Generalized Estimating Equation (GEE) is a marginal model popularly applied for longitudinal/clustered data analysis in clinical trials or biomedical studies. We provide a systematic review on GEE including basic concepts as well as several recent developments due to practical challenges in real applications. The topics including the selection of “working” correlation structure, sample size and power calculation, and the issue of informative cluster size are covered because these aspects play important roles in GEE utilization and its statistical inference. A brief summary and discussion of potential research interests regarding GEE are provided in the end.

Studying survivorship and causes of death in patients with advanced or metastatic cancer remains an important task. We characterize the causes of death among patients with metastatic cancer, across 13 cancer types and 25 non-cancer causes and predict the risk of death after diagnosis from the diagnosed cancer versus other causes (e.g., stroke, heart disease, etc.). Among 1,030,937 US (1992–2019) metastatic cancer survivors, 82.6% of patients (n = 688,529) died due to the diagnosed cancer, while 17.4% (n = 145,006) died of competing causes. Patients with lung, pancreas, esophagus, and stomach tumors are the most likely to die of their metastatic cancer, while those with prostate and breast cancer have the lowest likelihood. The median survival time among patients living with metastases is 10 months; our Fine and Gray competing risk model predicts 1 year survival with area under the receiver operating characteristic curve of 0.754 (95% CI [0.754, 0.754]). Leading non-cancer deaths are heart disease (32.4%), chronic obstructive and pulmonary disease (7.9%), cerebrovascular disease (6.1%), and infection (4.1%).

BACKGROUND AND OBJECTIVE: To reduce missed cases of pediatric abusive head trauma (AHT), Pediatric Brain Injury Research Network investigators derived a 4-variable AHT clinical prediction rule (CPR) with sensitivity of .96. Our objective was to validate the screening performance of this AHT CPR in a new, equivalent patient population. METHODS: We conducted a prospective, multicenter, observational, cross-sectional study. Applying the same inclusion criteria, definitional criteria for AHT, and methods used in the completed derivation study, Pediatric Brain Injury Research Network investigators captured complete clinical, historical, and radiologic data on 291 acutely head-injured children <3 years of age admitted to PICUs at 14 participating sites, sorted them into comparison groups of abusive and nonabusive head trauma, and measured the screening performance of the AHT CPR. RESULTS: In this new patient population, the 4-variable AHT CPR demonstrated sensitivity of .96, specificity of .46, positive predictive value of .55, negative predictive value of .93, positive likelihood ratio of 1.67, and negative likelihood ratio of 0.09. Secondary analysis revealed that the AHT CPR identified 98% of study patients who were ultimately diagnosed with AHT. CONCLUSIONS: Four readily available variables (acute respiratory compromise before admission; bruising of the torso, ears, or neck; bilateral or interhemispheric subdural hemorrhages or collections; and any skull fractures other than an isolated, unilateral, nondiastatic, linear, parietal fracture) identify AHT with high sensitivity in young, acutely head-injured children admitted to the PICU.

Background: Previous studies have demonstrated epidemiological trends in individual metastatic cancer subtypes; however, research forecasting long-term incidence trends and projected survivorship of metastatic cancers is lacking. We assess the burden of metastatic cancer to 2040 by (1) characterizing past, current, and forecasted incidence trends, and (2) estimating odds of long-term (5-year) survivorship. Methods: This retrospective, serial cross-sectional, population-based study used registry data from the Surveillance, Epidemiology, and End Results (SEER 9) database. Average annual percentage change (AAPC) was calculated to describe cancer incidence trends from 1988 to 2018. Autoregressive integrating moving average (ARIMA) models were used to forecast the distribution of primary metastatic cancer and metastatic cancer to specific sites from 2019 to 2040 and JoinPoint models were fitted to estimate mean projected annual percentage change (APC). Results: The average annual percent change (AAPC) in incidence of metastatic cancer decreased by 0.80 per 100,000 individuals (1988–2018) and we forecast an APC decrease by 0.70 per 100,000 individuals (2018–2040). Analyses predict a decrease in metastases to liver (APC = −3.40, 95% CI [−3.50, −3.30]), lung (APC (2019–2030) = −1.90, 95% CI [−2.90, −1.00]); (2030–2040) = −3.70, 95% CI [−4.60, −2.80]), bone (APC = −4.00, 95% CI [−4.30, −3.70]), and brain (APC = −2.30, 95% CI [−2.60, −2.00]). By 2040, patients with metastatic cancer are predicted to have 46.7% greater odds of long-term survivorship, driven by increasing plurality of patients with more indolent forms of metastatic disease. Conclusions: By 2040, the distribution of metastatic cancer patients is predicted to shift in predominance from invariably fatal to indolent cancers subtypes. Continued research on metastatic cancers is important to guide health policy and clinical intervention efforts, and direct allocations of healthcare resources.

T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif (ITIM) domain (TIGIT) and programmed cell death protein 1 (PD-1) are important inhibitory receptors that associate with T cell exhaustion in acute myeloid leukemia (AML). In this study, we aimed to determine the underlying transcriptional mechanisms regulating these inhibitory pathways. Specifically, we investigated the role of transcription factor B lymphocyte-induced maturation protein 1 (Blimp-1) in T cell response and transcriptional regulation of TIGIT and PD-1 in AML. Peripheral blood samples collected from patients with AML were used in this study. Blimp-1 expression was examined by flow cytometry. The correlation of Blimp-1 expression to clinical characteristics of AML patients was analyzed. Phenotypic and functional studies of Blimp-1-expressing T cells were performed using flow cytometry-based assays. Luciferase reporter assays and ChIP assays were applied to assess direct binding and transcription activity of Blimp-1. Using siRNA to silence Blimp-1, we further elucidated the regulatory role of Blimp-1 in the TIGIT and PD-1 expression and T cell immune response. Blimp-1 expression is elevated in T cells from AML patients. Consistent with exhaustion, Blimp-1+ T cells upregulate multiple inhibitory receptors including PD-1 and TIGIT. In addition, they are functionally impaired manifested by low cytokine production and decreased cytotoxicity capacity. Importantly, the functional defect is reversed by inhibition of Blimp-1 via siRNA knockdown. Furthermore, Blimp-1 binds to the promoters of PD-1 and TIGIT and positively regulates their expression. Our study demonstrates an important inhibitory effect of Blimp-1 on T cell response in AML; thus, targeting Blimp-1 and its regulated molecules to improve the immune response may provide effective leukemia therapeutics.