The association between unexpected weight loss and cancer diagnosis in primary care: a matched cohort analysis of 65,000 presentations.
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ABSTRACT: Background
We aimed to understand the time period of cancer diagnosis and the cancer types detected in primary care patients with unexpected weight loss (UWL) to inform cancer guidelines.Methods
This retrospective matched cohort study used cancer registry linked electronic health records from the UK's Clinical Practice Research Datalink from between 2000 and 2014. Univariable and multivariable time-to-event analyses examined the association between UWL, and all cancers combined, cancer site and stage.Results
In all, 63,973 patients had UWL recorded, of whom 1375 (2.2%) were diagnosed with cancer within 2 years (days-to-diagnosis: mean 181; median 80). Men with UWL (HR 3.28 (2.88-3.73)) and women (1.87 (1.68-2.08)) were more likely than comparators to be diagnosed with cancer within 3 months. The association was greatest in men aged ≥50 years and women ≥70 years. The commonest cancers were pancreas, cancer of unknown primary, gastro-oesophageal, lymphoma, hepatobiliary, lung, bowel and renal-tract. The majority were late-stage, but there was some evidence of association with stage II and stage III cancers. In the 3-24 months after presenting with UWL, cancer diagnosis was less likely than in comparators.Conclusion
UWL recorded in primary care is associated with a broad range of cancer sites of early and late-stage.
SUBMITTER: Nicholson BD
PROVIDER: S-EPMC7283307 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo 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).DesignDiagnostic accuracy study.SettingClinical Practice Research Datalink electronic health records data linked to the National Cancer Registration and Analysis Service in primary care, England.Participants63 973 adults (≥18 years) with a code for unexpected WL from 1 January 2000 to 31 December 2012.Main outcome measuresCancer 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.ResultsOf 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.ConclusionThe 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.
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Project description:BackgroundDiagnosis of Parkinson's disease (PD) is typically preceded by nonspecific presentations in primary care.ObjectivesThe objective of this study was to develop and validate a prediction model for diagnosis of PD based on presentations in primary care.SettingThe settings were general practices providing data for The Health Improvement Network UK primary care database.MethodsData from 8,166 patients aged older than age 50 years with incident diagnosis of PD and 46,755 controls were analyzed. Likelihood ratios, sensitivity, specificity, and positive and negative predictive values for individual symptoms and combinations of presentations were calculated. An algorithm for risk of diagnosis of PD within 5 years was calculated using multivariate logistic regression analysis. Split sample analysis was used for model validation with a 70% development sample and a 30% validation sample.ResultsPresentations independently and significantly associated with later diagnosis of PD in multivariate analysis were tremor, constipation, depression or anxiety, fatigue, dizziness, urinary dysfunction, balance problems, memory problems and cognitive decline, hypotension, rigidity, and hypersalivation. The discrimination and calibration of the risk algorithm were good with an area under the curve of 0.80 (95% confidence interval 0.78-0.81). At a threshold of 5%, 37% of those classified as high risk would be diagnosed with PD within 5 years and 99% of those who were not classified as high risk would not be diagnosed with PD.ConclusionThis risk algorithm applied to routine primary care presentations can identify individuals at increased risk of diagnosis of PD within 5 years to allow for monitoring and earlier diagnosis of PD. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Project description:Early-onset dementia (EOD) affects the employment of patients and family members. To demonstrate how likely employees are to leave their jobs after an EOD diagnosis for themselves or a family member, we conducted a matched cohort study of 143 employees and 77 family members diagnosed with EOD using a claims database. We matched these participants to 5 controls each, and followed them for approximately 600 days. In the employee cohort, patients with EOD were more likely to leave their jobs than were controls (hazard ratio: 2.26). This suggests that healthcare providers should offer employment support to patients just after diagnosis.
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Project description:OBJECTIVES:Early diagnosis of childhood cancer is critical. Nevertheless, little is known about the potential role of inequality. This study aims to describe the use of primary care 2?years before a childhood cancer diagnosis and to investigate whether socioeconomic factors influence the use of consultations and diagnostic tests in primary care. DESIGN:A national population-based matched cohort study. SETTING AND PARTICIPANTS:This study uses observational data from four Danish nationwide registers. All children aged 0-15 diagnosed with cancer during 2008-2015 were included (n=1386). Each case was matched based on gender and age with 10 references (n=13?860). PRIMARY AND SECONDARY OUTCOME MEASURES:The primary outcome was additional rates for consultations and for invoiced diagnostic tests for children with cancer according to parental socioeconomic factors. Furthermore, we estimated the association between socioeconomic factors and frequent use of consultations, defined as at least four consultations, and the odds of receiving a diagnostic test within 3?months of diagnosis. RESULTS:Children with cancer from families with high income had 1.46 (95% CI 1.23 to 1.69) additional consultations 3?months before diagnosis, whereas children from families with low income had 1.85 (95% CI 1.60 to 2.11) additional consultations. The highest odds of frequent use of consultations was observed among children from low-income families (OR: 1.94, 95%?CI 1.24 to 3.03). A higher odds of receiving an invoiced diagnostic test was seen for children from families with mid-educational level (OR: 1.46, 95%?CI 1.09 to 1.95). CONCLUSION:We found a socioeconomic gradient in the use of general practice before a childhood cancer diagnosis. This suggests that social inequalities exist in the pattern of healthcare utilisation in general practice.
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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.
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Project description:OBJECTIVE:Our previous randomized controlled trial found that nutrition psychoeducation (NP), an attention-control condition, produced statistically significantly more weight loss than usual care (UC), whereas motivational interviewing (MI) did not. NP, MI, and UC resulted in medium-large, medium, and negligible effects on weight loss, respectively. To examine whether weight loss could be further improved by combining MI and NP, the current study evaluated the scalable combination (MINP) with accessible web-based materials. METHODS:31 adults with overweight/obesity, with and without binge-eating disorder (BED), were enrolled in the 3-month MINP treatment in primary care. Participants were assessed at baseline, post, and 3-month follow-up. Mixed-model analyses examined MINP effects over time and the prognostic significance of BED. RESULTS:Mixed-model analyses revealed that percentage weight loss was statistically significant at post and 3-month follow-up; d'=0.59 and 0.53, respectively. BED status did not predict or moderate weight loss. Twenty-one percent (6 of 28) and 26% (7 of 27) of participants attained 5% weight loss by post-treatment and 3-month follow-up, respectively. Participants with BED had statistically significantly greater improvements in disordered eating and depression (in addition to binge-eating reductions) compared to those without BED. CONCLUSION:MINP resulted in weight and psychological improvements at post-treatment and through 3-months after treatment completion. There did not appear to be additional benefits to combining basic nutrition information with MI when compared to the previous randomized controlled trial testing nutrition psychoeducation alone. CLINICAL TRIAL REGISTRATION:NCT02578199.
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Project description:BackgroundThe COVID-19 pandemic has highlighted the urgency of addressing an epidemic of obesity and associated inflammatory illnesses. Previous studies have demonstrated that interactions between single-nucleotide polymorphisms (SNPs) and lifestyle interventions such as food and exercise may vary metabolic outcomes, contributing to obesity. However, there is a paucity of research relating outcomes from digital therapeutics to the inclusion of genetic data in care interventions.ObjectiveThis study aims to describe and model the weight loss of participants enrolled in a precision digital weight loss program informed by the machine learning analysis of their data, including genomic data. It was hypothesized that weight loss models would exhibit a better fit when incorporating genomic data versus demographic and engagement variables alone.MethodsA cohort of 393 participants enrolled in Digbi Health's personalized digital care program for 120 days was analyzed retrospectively. The care protocol used participant data to inform precision coaching by mobile app and personal coach. Linear regression models were fit of weight loss (pounds lost and percentage lost) as a function of demographic and behavioral engagement variables. Genomic-enhanced models were built by adding 197 SNPs from participant genomic data as predictors and refitted using Lasso regression on SNPs for variable selection. Success or failure logistic regression models were also fit with and without genomic data.ResultsOverall, 72.0% (n=283) of the 393 participants in this cohort lost weight, whereas 17.3% (n=68) maintained stable weight. A total of 142 participants lost 5% bodyweight within 120 days. Models described the impact of demographic and clinical factors, behavioral engagement, and genomic risk on weight loss. Incorporating genomic predictors improved the mean squared error of weight loss models (pounds lost and percent) from 70 to 60 and 16 to 13, respectively. The logistic model improved the pseudo R2 value from 0.193 to 0.285. Gender, engagement, and specific SNPs were significantly associated with weight loss. SNPs within genes involved in metabolic pathways processing food and regulating fat storage were associated with weight loss in this cohort: rs17300539_G (insulin resistance and monounsaturated fat metabolism), rs2016520_C (BMI, waist circumference, and cholesterol metabolism), and rs4074995_A (calcium-potassium transport and serum calcium levels). The models described greater average weight loss for participants with more risk alleles. Notably, coaching for dietary modification was personalized to these genetic risks.ConclusionsIncluding genomic information when modeling outcomes of a digital precision weight loss program greatly enhanced the model accuracy. Interpretable weight loss models indicated the efficacy of coaching informed by participants' genomic risk, accompanied by active engagement of participants in their own success. Although large-scale validation is needed, our study preliminarily supports precision dietary interventions for weight loss using genetic risk, with digitally delivered recommendations alongside health coaching to improve intervention efficacy.
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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.
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Project description:IntroductionHydatid disease is endemic in farming areas but occurs worldwide. The most common site of disease is liver. Hydatid disease of the spleen is a rare condition. Worldwide incidence of splenic hydatid is 0.5-4%. Surgery is the mainstay of treatment. The standard treatment is open total or partial splenectomy.Presentation of caseA 28 year-old female patient was referred to our institution, after coincidental sonography finding. On abdominal examination, there was no sensitization, and there was no resistance or rebound.Ultrasound showed an enlarge spleen; an abdominal CT confirmed the presence of a splenic cyst at the lower pole of the spleen of 7 cm in diameter, no other organ involvement. The biological confirmation was made by indirect hemagglutination. Spleen-sparing surgery was performed. Macroscopic and microscopic examination of the specimen confirmed Hydatid cyst. The patient was discharged from hospital on the seventh postoperative day with a prescription for albendazole (2 × 400 mg/day) for three months.Discussion and conclusionThe rarity of primary splenic hydatid disease poses a diagnostic challenge for clinicians, the disease should be considered in differential in every patient in endemic areas with cystic lesion of spleen until proved otherwise, it may be detected incidentally or present with non-specific complaints, preservation surgery should always be tried to avoid post splenectomy infection, especially in young patients.
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