Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation

BACKGROUND

The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy.

METHODS

For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961-2007, median latest follow-up years 1980-2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU.

FINDINGS

For participants with diabetes, we observed a linear dose-response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43-2·97) when diagnosed at 30-39 years, 2·26 (2·08-2·45) at 40-49 years, 1·84 (1·72-1·97) at 50-59 years, 1·57 (1·47-1·67) at 60-69 years, and 1·39 (1·29-1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier.

INTERPRETATION

Every decade of earlier diagnosis of diabetes was associated with about 3-4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes.

FUNDING

British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.

Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP

Background

The 2021 ESC guideline on cardiovascular disease (CVD) prevention qualitatively categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, SCORE2 and SCORE2-OP, to predict CVD risk.

Purpose

To develop and validate an “Add-on” to incorporate CKD measures into these algorithms, using a validated approach.

Methods

In 3,054,840 participants from 34 datasets, we developed three Add-ons (eGFR only, eGFR + urinary albumin-to-creatinine ratio [ACR] [the primary Add-on], and eGFR + dipstick proteinuria) for SCORE2 and SCORE2-OP. We validated c-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,995,067 participants from 33 different datasets.

Results

In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved c-statistic by 0.006 (95% CI 0.005–0.008) and 0.018 (0.012–0.024), respectively, for SCORE2 and 0.012 (0.009–0.015) and 0.023 (0.013–0.032), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57,485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI (e.g., 0.100 [0.062–0.138] for SCORE2) compared to the qualitative approach in the ESC guideline.

Conclusion

Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.

Funding Acknowledgement

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): US National Kidney Foundation funding as well as US NIDDK

The value of additional risk factors for improving 10-year cardiovascular risk prediction in apparently healthy people

Background

In clinical practice, factors known to be associated with cardiovascular disease (CVD) like albuminuria, education level, or coronary calcium score are not directly incorporated in cardiovascular risk prediction models. The aim of the current study was to quantify the added value of potential risk modifying characteristics when added to the SCORE2 algorithm for individuals without diabetes mellitus (DM) or prior CVD.

Methods and results

Individuals without previous CVD or DM were included from the ARIC, MESA, EPIC-NL and HNR studies (n=46,285) in whom 2,177 CVD events and 2,062 non-cardiovascular deaths were observed over exactly 10.0 years of follow-up. The effect of each possible risk modifying characteristic was derived using Fine and Gray models that included an offset term for the SCORE2 linear predictor. The risk modifying characteristics were applied to individual predictions using the “naïve approach”, which modifies predicted risks based on the population prevalence and the SHR of the relevant predictor. Subdistribution hazard ratios are presented in the table. External validation was performed in the CPRD cohort (UK, n=518,015, 12,675 CVD events). In the external validation, adjustment of SCORE2 predicted risks with both single and with all available risk modifiers did not negatively affect calibration (see figure) and led to a modest increase in discrimination (C-index 0.742 [95% CI 0.737–0.746] versus unimproved SCORE2 risk C-index 0.737 [95% CI 0.732–0.741]). The net reclassification index or adding all these predictors was +0.032 (95% CI 0.025; 0.028) for future events and −0.008 (95% CI −0.009; −0.007) for future non-events. The coronary calcium score was found to the single strongest added predictor.

Interpretation

The current analysis presents a method on how to integrate possible risk modifying characteristics that are not included in existing CVD risk models for the prediction of CVD event risk in apparently healthy people. This flexible methodology improves the accuracy of predicted risks and increases applicability of prediction models for individuals with additional risk known modifiers

Funding Acknowledgement

Type of funding sources: None.

Province-specific recalibration of CVD risk models using population-specific routine data for Chinese people is important

Funding Acknowledgements

Type of funding sources: None.

Background

Cardiovascular diseases (CVD) are the leading causes of death in China. Since population CVD incidence and risk factor levels vary considerably across regions in China, geo-specific investment in the prevention of CVD could be advantageous. Risk prediction models are an integral part of CVD prevention guidelines and can be used to help guide intervention. However, there is no CVD model generalizable to the various incidence rates, risk-factor levels and composition of CVD in different regions of China.

Purpose

To construct a CVD risk estimation system, which is calibrated to CVD risk in different regions in China, and can be regularly updated in the future using routinely available aggregate level CVD incidence and risk factor data, in response to changing trends with time and divergent CVD rates.

Methods

The risk prediction model used was the WHO CVD score, initially calibrated to predict CVD mortality in the whole of mainland China. Further province-specific recalibration was then completed to give models tailored to the 31 provinces. The recalibration approach used aggregate level province, sex- and age group-specific levels of risk factors and CVD mortality. Risk factor values were estimated using 145 268 participants aged 40-80 years old from the China Chronic Disease and Risk Factors Surveillance, a nationally and provincially representative cross-sectional survey in 2015. Province-specific CVD mortality rates in 2017 were estimated based on published scientific reports, unpublished registry data, and health system administrative data.

Results

Compared with the province-specific models, the China-specific WHO score overestimated mortality risk in some provinces while underestimating risk in others. For example, while the predicted population risk of 10-year CVD mortality was 3.5% in male in both Shanghai and Hebei using the China-specific score (with province-specific observed risk factor values), the province-specific scores gave predicted population risks of 1.1% for Shanghai and 5.5% for Hebei. Accordingly, using the province-specific scores for an individual with the same combination of risk factors, the 10-year risk of CVD mortality differed substantially across provinces. For example, the estimated 10-year risk for a 60 year old, male smoker without diabetes and systolic blood pressure of 140 mmHg and total cholesterol 5 mmol/L ranged from 2.4% in Shanghai to 13.2% in Tibet. Similarly, the estimated 10-year risk for a female with the same risk factor profile ranged from 1.5% in Shanghai to 11.5% in Tibet.

Conclusion

We have developed a CVD risk estimation system, which is calibrated to CVD risk in different provinces of China, and can be regularly recalibrated in the future using routinely available information. Application of this approach should help accurately estimate CVD risk in individuals from China, and assist policy makers in making more appropriate decisions about allocation of preventative resources.

Abstract Figure. Predicted 10 year CVD mortality risk

Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

BACKGROUND

Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances.

METHODS

We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease.

FINDINGS

Analyses included data for 698 782 people (52 765 non-fatal or fatal vascular outcomes; 8.49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2.00 (95% CI 1.83-2.19) for coronary heart disease; 2.27 (1.95-2.65) for ischaemic stroke; 1.56 (1.19-2.05) for haemorrhagic stroke; 1.84 (1.59-2.13) for unclassified stroke; and 1.73 (1.51-1.98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40-59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10-12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3.90 mmol/L and 5.59 mmol/L. Compared with fasting blood glucose concentrations of 3.90-5.59 mmol/L, HRs for coronary heart disease were: 1.07 (0.97-1.18) for lower than 3.90 mmol/L; 1.11 (1.04-1.18) for 5.60-6.09 mmol/L; and 1.17 (1.08-1.26) for 6.10-6.99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors.

INTERPRETATION

Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and non-linearly associated with risk of vascular disease.

FUNDING

British Heart Foundation, UK Medical Research Council, and Pfizer.

Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

BACKGROUND

Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances.

METHODS

We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease.

FINDINGS

Analyses included data for 698 782 people (52 765 non-fatal or fatal vascular outcomes; 8.49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2.00 (95% CI 1.83-2.19) for coronary heart disease; 2.27 (1.95-2.65) for ischaemic stroke; 1.56 (1.19-2.05) for haemorrhagic stroke; 1.84 (1.59-2.13) for unclassified stroke; and 1.73 (1.51-1.98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40-59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10-12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3.90 mmol/L and 5.59 mmol/L. Compared with fasting blood glucose concentrations of 3.90-5.59 mmol/L, HRs for coronary heart disease were: 1.07 (0.97-1.18) for lower than 3.90 mmol/L; 1.11 (1.04-1.18) for 5.60-6.09 mmol/L; and 1.17 (1.08-1.26) for 6.10-6.99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors.

INTERPRETATION

Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and non-linearly associated with risk of vascular disease.

FUNDING

British Heart Foundation, UK Medical Research Council, and Pfizer.

The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases

Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of individual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age- and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily, with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.

Serum insulin-like growth factor-I, IGF binding protein-3 and IGFBP-3 protease activity after cranial irradiation

The relationship between peak growth hormone (GH), insulin-like growth factor I (IGF-I), IGF-I binding protein 3 (IGFBP-3) and IGFBP-3 protease activity was studied in 28 children and adolescents undergoing investigation of pituitary function 0.4-14.2 years after cranial or craniospinal irradiation for the treatment of CNS tumours distant from the hypothalamic-pituitary axis (n = 16) or prophylaxis against CNS leukaemia (n = 12). Seven out of 15 patients with GH deficiency (GHD) (defined as a peak GH concentration <7.5 ng/ml in a stimulation test) had IGF-I <-2 standard deviation score (SDS). None of the 28 patients had serum IGFBP-3 concentrations measured by radioimmunoassay (RIA) <-1.5 SDS with no difference between those with and without GHD. IGFBP-3 concentrations measured by RIA were strongly correlated to IGFBP-3 band density on Western ligand blot (WLB) (r = 0.71; p < 0.0001). IGFBP-3 protease activity was negatively correlated to IGFBP-3 by RIA (r = -0.55; p < 0.01) and to IGFBP-3 by WLB (r = -0.51; p < 0.01). Twenty-two patients had normal IGFBP-3 protease activity (<30% of the activity in pregnancy serum) indicating that serum IGFBP-3 protease activity does not account for the normal levels of IGFBP-3 in RIA. Low serum IGF-I but normal IGFBP-3 concentrations and in the majority normal IGFBP-3 protease activity was found in patients in the years after CNS irradiation. Neither serum IGF-I nor IGFBP-3 can be used as a reliable index of the development of radiation-induced GHD.

Relationship between serum and urinary insulin-like growth factor-I through childhood and adolescence: their use in the assessment of disordered growth

OBJECTIVE

Serum insulin-like growth factor-I (sIGF-I) measurement as an index of growth hormone status has become a common test in the investigation of disordered growth. IGF-I may also be measured in the urine. The aims of this study were to investigate the correlation between serum and urinary IGF-I in normal children and compare their use in the evaluation of growth disorders.

DESIGN

Normal ranges for serum and urinary IGF-I were devised from a cross-sectional study of normal schoolchildren. These were then used to assess the sensitivity and specificity of serum and urinary IGF-I in the diagnosis of childhood GH deficiency.

PATIENTS

A cohort of 333 (M = 156, F = 177) healthy schoolchildren aged 5-19 years were recruited and data previously collected from 22 growth hormone deficient (GHD) and 47 short normal (SN) children were compared with those of the normal children.

MEASUREMENTS

Height, weight and pubertal status were assessed in all children. Serum IGF-I (sIGF-I) (n = 305) and total amount of urinary IGF-I excreted overnight (TuIGF-I) (n = 205) were measured by RIA using excess IGF-II to block the interference of IGFBPs.

RESULTS

Serum IGF-I was loge transformed and overall levels (geometric mean +/- 1 tolerance factor) were higher in females than males (F: 569 (329, 985) micrograms/l; M: 398 (227, 696) micrograms/l). LogeIGF-I correlated with age (F: r = +0.76, P < 0.001, M: r = +0.71, P < 0.001) and was significantly affected by both sex and Tanner stage of puberty (TS) (both P < 0.001). The distribution of TuIGF-I was normalized by performing a square root transformation (square root of TuIGF-I). square root of TuIGF-I was correlated with age (F: r = +0.36, P < 0.001; M: r = +0.5, P < 0.001) and was significantly affected by TS (P < 0.001). In both sexes there was a highly significant correlation between logeIGF-I and square root of TuIGF-I (F: r = +0.39, P < 0.001; M: r = +0.41, P < 0.001). Using the third centile of our normal ranges as a cut off to identify GHD, sIGF-I had a sensitivity of 82% and specificity of 62%, whereas TuIGF-I had a sensitivity of 18% and specificity of 79%.

CONCLUSIONS

This study demonstrates that although urinary IGF-I has no place in the diagnosis of growth disorders, in normal children there is a highly significant relationship between serum and urinary IGF-I with levels of each changing in a similar manner through childhood and adolescence. Thus, TuIGF-I could be used as a valid surrogate for sIGF-I in the physiological assessment of the relationship between IGF-I status and the normal growth process.

Insulin-like growth factor I, IGF binding protein 3, and IGFBP protease activity: relation to anthropometric indices in solid tumours or leukaemia

OBJECTIVES

To measure the serum concentrations of insulin-like growth factor I (IGF-I) and IGF binding protein 3 (IGFBP-3), and the level of IGFBP-3 protease activity in 38 children presenting with malignancies, and to assess their relation with auxological parameters and nutritional status.

METHODS

Height, weight, skinfold thickness, and mid-upper arm circumference (MUAC) were recorded using standard techniques. IGF-I and IGFBP-3 were measured using specific radioimmunoassays. Serum IGFBPs were also visualised on western ligand blot. IGFBP-3 protease activity was assessed by the extent of fragmentation of recombinant [125I]-IGFBP-3, compared with that induced by pregnancy serum. Anthropometric and radioimmunoassay data were expressed as standard deviation scores (SDS).

RESULTS

The median (range) IGF-I SDS was significantly reduced in all patients (-1.1 (-5.1 to 1.2)) and lower in children who were malnourished (-2.5 (-3.9 to 0.1)). IGFBP-3 SDS was within the normal range for 31 of 38 patients but IGFBP-3 protease activity was raised in all patients. Neither IGFBP-3 concentration nor protease activity was affected by nutritional status. IGF-I correlated with MUAC (r = 0.41) and subscapular skinfold thickness SDS (r = 0.38), but not with weight, height, weight for height, or triceps skinfold thickness.

CONCLUSIONS

IGF-I is low in children with malignancies, and even lower in those who are malnourished. IGFBP-3 concentrations were normal in most patients but interpretation is complicated by the presence of raised IGFBP-3 protease activity, which could lead to overestimating concentrations of intact peptide. IGF-I appears to relate to arm anthropometry as an index of nutritional status but not height, weight, or weight for height, as would be expected in normal children.