Weight loss as a predictor of cancer and serious disease in primary care: an ISAC-approved CPRD protocol for a retrospective cohort study using routinely collected primary care data from the UK

Prioritising primary care patients with unexpected weight loss for cancer investigation: diagnostic accuracy study (update)

OBJECTIVE

To quantify the predictive value of unexpected weight loss 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 (update).

SETTING

Data from Clinical Practice Research Datalink electronic health records linked to the National Cancer Registration and Analysis Service in primary care, England.

PARTICIPANTS

326 240 adults (≥18 years) with a code for unexpected weight loss from 1 January 2000 to 31 December 2019.

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 326 240 adults with unexpected weight loss, 184 270 (56.5%) were women, 176 508 (54.1%) were aged ≥60 years, and 176 053 (54.0%) were ever smokers. 15 624 (4.8%) had a diagnosis of cancer within six months of the index date, of whom 15 051 (96.3%) were aged ≥50 years. 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 men aged ≥50 years and women aged ≥60 years. 17 additional clinical features were associated with cancer in younger men with unexpected weight loss, and eight in women. Positive likelihood ratios in men ranged from 1.43 (95% confidence interval 1.30 to 1.58) for fatigue to 21.00 (8.59 to 51.37) for rectal mass, and in women from 1.28 (1.16 to 1.41) for back pain to 19.46 (12.69 to 29.85) for pelvic mass. Abnormal blood test results associated with cancer included low albumin (positive likelihood ratio 3.24, 3.13 to 3.35) and raised platelets (3.48, 3.35 to 3.62), total white cell count (3.01, 2.89 to 3.14), and C reactive protein (3.13, 3.05 to 3.20). However, no normal blood test result in isolation ruled out cancer. Clinical features co-occurring with unexpected weight loss were associated with multiple cancer sites.

CONCLUSION

The risk of cancer in younger adults with unexpected weight loss presenting to primary care is <3% and does not merit investigation under current UK guidelines. However, in men aged ≥50 years, women aged ≥60 years, and younger 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 weight loss.

READERS' NOTE

This article is an updated version of a previously published BMJ paper that has since been retracted.

Referral to the NHS Diabetes Prevention Programme and conversion from nondiabetic hyperglycaemia to type 2 diabetes mellitus in England: A matched cohort analysis

BACKGROUND

The NHS Diabetes Prevention Programme (NDPP) is a behaviour change programme for adults who are at risk of developing type 2 diabetes mellitus (T2DM): people with raised blood glucose levels, but not in the diabetic range, diagnosed with nondiabetic hyperglycaemia (NDH). We examined the association between referral to the programme and reducing conversion of NDH to T2DM.

METHODS AND FINDINGS

Cohort study of patients attending primary care in England using clinical Practice Research Datalink data from 1 April 2016 (NDPP introduction) to 31 March 2020 was used. To minimise confounding, we matched patients referred to the programme in referring practices to patients in nonreferring practices. Patients were matched based on age (≥3 years), sex, and ≥365 days of NDH diagnosis. Random-effects parametric survival models evaluated the intervention, controlling for numerous covariates. Our primary analysis was selected a priori: complete case analysis, 1-to-1 practice matching, up to 5 controls sampled with replacement. Various sensitivity analyses were conducted, including multiple imputation approaches. Analysis was adjusted for age (at index date), sex, time from NDH diagnosis to index date, BMI, HbA1c, total serum cholesterol, systolic blood pressure, diastolic blood pressure, prescription of metformin, smoking status, socioeconomic status, a diagnosis of depression, and comorbidities. A total of 18,470 patients referred to NDPP were matched to 51,331 patients not referred to NDPP in the main analysis. Mean follow-up from referral was 482.0 (SD = 317.3) and 472.4 (SD = 309.1) days, for referred to NDPP and not referred to NDPP, respectively. Baseline characteristics in the 2 groups were similar, except referred to NDPP were more likely to have higher BMI and be ever-smokers. The adjusted HR for referred to NDPP, compared to not referred to NDPP, was 0.80 (95% CI: 0.73 to 0.87) (p < 0.001). The probability of not converting to T2DM at 36 months since referral was 87.3% (95% CI: 86.5% to 88.2%) for referred to NDPP and 84.6% (95% CI: 83.9% to 85.4%) for not referred to NDPP. Associations were broadly consistent in the sensitivity analyses, but often smaller in magnitude. As this is an observational study, we cannot conclusively address causality. Other limitations include the inclusion of controls from the other 3 UK countries, data not allowing the evaluation of the association between attendance (rather than referral) and conversion.

CONCLUSIONS

The NDPP was associated with reduced conversion rates from NDH to T2DM. Although we observed smaller associations with risk reduction, compared to what has been observed in RCTs, this is unsurprising since we examined the impact of referral, rather than attendance or completion of the intervention.

Serious disease risk among patients with unexpected weight loss: a matched cohort of over 70 000 primary care presentations

BACKGROUND

Unexpected 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.

METHODS

This 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.

RESULTS

Between 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).

CONCLUSIONS

This 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.

Combining simple blood tests to identify primary care patients with unexpected weight loss for cancer investigation: Clinical risk score development, internal validation, and net benefit analysis

BACKGROUND

Unexpected 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 FINDINGS

We 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.

CONCLUSIONS

Our 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.

Patterns of age disparities in colon and lung cancer survival: a systematic narrative literature review

OBJECTIVES

To identify patterns of age disparities in cancer survival, using colon and lung cancer as exemplars.

DESIGN

Systematic review of the literature.

DATA SOURCES

We searched Embase, MEDLINE, Scopus and Web of Science through 18 December 2020.

ELIGIBILITY CRITERIA

We retained all original articles published in English including patients with colon or lung cancer. Eligible studies were required to be population-based, report survival across several age groups (of which at least one was over the age of 65) and at least one other characteristic (eg, sex, treatment).

DATA EXTRACTION AND SYNTHESIS

Two independent reviewers extracted data and assessed the quality of included studies against selected evaluation domains from the QUIPS tool, and items concerning statistical reporting. We evaluated age disparities using the absolute difference in survival or mortality rates between the middle-aged group and the oldest age group, or by describing survival curves.

RESULTS

Out of 3047 references, we retained 59 studies (20 for colon, 34 for lung and 5 for both sites). Regardless of the cancer site, the included studies were highly heterogeneous and often of poor quality. The magnitude of age disparities in survival varied greatly by sex, ethnicity, socioeconomic status, stage at diagnosis, cancer site, and morphology, the number of nodes examined and treatment strategy. Although results were inconsistent for most characteristics, we consistently observed greater age disparities for women with lung cancer compared with men. Also, age disparities increased with more advanced stages for colon cancer and decreased with more advanced stages for lung cancer.

CONCLUSIONS

Although age is one of the most important prognostic factors in cancer survival, age disparities in colon and lung cancer survival have so far been understudied in population-based research. Further studies are needed to better understand age disparities in colon and lung cancer survival.

PROSPERO REGISTRATION NUMBER

CRD42020151402.

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

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.

The association between unexpected weight loss and cancer diagnosis in primary care: a matched cohort analysis of 65,000 presentations

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.

Determinants and extent of weight recording in UK primary care: an analysis of 5 million adults' electronic health records from 2000 to 2017

BACKGROUND

Excess weight and unexpected weight loss are associated with multiple disease states and increased morbidity and mortality, but weight measurement is not routine in many primary care settings. The aim of this study was to characterise who has had their weight recorded in UK primary care, how frequently, by whom and in relation to which clinical events, symptoms and diagnoses.

METHODS

A longitudinal analysis of UK primary care electronic health records (EHR) data from 2000 to 2017. Descriptive statistics were used to summarise weight recording in terms of patient sociodemographic characteristics, health professional encounters, clinical events, symptoms and diagnoses. Negative binomial regression was used to model the likelihood of having a weight record each year, and Cox regression to the likelihood of repeated weight recording.

RESULTS

A total of 14,049,871 weight records were identified in the EHR of 4,918,746 patients during the study period, representing 26,998,591 person-years of observation. Around a third of patients had a weight record each year. Forty-nine percent of weight records were repeated within a year with an average time to a repeat weight record of 1.92 years. Weight records were most often taken by nursing staff (38-42%) and GPs (37-39%) as part of a routine clinical care, such as chronic disease reviews (16%), medication reviews (6-8%) and health checks (6-7%), or were associated with consultations for contraception (5-8%), respiratory disease (5%) and obesity (1%). Patient characteristics independently associated with an increased likelihood of weight recording were as follows: female sex, younger and older adults, non-drinkers, ex-smokers, low or high BMI, being more deprived, diagnosed with a greater number of comorbidities and consulting more frequently. The effect of policy-level incentives to record weight did not appear to be sustained after they were removed.

CONCLUSION

Weight recording is not a routine activity in UK primary care. It is recorded for around a third of patients each year and is repeated on average every 2 years for these patients. It is more common in females with higher BMI and in those with comorbidity. Incentive payments and their removal appear to be associated with increases and decreases in weight recording.