Association of Glycemic Control Trajectory with Short-Term Mortality in Diabetes Patients with High Cardiovascular Risk: a Joint Latent Class Modeling Study

Tumor Marker Trajectories and Survival Analysis in Patients With Normal Carcinoembryonic Antigen Ranges After Colorectal Cancer Resection

BACKGROUND

Evidence regarding postoperative CEA for predicting long-term outcomes of colorectal cancer remains controversial, especially in patients with normal postoperative CEA.

OBJECTIVE

To investigate the risk difference among different postoperative CEA trajectories in patients with normal postoperative CEA after curative colorectal cancer resection.

DESIGN

This cohort study was conducted at a comprehensive cancer center and included data retrieved from a prospectively collected database between January 2006 and December 2018.

SETTINGS

Retrospective cohort study.

PATIENTS

Patients with colorectal cancer who underwent surgery for primary stage I to III colorectal adenocarcinoma were included and those with postoperative CEA >5 ng/mL were excluded.

INTERVENTIONS

Standard curative radical resection was performed.

MAIN OUTCOME MEASURES

Ten-year overall survival and disease-free survival were analyzed.

RESULTS

The study population (n = 8156) was categorized into 6 trajectories: persistent-ultralow (n = 2351), persistent-low (n = 2474), gradually decrease (n = 401), persistent-medium (n = 1727), slightly increase (n = 909), and around-upper-limit (n = 394). The median follow-up time was 7.8 years, and the median time frame in which CEA was measured to determine trajectory was 2.6 years. The persistent-ultralow group had the highest 10-year overall survival (85.1%) and disease-free survival (82.7%). The around-upper-limit group had the lowest 10-year overall survival (55.5%) and disease-free survival (53.4%). The adjusted HR trend was comparable to the crude HR of the persistent-ultralow group. Consequently, the higher initial serum CEA groups had higher HRs of overall survival and disease-free survival. The adjusted HR of overall survival was 2.96 (95% CI, 2.39-3.66) and of disease-free survival was 2.66 (95% CI, 2.18-3.69) for the around-upper-limit groups.

LIMITATIONS

Retrospective design.

CONCLUSIONS

The postoperative serum CEA trajectory is an independent factor associated with long-term outcomes. Although CEA levels were all within normal range, higher levels of postoperative serum CEA trajectory correlated with worse long-term oncological outcomes. See Video Abstract.

TRAYECTORIAS DE MARCADORES TUMORALES Y ANLISIS DE SUPERVIVENCIA EN PACIENTES CON RANGOS NORMALES DE ANTGENO CARCINOEMBRIONARIO POSTERIOR A RESECCIN DE CNCER COLORRECTAL

ANTECEDENTES:La evidencia sobre el CEA post operatorio para la predicción de los resultados a largo plazo del cáncer colorrectal sigue siendo controversial, especialmente en pacientes con CEA post quirúrgico normal.OBJETIVO:Investigar la diferencia de riesgo entre diferentes trayectorias postoperatorias del CEA en pacientes con CEA post quirúrgico normal tras la resección curativa del cáncer colorrectal.DISEÑO:Este estudio de cohorte se realizó en un centro oncológico integral e incluyó datos recuperados de una base de datos recopilada prospectivamente entre enero de 2006 y diciembre de 2018.AJUSTES:Estudio de cohorte retrospectivo.PACIENTES:Se incluyeron pacientes con el diagnostico de CCR que fueron sometidos a cirugía por adenocarcinoma colorrectal primario en estadio I-III. Se excluyeron pacientes con CEA postoperatorio >5 ng/mL.INTERVENCIONES:Se realizó una resección radical curativa estandarizada.PRINCIPALES MEDIDAS DE RESULTADO:Se analizaron la supervivencia general a diez años y la supervivencia libre de enfermedad.RESULTADOS:La población de estudio (n = 8156) fue clasificada en seis trayectorias, que incluyeron ultrabajo persistente (n = 2351), bajo persistente (n = 2474), disminución gradual (n = 401), medio persistente (n = 1727), aumento leve (n = 909) y alrededor del límite superior (n = 394). La mediana del tiempo de seguimiento fue de 7,8 años y la mediana del período de tiempo en el que el CEA fue medido para determinar la trayectoria fue de 2,6 años. El grupo ultrabajo persistente tuvo la mayor supervivencia general a 10 años (85,1 %) y supervivencia libre de enfermedad (82,7 %). El grupo alrededor del límite superior tuvo la supervivencia general a 10 años más baja (55,5 %) y la supervivencia libre de enfermedad (53,4 %). La tendencia del índice de riesgo ajustado fue comparable al índice de riesgo bruto del grupo ultrabajo persistente. En consecuencia, los grupos con CEA sérico iniciales más altos tenían índices de riesgos más altos de supervivencia general y supervivencia libre de enfermedad. Los índices de riesgos ajustados de supervivencia general/supervivencia libre de enfermedad fueron 2,96/2,66 (intervalo de confianza del 95 %: 2,39-3,66/2,18-3,69) para los grupos cercanos al límite superior.LIMITACIONES:El estudio estuvo limitado por su diseño retrospectivo.CONCLUSIONES:La trayectoria del CEA sérico postoperatorio es un factor independiente asociado con resultados a largo plazo. Aunque los niveles de CEA se encontraban todos dentro del rango normal, los niveles más altos de trayectoria del CEA en suero posoperatorio se correlacionaron con peores resultados oncológicos a largo plazo. (Traducción-Dr Osvaldo Gauto ).

Risk factors associated with glycated hemoglobin A1c trajectories progressing to type 2 diabetes

BACKGROUND AND OBJECTIVE

The notion of prediabetes, defined by the ADA as glycated hemoglobin A1c (HbA1c) of 5.7-6.4%, implies increased vascular inflammatory and immunologic processes and higher risk for developing diabetes mellitus and major cardiovascular events. We aimed to determine the risk factors associated with rapid progression of normal and prediabetes patients to type 2 diabetes mellitus (T2DM).

METHODS

Retrospective cohort study in a single 8-hospital health system in southeast Michigan, between 2006 and 2020. All patients with HbA1c <6.5% at baseline and at least 2 other HbA1c measurements were clustered in five trajectories encompassing more than 95% of the study population. Multivariate linear regression analysis was performed to examine the association of demographic and comorbidities with HbA1c trajectories progressing to diabetes.

RESULTS

A total of 5,347 prediabetic patients were clustered based on their HbA1c progression (C1: 4,853, C2: 253, C66: 102, C12: 85, C68: 54). The largest cluster (C1) had a baseline median HbA1c value of 6.0% and exhibited stable HbA1c levels in prediabetic range across all subsequent years. The smallest cluster (C68) had the lowest median baseline HbA1c value and also remained stable across subsequent years. The proportion of normal HbA1c in each of the pre-diabetic trajectories ranged from 0 to 12.7%, whereas 81.5% of the reference cluster (C68) were normal HbA1c at baseline. The C2 (steady rising) trajectory was significantly associated with BMI (adj OR 1.10, 95%CI 1.03-1.17), and family history of DM (adj OR 2.75, 95%CI 1.32-5.74). With respect to the late rising trajectories, baseline BMI was significantly associated with both C66 and C12 trajectory (adj OR 1.10, 95%CI 1.03-1.18) and (adj OR 1.13, 95%CI 1.05-1.23) respectively, whereas, the C12 trajectory was also significantly associated with age (adj OR 1.62, 95%CI 1.04-2.53) and history of MACE (adj OR 3.20, 95%CI 1.14-8.93).

CONCLUSIONS

We suggest that perhaps a more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c, whether they have normal hemoglobin A1c or they have prediabetes.KEY MESSAGESProgression to diabetes from normal or prediabetic hemoglobin A1c within four years is associated with baseline BMI.A steady rise in HbA1c during a four-year period is associated with age and family history of T2DM, whereas age and personal history of MACE are associated with a rapid rise in HbA1c.A more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c.

Effect of SARS-CoV-2 Infection and Infection Severity on Longer-Term Glycemic Control and Weight in People With Type 2 Diabetes

OBJECTIVE

To evaluate the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severity of infection with longer-term glycemic control and weight in people with type 2 diabetes (T2D) in the U.S.

RESEARCH DESIGN AND METHODS

We conducted a retrospective cohort study using longitudinal electronic health record data of patients with SARS-CoV-2 infection from the National COVID Cohort Collaborative (N3C). Patients were ≥18 years old with an ICD-10 diagnosis of T2D and at least one HbA1c and weight measurement prior to and after an index date of their first coronavirus disease 2019 (COVID-19) diagnosis or negative SARS-CoV-2 test. We used propensity scores to identify a matched cohort balanced on demographic characteristics, comorbidities, and medications used to treat diabetes. The primary outcome was the postindex average HbA1c and postindex average weight over a 1 year time period beginning 90 days after the index date among patients who did and did not have SARS-CoV-2 infection. Secondary outcomes were postindex average HbA1c and weight in patients who required hospitalization or mechanical ventilation.

RESULTS

There was no significant difference in the postindex average HbA1c or weight in patients who had SARS-CoV-2 infection compared with control subjects. Mechanical ventilation was associated with a decrease in average HbA1c after COVID-19.

CONCLUSIONS

In a multicenter cohort of patients in the U.S. with preexisting T2D, there was no significant change in longer-term average HbA1c or weight among patients who had COVID-19. Mechanical ventilation was associated with a decrease in HbA1c after COVID-19.

Great diversity in the utilization and reporting of latent growth modeling approaches in type 2 diabetes: A literature review

Introduction

The progression of complications of type 2 diabetes (T2D) is unique to each patient and can be depicted through individual temporal trajectories. Latent growth modeling approaches (latent growth mixture models [LGMM] or latent class growth analysis [LCGA]) can be used to classify similar individual trajectories in a priori non-observed groups (latent groups), sharing common characteristics. Although increasingly used in the field of T2D, many questions remain regarding the utilization of these methods.

Objective

To review the literature of longitudinal studies using latent growth modeling approaches to study T2D.

Methods

MEDLINE (Ovid), EMBASE, CINAHL and Wb of Science were searched through August 25^th, 2021. Data was collected on the type of latent growth modeling approaches (LGMM or LCGA), characteristics of studies and quality of reporting using the GRoLTS-Checklist and presented as frequencies.

Results

From the 4,694 citations screened, a total of 38 studies were included. The studies were published beetween 2011 and 2021 and the length of follow-up ranged from 8 weeks to 14 years. Six studies used LGMM, while 32 studies used LCGA. The fields of research varied from clinical research, psychological science, healthcare utilization research and drug usage/pharmaco-epidemiology. Data sources included primary data (clinical trials, prospective/retrospective cohorts, surveys), or secondary data (health records/registries, medico-administrative). Fifty percent of studies evaluated trajectory groups as exposures for a subsequent clinical outcome, while 24% used predictive models of group membership and 5% used both. Regarding the quality of reporting, trajectory groups were adequately presented, however many studies failed to report important decisions made for the trajectory group identification.

Conclusion

Although LCGA were preferred, the contexts of utilization were diverse and unrelated to the type of methods. We recommend future authors to clearly report the decisions made regarding trajectory groups identification.

•

There is a growing body of literature on trajectory modeling in type 2 diabetes.

•

Latent class growth analysis can be used in many different contexts.

•

The current reporting of methods used should be improved.

The association between trajectories of risk factors and risk of cardiovascular disease or mortality among patients with diabetes or hypertension: A systematic review

Introduction

Cardiometabolic risk factors and renal function are monitored regularly for patients with diabetes mellitus (DM)/ hypertension (HT). In addition to risk factor levels at a single time point, their trajectory (changes over time) can also be differentially related to the risk of cardiovascular diseases (CVD) and mortality. This study aimed to systematically examine the evidence regarding the association between risk factor trajectories and risk of CVD/mortality in patients with DM/HT.

Method

PubMed, MEDLINE, and Embase were searched for articles from January 1963 to April 2021. Inclusion criteria: studies that 1) analyzed trajectories of risk factors including haemoglobin A1c (HbA1c), blood pressure, estimated glomerular filtration rate (eGFR), body mass index (BMI), and blood lipids; 2) were performed in the DM/HT population and, 3) included risk of CVD/mortality as outcomes. Study quality was assessed using the Newcastle-Ottawa quality assessment scale.

Results

A total of 22,099 articles were identified. After screening by title and abstract, 22,027 articles were excluded by irrelevant outcomes, exposure, population, or type of articles. Following full-text screening, 11 articles investigating the trajectories of HbA1c (N = 7), systolic blood pressure (SBP) (N = 3), and eGFR (N = 1) were included for data extraction and analysis. No studies were identified examining the association of BMI or lipid trajectories with CVD/mortality. All included studies were of good quality based on the NOS criteria. In general, stable trajectories within optimal ranges of the risk factors (HbA1c: <7%, SBP: 120-139mmHg, eGFR: >60mL/min/1.73m²) had the lowest CVD/mortality risk compared to an increasing HbA1c trajectory (from 8% to 10%), an increasing SBP trajectory (from 120–139 to ≥140mmHg), or a decreasing eGFR trajectory (from 90 to 70mL/min/1.73m²).

Conclusion

A relatively stable and well-controlled trajectory for cardiometabolic risk factors was associated with the lowest risk of CVD/mortality. Risk factor trajectories have important clinical implications in addition to single time point measurements. More attention should be given to patients with suboptimal control and those with unstable trends of cardiometabolic risk factors.