1 January 2000 to 31 December 2012. MAIN OUTCOME MEASURES:Cancer diagnosis in the six months after the earliest weight loss code (index date). Codes for additional clinical features were identified in the three months before to one month after the index date. Diagnostic accuracy measures included positive and negative likelihood ratios, positive predictive values, and diagnostic odds ratios. RESULTS:Of 63?973 adults with unexpected WL, 37?215 (58.2%) were women, 33?167 (51.8%) were aged 60 years or older, and 16?793 (26.3%) were ever smokers. 908 (1.4%) had a diagnosis of cancer within six months of the index date, of whom 882 (97.1%) were aged 50 years or older. The positive predictive value for cancer was above the 3% threshold recommended by the National Institute for Health and Care Excellence for urgent investigation in male ever smokers aged 50 years or older, but not in women at any age. 10 additional clinical features were associated with cancer in men with unexpected WL, and 11 in women. Positive likelihood ratios in men ranged from 1.86 (95% confidence interval 1.32 to 2.62) for non-cardiac chest pain to 6.10 (3.44 to 10.79) for abdominal mass, and in women from 1.62 (1.15 to 2.29) for back pain to 20.9 (10.7 to 40.9) for jaundice. Abnormal blood test results associated with cancer included low albumin levels (4.67, 4.14 to 5.27) and raised values for platelets (4.57, 3.88 to 5.38), calcium (4.28, 3.05 to 6.02), total white cell count (3.76, 3.30 to 4.28), and C reactive protein (3.59, 3.31 to 3.89). However, no normal blood test result in isolation ruled out cancer. Clinical features co-occurring with unexpected WL were associated with multiple cancer sites. CONCLUSION:The risk of cancer in adults with unexpected WL presenting to primary care is 2% or less and does not merit investigation under current UK guidelines. However, in male ever smokers aged 50 years or older and in patients with concurrent clinical features, the risk of cancer warrants referral for invasive investigation. Clinical features typically associated with specific cancer sites are markers of several cancer types when they occur with unexpected WL.

SUBMITTER: Nicholson BD

PROVIDER: S-EPMC7424394 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

RETRACTED: Prioritising primary care patients with unexpected weight loss for cancer investigation: diagnostic accuracy study.

Nicholson Brian D BD Aveyard Paul P Price Sarah J SJ Hobbs Fd Richard FR Koshiaris Constantinos C Hamilton Willie W

BMJ (Clinical research ed.) 20200813

<h4>Objective</h4>To quantify the predictive value of unexpected weight loss (WL) for cancer according to patient's age, sex, smoking status, and concurrent clinical features (symptoms, signs, and abnormal blood test results).<h4>Design</h4>Diagnostic accuracy study.<h4>Setting</h4>Clinical Practice Research Datalink electronic health records data linked to the National Cancer Registration and Analysis Service in primary care, England.<h4>Participants</h4>63 973 adults (≥18 years) with a code fo ...[more]

PMID: 32816714

Similar Datasets

Project description:BackgroundUnexpected weight loss (UWL) is a presenting feature of cancer in primary care. Existing research proposes simple combinations of clinical features (risk factors, symptoms, signs, and blood test data) that, when present, warrant cancer investigation. More complex combinations may modify cancer risk to sufficiently rule-out the need for investigation. We aimed to identify which clinical features can be used together to stratify patients with UWL based on their risk of cancer.Methods and findingsWe used data from 63,973 adults (age: mean 59 years, standard deviation 21 years; 42% male) to predict cancer in patients with UWL recorded in a large representative United Kingdom primary care electronic health record between January 1, 2000 and December 31, 2012. We derived 3 clinical prediction models using logistic regression and backwards stepwise covariate selection: Sm, symptoms-only model; STm, symptoms and tests model; Tm, tests-only model. Fifty imputations replaced missing data. Estimates of discrimination and calibration were derived using 10-fold internal cross-validation. Simple clinical risk scores are presented for models with the greatest clinical utility in decision curve analysis. The STm and Tm showed improved discrimination (area under the curve ≥ 0.91), calibration, and greater clinical utility than the Sm. The Tm was simplest including age-group, sex, albumin, alkaline phosphatase, liver enzymes, C-reactive protein, haemoglobin, platelets, and total white cell count. A Tm score of 5 balanced ruling-in (sensitivity 84.0%, positive likelihood ratio 5.36) and ruling-out (specificity 84.3%, negative likelihood ratio 0.19) further cancer investigation. A Tm score of 1 prioritised ruling-out (sensitivity 97.5%). At this threshold, 35 people presenting with UWL in primary care would be referred for investigation for each person with cancer referred, and 1,730 people would be spared referral for each person with cancer not referred. Study limitations include using a retrospective routinely collected dataset, a reliance on coding to identify UWL, and missing data for some predictors.ConclusionsOur findings suggest that combinations of simple blood test abnormalities could be used to identify patients with UWL who warrant referral for investigation, while people with combinations of normal results could be exempted from referral.

Project description:BackgroundUnexpected weight loss (UWL) in patients consulting in primary care presents dilemmas for management because of the broad differential diagnoses associated with UWL. Research on the risks of serious disease among patients with UWL to date has largely taken place in secondary care, limiting generalizability to primary care patients. In this study, we use a large matched cohort study to estimate the risks of 12 serious diseases among patients presenting to primary care with UWL where this was recorded, stratified by age and sex, in order to inform a rational clinical approach to patients presenting with UWL.MethodsThis was a retrospective matched cohort study using electronic health records (EHRs) from the UK Clinical Practice Research Datalink (CPRD). Each patient with UWL (ascertained from EHR coding) was matched to five patients without UWL and followed until the earliest of a diagnosis of the serious disease, date of death, exit from the CPRD database, or end of the study. Observed absolute risks of the 12 serious diseases were estimated as probabilities, and hazard ratios (HRs) were estimated with Cox proportional hazards models.ResultsBetween 2000 and 2012, 70 193 patients in CPRD had at least one record of UWL and were matched with 295 579 patients without UWL. Patients with UWL had significantly higher risk of nearly all serious diseases examined compared with patients without. HRs ranged from 1.43 for congestive heart failure [95% confidence interval (CI): 1.27-1.62] to 9.70 for malabsorption (95% CI: 6.81-13.82). The absolute risks of any given serious disease were relatively low (<6% after 1 year). The magnitude and rank order of absolute risks varied by age and sex. Depression was the most common diagnosis among women aged <80 with UWL (3.74% of women aged <60 and 2.46% of women aged 60-79), whereas diabetes was the most common in men <60 with UWL (2.96%) and cancer was the most common in men aged 60 and over with UWL (3.79% of men aged 60-70 and 5.28% of men aged ≥80).ConclusionsThis analysis provides new evidence to patients and clinicians about the risks of serious disease among patients presenting with UWL in primary care. Depending on age and sex, the results suggest that workup for UWL should include screening for diabetes, thyroid dysfunction, depression, and dementia. If performed in a timely manner, this workup could be used to triage patients eligible for cancer pathway referral.

Project description:ImportanceAmong individuals with obesity, 5% or greater weight loss can improve health. Weight management treatments (WMT) include nutrition counseling, very low-calorie meal replacement (MR), antiobesity medications (AOM), and bariatric surgery; however, little is known about how these WMT are associated with weight change among individual patients and populations.ObjectiveTo characterize weight status and WMT use among primary care patients and assess associations between WMT and weight trajectories.Design, setting, and participantsRetrospective, population-based cohort study of primary care patients from 1 academic health system in Michigan between October 2015 and March 2020 using cross-sectional analysis to compare obesity prevalence and WMT utilization. For patients with obesity and WMT exposure or matched controls, a multistate Markov model assessing associations between WMT and longitudinal weight status trajectories was used. Data were analyzed from October 2021 to October 2023.ExposuresCross-sectional exposure was year: 2017 or 2019. Trajectory analysis exposures were WMT: nutrition counseling, MR, AOM, and bariatric surgery.Main outcomes and measuresCross-sectional analysis compared mean body mass index (BMI), obesity prevalence, and, among patients with obesity, prospective WMT use. The trajectory analysis examined longitudinal weight status using thresholds of ±5% and 10% of baseline weight with primary outcomes being the 1-year probabilities of 5% or greater weight loss for each WMT.ResultsAdult patients (146 959 participants) consisted of 83 636 female participants (56.9%); 8940 (6.1%) were Asian, 14 560 (9.9%) were Black, and 116 664 (79.4%) were White. Patients had a mean (SD) age of 49.6 (17.7) years and mean (SD) BMI of 29.2 (7.2). Among 138 682 patients, prevalence of obesity increased from 39.2% in 2017 to 40.7% in 2019; WMT use among patients with obesity increased from 5.3% to 7.1% (difference: 1.7%; 95% CI, 1.3%-2.2%). In a multistate model (10 180 patients; 33 549 patient-years), the 1-year probability of 5% or greater weight loss without WMT exposure was 15.6% (95% CI, 14.3%-16.5%) at reference covariates. In contrast, the probability of 5% or greater weight loss was more likely with year-long exposures to any WMT (nutrition counseling: 23.1%; 95% CI, 21.3%-25.1%; MR: 54.6%; 95% CI, 46.5%-61.2%; AOM: 27.8%; 95% CI, 25.0%-30.5%; bariatric surgery: 93.0%; 95% CI, 89.7%-95.0%).Conclusions and relevanceIn this cohort study of primary-care patients with obesity, all WMT increased the patient-level probability of achieving 5% or greater weight loss, but current rates of utilization are low and insufficient to reduce weight at the population level.

Project description:OBJECTIVE:The diagnosis of transient ischaemic attack (TIA) based on symptoms and signs can be challenging and would greatly benefit from a rapid serum biomarker of brain ischaemia. We aimed to quantify the added diagnostic value of serum biomarkers in patients suspected of TIA beyond symptoms and signs. METHODS:This is a cross-sectional diagnostic accuracy study with a 6-month follow-up period. Participants were patients suspected of TIA by the general practitioner (GP) in whom a blood sample could be collected within 72 hours from symptom onset. A research nurse visited the participant for the blood sample and a standardised interview. The GP referred participants to the regional TIA service. An expert panel of three neurologists classified cases as TIA, minor stroke or any other diagnosis, based on all available diagnostic information including the GP's and neurologist's correspondence and the follow-up period. We used multivariable logistic regression analyses to quantify the diagnostic accuracy of clinical predictors and the improvement of accuracy by seven biomarkers (NR2, NR2 antibodies, PARK7, NDKA, UFD1, B-FABP and H-FABP). RESULTS:206 patients suspected of TIA participated, of whom 126 (61.2%) were diagnosed with TIA (n=104) or minor stroke (n=22) by the expert panel. The median time from symptom onset to the blood sample collection was 48.0 (IQR 28.3-56.8) hours. None of the seven biomarkers had discriminative value in the diagnosis of TIA, with C-statistics ranging from 0.45 to 0.58. The final multivariable model (C-statistic 0.83 (0.78-0.89)) consisted of eight clinical predictors of TIA/minor stroke: increasing age, a history of coronary artery disease, sudden onset of symptoms, occurrence of symptoms in full intensity, dysarthria, no history of migraine, absence of loss of consciousness and absence of headache. Addition of the individual biomarkers did not further increase the C-statistics. CONCLUSIONS:Currently available blood biomarkers have no added diagnostic value in suspected TIA. TRIAL REGISTRATION NUMBER:NCT01954329.

Project description:BackgroundThe US Preventive Services Task Force recommends screening for and treating obesity. However, there are many barriers to successfully treating obesity in primary care (PC). Technology-assisted weight loss interventions offer novel ways of improving treatment, but trials are overwhelmingly conducted outside of PC and may not translate well into this setting. We conducted a systematic review of technology-assisted weight loss interventions specifically tested in PC settings.MethodsWe searched the literature from January 2000 to March 2014.Inclusion criteria(1) Randomized controlled trial; (2) trials that utilized the Internet, personal computer, and/or mobile device; and (3) occurred in an ambulatory PC setting. We applied the Cochrane Effective Practice and Organization of Care (EPOC) and Delphi criteria to assess bias and the Pragmatic-Explanatory Continuum Indicator Summary (PRECIS) criteria to assess pragmatism (whether trials occurred in the real world versus under ideal circumstances). Given heterogeneity, results were not pooled quantitatively.ResultsSixteen trials met inclusion criteria. Twelve (75 %) interventions achieved weight loss (range: 0.08 kg - 5.4 kg) compared to controls, while 5-45 % of patients lost at least 5 % of baseline weight. Trial duration and attrition ranged from 3-36 months and 6-80 %, respectively. Ten (63 %) studies reported results after at least 1 year of follow-up. Interventions used various forms of personnel, technology modalities, and behavior change elements; trials most frequently utilized medical doctors (MDs) (44 %), web-based applications (63 %), and self-monitoring (81 %), respectively. Interventions that included clinician-guiding software or feedback from personnel appeared to promote more weight loss than fully automated interventions. Only two (13 %) studies used publically available technologies. Many studies had fair pragmatism scores (mean: 2.8/4), despite occurring in primary care.DiscussionCompared to usual care, technology-assisted interventions in the PC setting help patients achieve weight loss, offering evidence-based options to PC providers. However, best practices remain undetermined. Despite occurring in PC, studies often fall short in utilizing pragmatic methodology and rarely provide publically available technology. Longitudinal, pragmatic, interdisciplinary, and open-source interventions are needed.

Dataset Information

Prioritising primary care patients with unexpected weight loss for cancer investigation: diagnostic accuracy study.

Publications

RETRACTED: Prioritising primary care patients with unexpected weight loss for cancer investigation: diagnostic accuracy study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets