Biomarker stratified clinical trial designs are versatile tools to assess biomarker clinical utility and address its relationship with clinical endpoints. Due to imperfect assays and/or ...classification rules, biomarker status is prone to errors. To account for biomarker misclassification, we consider a two‐stage stratified design for survival outcomes with an adjustment for misclassification in predictive biomarkers. Compared to continuous and/or binary outcomes, the test statistics for survival outcomes with an adjustment for biomarker misclassification is much more complicated and needs to take special care. We propose to use the information from the observed biomarker status strata to construct adjusted log‐rank statistics for true biomarker status strata. These adjusted log‐rank statistics are then used to develop sequential tests for the global (composite) hypothesis and component‐wise hypothesis. We discuss the power analysis with the control of the type‐I error rate by using the correlations between the adjusted log‐rank statistics within and between the design stages. Our method is illustrated with examples of the recent successful development of immunotherapy in nonsmall‐cell lung cancer.
Multivariate failure time data are frequently analyzed using the marginal proportional hazards models and the frailty models. When the sample size is extraordinarily large, using either approach ...could face computational challenges. In this paper, we focus on the marginal model approach and propose a divide‐and‐combine method to analyze large‐scale multivariate failure time data. Our method is motivated by the Myocardial Infarction Data Acquisition System (MIDAS), a New Jersey statewide database that includes 73,725,160 admissions to nonfederal hospitals and emergency rooms (ERs) from 1995 to 2017. We propose to randomly divide the full data into multiple subsets and propose a weighted method to combine these estimators obtained from individual subsets using three weights. Under mild conditions, we show that the combined estimator is asymptotically equivalent to the estimator obtained from the full data as if the data were analyzed all at once. In addition, to screen out risk factors with weak signals, we propose to perform the regularized estimation on the combined estimator using its combined confidence distribution. Theoretical properties, such as consistency, oracle properties, and asymptotic equivalence between the divide‐and‐combine approach and the full data approach are studied. Performance of the proposed method is investigated using simulation studies. Our method is applied to the MIDAS data to identify risk factors related to multivariate cardiovascular‐related health outcomes.
A two‐stage enrichment design is a type of adaptive design, which extends a stratified design with a futility analysis on the marker negative cohort at the first stage, and the second stage can be ...either a targeted design with only the marker positive stratum, or still the stratified design with both marker strata, depending on the result of the interim futility analysis. In this paper, we consider the situation where the marker assay and the classification rule are possibly subject to error. We derive the sequential tests for the global hypothesis as well as the component tests for the overall cohort and the marker‐positive cohort. We discuss the power analysis with the control of the type I error rate and show the adverse impact of the misclassification on the powers. We also show the enhanced power of the two‐stage enrichment over the one‐stage design and illustrate with examples of the recent successful development of immunotherapy in non–small‐cell lung cancer.
Purpose
The Epworth sleepiness scale (ESS) is a widely used tool which has been validated as a measure of sleepiness. However, the scores within individual patients referred for clinical sleep ...services vary considerably which may limit the clinical use of the ESS. We sought to determine the test-retest reliability of the ESS if scores were classified as either normal or sleepy.
Methods
We measured the ESS in patients presenting to our sleep center at a clinical visit and again when a sleep study was done. Demographic and clinical information was extracted from the electronic medical record.
Results
Average ESS scores were similar on 2 administrations, mean (SD) of 9.8 (5.4) and 10.2 (6.2). Bland-Altman analysis showed upper and lower limits of agreement of 7.5 and − 6.7, respectively. No demographic or clinical variables were identified which contributed to the intra-individual variability. Of the patients who presented with an initial ESS < 11, 80% had a second ESS < 11. Of the patients who presented with an initial ESS ≥ 11, 89% had a second ESS ≥ 11. Cohen’s kappa for the two administrations of the ESS was 0.67 (95% CI of 0.51–0.83). Using previously published reports, we calculated Cohen’s kappa for polysomnographic determination of the apnea-hypopnea index (AHI) with values ranging from 0.26 to 0.69.
Conclusions
Individual ESS scores varied considerably within individual patients, but with classification into either normal or sleepy, the test-retest reliability was substantial and in line with other clinical measures including polysomnographic determination of the AHI.
Background and Objectives
The COVID‐19 pandemic significantly affected healthcare delivery, shifting focus away from nonurgent care. The aim of this study was to examine the impact of the pandemic on ...the practice of surgical oncology.
Methods
A web‐based survey of questions about changes in practice during the COVID‐19 pandemic was approved by the Society of Surgical Oncology (SSO) Research and Executive Committees and sent by SSO to its members.
Results
A total of 121 SSO members completed the survey, 77.7% (94/121) of whom were based in the United States. Breast surgeons were more likely than their peers to refer patients to neoadjuvant therapy (p = 0.000171). Head and neck surgeons were more likely to refer patients to definitive nonoperative treatment (p = 0.044), while melanoma surgeons were less likely to do so (p = 0.029). In all, 79.2% (95/120) of respondents are currently using telemedicine. US surgeons were more likely to use telemedicine (p = 0.004). Surgeons believed telemedicine is useful for long‐term/surveillance visits (70.2%, 80/114) but inappropriate (50.4%, 57/113) for new patient visits.
Conclusion
COVID‐19 pandemic resulted in increased use of neoadjuvant therapy, delays in operative procedures, and increased use of telemedicine. Telemedicine is perceived to be most efficacious for long‐term/surveillance visits or postoperative visits.
Phosphoglycerate dehydrogenase (PHGDH), the first rate-limiting enzyme of serine synthesis, is frequently overexpressed in human cancer. PHGDH overexpression activates serine synthesis to promote ...cancer progression. Currently, PHGDH regulation in normal cells and cancer is not well understood. Parkin, an E3 ubiquitin ligase involved in Parkinson's disease, is a tumor suppressor. Parkin expression is frequently downregulated in many types of cancer, and its tumor-suppressive mechanism is poorly defined. Here, we show that PHGDH is a substrate for Parkin-mediated ubiquitination and degradation. Parkin interacted with PHGDH and ubiquitinated PHGDH at lysine 330, leading to PHGDH degradation to suppress serine synthesis. Parkin deficiency in cancer cells stabilized PHGDH and activated serine synthesis to promote cell proliferation and tumorigenesis, which was largely abolished by targeting PHGDH with RNA interference, CRISPR/Cas9 KO, or small-molecule PHGDH inhibitors. Furthermore, Parkin expression was inversely correlated with PHGDH expression in human breast cancer and lung cancer. Our results revealed PHGDH ubiquitination by Parkin as a crucial mechanism for PHGDH regulation that contributes to the tumor-suppressive function of Parkin and identified Parkin downregulation as a critical mechanism underlying PHGDH overexpression in cancer.
Air pollution is a risk factor for cardiovascular diseases (CVD), but the underlying biological mechanisms are not well understood.
To determine whether markers related to CVD pathophysiological ...pathways (biomarkers for systemic inflammation and thrombosis, heart rate, and blood pressure) are sensitive to changes in air pollution.
Using a quasi-experimental opportunity offered by greatly restricted air pollution emissions during the Beijing Olympics, we measured pollutants daily and the outcomes listed below in 125 healthy young adults before, during, and after the 2008 Olympics (June 2-October 30). We used linear mixed-effects models to estimate the improvement in outcome levels during the Olympics and the anticipated reversal of outcome levels after pollution controls ended to determine whether changes in outcome levels were associated with changes in pollutant concentrations.
C-reactive protein (CRP), fibrinogen, von Willebrand factor, soluble CD40 ligand (sCD40L), soluble P-selectin (sCD62P) concentrations; white blood cell count (WBC); heart rate; and blood pressure.
Concentrations of particulate and gaseous pollutants decreased substantially (-13% to -60%) from the pre-Olympic period to the during-Olympic period. Using 2-sided tests conducted at the .003 level, we observed statistically significant improvements in sCD62P levels by -34.0% (95% CI, -38.4% to -29.2%; P < .001) from a pre-Olympic mean of 6.29 ng/mL to a during-Olympic mean of 4.16 ng/mL and von Willebrand factor by -13.1% (95% CI, -18.6% to -7.5%; P < .001) from 106.4% to 92.6%. After adjustments for multiple comparisons, changes in the other outcomes were not statistically significant. In the post-Olympic period when pollutant concentrations increased, most outcomes approximated pre-Olympic levels, but only sCD62P and systolic blood pressure were significantly worsened from the during-Olympic period. The fraction of above-detection-limit values for CRP (percentage ≥ 0.3 mg/L) was reduced from 55% in the pre-Olympic period to 46% in the during-Olympic period and reduced further to 36% in the post-Olympic period. Interquartile range increases in pollutant concentrations were consistently associated with statistically significant increases in fibrinogen, von Willebrand factor, heart rate, sCD62P, and sCD40L concentrations.
Changes in air pollution levels during the Beijing Olympics were associated with acute changes in biomarkers of inflammation and thrombosis and measures of cardiovascular physiology in healthy young persons. These findings are of uncertain clinical significance.
Current epidemiological studies report conflicting results for the effect of statin or metformin on pancreatic cancer overall survival. This literature review and meta-analysis summarize the studies ...reporting an association between statin or metformin use and overall survival of pancreatic cancer patients.
We systematically searched for studies about the association between statin or metformin use and pancreatic cancer overall survival in electronic databases (PubMed, ISI Web of Science, MEDLINE, Cochrane, Scopus, Google Scholar). A meta-analysis based on hazard ratios (HRs) and 95% confidence intervals (CIs) was performed using random effect models. Heterogeneity between the studies was examined using I2 statistics, and sensitivity analyses were conducted to assess the robustness of the findings.
Of 116 statin-related articles identified, 6 retrospective cohort studies representing 12,057 patients were included. There was significant heterogeneity between studies. Statin use was associated with improved survival among pancreatic cancer patients (meta-HR = 0.75; 95% CI: 0.59, 0.90; P < 0.001). Of 311 metformin-related articles, 8 retrospective cohort studies and 2 randomized clinical trials, representing 3,042 patients were identified. Metformin use was associated with better overall survival among pancreatic cancer patients (meta-HR = 0.79; 95% CI: 0.70, 0.92, P < 0.001), and significant heterogeneity was observed between studies.
Our findings suggest that the improved survival time of pancreatic cancer patients are associated with statin or metformin use. Due to the multiple sources of heterogeneity of the original studies, these findings should be considered cautiously, and confirmed with larger prospective individual-level studies.
Unprecedented pollution control actions during the Beijing Olympics provided a quasi-experimental opportunity to examine biologic responses to drastic changes in air pollution levels.
To determine ...whether changes in levels of biomarkers reflecting pulmonary inflammation and pulmonary and systemic oxidative stress were associated with changes in air pollution levels in healthy young adults.
We measured fractional exhaled nitric oxide, a number of exhaled breath condensate markers (H(+), nitrite, nitrate, and 8-isoprostane), and urinary 8-hydroxy-2-deoxyguanosine in 125 participants twice in each of the pre- (high pollution), during- (low pollution), and post-Olympic (high pollution) periods. We measured concentrations of air pollutants near where the participants lived and worked. We used mixed-effects models to estimate changes in biomarker levels across the three periods and to examine whether changes in biomarker levels were associated with changes in pollutant concentrations, adjusting for meteorologic parameters.
From the pre- to the during-Olympic period, we observed significant and often large decreases (ranging from -4.5% to -72.5%) in levels of all the biomarkers. From the during-Olympic to the post-Olympic period, we observed significant and larger increases (48-360%) in levels of these same biomarkers. Moreover, increased pollutant concentrations were consistently associated with statistically significant increases in biomarker levels.
These findings support the important role of oxidative stress and that of pulmonary inflammation in mediating air pollution health effects. The findings demonstrate the utility of novel and noninvasive biomarkers in the general population consisting largely of healthy individuals.
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