Survival analysis

Incidence and Risk Profiles for Suicide Mortality in Patients With Schizophrenia Receiving Homecare Case Management in Taiwan

Case management (CM)-based community therapy for patients with schizophrenia had little effect on reducing suicide mortality. We investigate the long-term suicide mortality outcome and associated risk factors in patients with schizophrenia receiving homecare (CM) in Taiwan. We enrolled a nationwide cohort of patients with schizophrenia who newly received homecare CM intervention (n = 13 317) between January 1, 2001, and December 31, 2015; their data were derived from Taiwan's National Health Insurance Research Database. We calculated the incidence rate of suicide methods. We examined the demographic and medical utilization profile for suicide and then performed a nested case-control study and multivariate regression to identify independent risk factors for suicide mortality. Among the 13 317 patients who received homecare CM intervention, 1766 died during the study period, of whom 213 died by suicide, which is the leading cause of unnatural death. Jumping from a high place, self-poisoning, and hanging were the top 3 suicide methods. Increased medical utilization was noted for both psychiatric and non-psychiatric services within 3 months of suicide mortality. Comorbidities of depressive disorder, nonspecific heart diseases, pneumonia, and gastrointestinal ulcers were identified as independent risk factors for suicide mortality. Suicide was the leading cause of unnatural mortality in patients with schizophrenia receiving homecare CM intervention in Taiwan. We noted the preferred suicide methods, high medical utilization, and comorbidities before suicide. Thus, we suggest that the CM team should assess lethal methods for suicide and ensure that patients adhere to psychiatry treatment for improving the current care model for this specified population.

Risk Assessment of Pulmonary Metastasis for Cervical Cancer Patients by Ensemble Learning Models: A Large Population Based Real-World Study

Objective

Pulmonary metastasis (PM) is an independent risk factor affecting the prognosis of cervical patients, but it still lacks a prediction. This study aimed to develop machine learning-based predictive models for PM.

Methods

A total of 22,766 patients diagnosed with or without PM from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in this study. The cohort was randomly split into a train set (70%) and a validation set (30%). In addition, 884 Chinese patients from two tertiary medical centers were included as an external validation set. Duplicated and useless candidate variables were excluded, and sixteen variables were included for the machine learning algorithm. We developed five predictive models, including the generalized linear model (GLM), random forest model (RFM), naive Bayesian model (NBM), artificial neural networks model (ANNM), and decision tree model (DTM). The predictive performance of these models was evaluated by the receiver operating characteristic (ROC) curve and calibration curve. The Cox proportional hazard model (CPHM) and competing risk model (CRM) were also included for survival outcome prediction.

Results

Of the patients included in the analysis, 2456 (4.38%) patients were diagnosed with PM. Age, organ-site metastasis (liver, bone, brain), distant lymph metastasis, tumor size, and pathology were the important predictors of PM. The RFM with 9 variables introduced was identified as the best predictive model for PM (AUC = 0.972, 95% CI: 0.958-0.986). The C-index for the CPHM and CRM was 0.626 (95% CI: 0.604-0.648) and 0.611 (95% CI: 0.586-0.636), respectively.

Conclusion

The prediction algorithm derived by machine-learning-based methods shows a robust ability to predict PM. This result suggests that machine learning techniques have the potential to improve the development and validation of predictive modeling in cervical patients with PM.

Methods to Determine the Role of Autophagy Proteins in C. elegans Aging

This chapter describes methods for the analysis of autophagy proteins in C. elegans aging. We discuss the strains to be considered, the methods for the delivery of double-stranded RNA, and the methods to measure autophagy levels, autophagic flux, and degradation by autophagy.

Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies

PURPOSE

Cancer is a manifestation of aberrant cellular proliferation, and the cell cycle is one of the most successfully drugged targets in oncology. No prior study has been reported that simultaneously targets the 3 principal cell cycle phases populated by proliferating cells--G1, S, and G2/M.

METHODS

Temsirolimus (G1 inhibitor), topotecan (S inhibitor), and bortezomib (G2/M inhibitor) were administered in combination to patients with advanced malignancies using a 3+3 dose escalation schedule to assess the safety and establish the maximum tolerated dose (primary endpoints) of this cell cycle targeting approach. An in silico pharmacodynamic model using established effects of each of these agents on the cell cycle was used to validate the regimen and to guide the dosing regimen.

RESULTS

Sixty-two subjects were enrolled. The most common adverse events and dose-limiting toxicities were cytopenias, consistent with the cell cycle targeting approach employed. All cytopenias resolved to baseline values upon holding study drug administration. The maximum tolerated dose was temsirolimus 15 mg/kg IV D1, 8, 15; topotecan 2.8 mg/m(2) IV D1, 8; and bortezomib 0.6 mg/m2 IV D1, 4, 8, 11 [DOSAGE ERROR CORRECTED] of a 21-day cycle. In silico modeling suggests the regimen induces cell population shifts from G2/M and S phases to G1 phase and the quiescent G0 phase. Eighteen percent of subjects (11/62) achieved partial response (n = 2, serous ovarian and papillary thyroid) or stable disease for > 6 months (n = 9).

CONCLUSION

Combining drugs with inhibitory activity of G1 phase, S phase, and G2/M phase is safe and warrants further evaluation.

Concurrent chemoradiotherapy plus adjuvant chemotherapy versus concurrent chemoradiotherapy in locoregionally advanced nasopharyngeal carcinoma : A matched-pair multicenter analysis of outcomes

PURPOSE

The benefit of adjuvant chemotherapy (AC) in locoregionally advanced nasopharyngeal carcinoma (NPC) is controversial. This study compared concurrent chemoradiotherapy plus AC (CCRT/AC) with CCRT.

METHODS

Pair-matched analysis based on eight clinicopathological features of 244 patients treated with platinum-based CCRT/AC or CCRT alone was performed. Survival outcomes were assessed using the Kaplan-Meier method and log-rank test. Toxicities and response rates were compared using Fisher's exact test.

RESULTS

Four-year overall survival, progression-free survival, distant failure-free survival, and locoregional failure-free survival were 72 %, 61 %, 71 %, and 81 %, respectively, for the CCRT arm, compared to 74 % (hazard ratio, HR 0.89; 95 % confidence interval, CI 0.64-1.23; P = 0.474), 62 % (HR 0.91, 95 % CI 0.68-1.20, P = 0.489), 73 % (HR 0.84, 95 % CI 0.59-1.18, P = 0.316), and 84 % (HR 0.84, 95 % CI 0.52-1.24, P = 0.323), respectively, for the CCRT/AC arm. Cox multivariate regression analysis demonstrated AC was not an independent prognostic factor. Overall, there was a higher incidence of grade 3-4 toxicities in the CCRT/AC arm. The most common grade 3-4 adverse events in the CCRT/AC arm were vomiting (27 %), nausea (43 %), leukopenia/neutropenia (23 %), thrombocytopenia (8.8 %), and anemia (6.2 %).

CONCLUSION

Addition of AC to CCRT increased toxicities but did not improve survival in locoregionally advanced NPC.

Advanced colorectal adenomas in patients under 45 years of age are mostly sporadic

BACKGROUND

The presence of advanced adenomas in younger individuals is a criterion for Lynch syndrome (LS). However, the utility of screening advanced adenomas for loss of mismatch repair (MMR) protein expression to identify suspected LS remains unclear.

AIMS

Determine the prevalence of MMR defects to understand whether these patients harbor a defined genetic risk for CRC.

METHODS

The study cohort included adult patients ≤45 years of age with advanced adenomas (villous histology, ≥1 cm in diameter, ≥3 polyps of any size) endoscopically removed between 2001 and 2011. Clinical records were reviewed along with detailed pathological review and immunohistochemical MMR analysis.

RESULTS

A total of 76 (40.1 % male, age 40.6 ± 5.4 years) patients met inclusion and exclusion criteria. Indications for colonoscopy were gastrointestinal (GI) bleeding 39 (51.3 %), CRC in a first-degree relative 17 (22.4 %) and somatic GI symptoms 20 (26.3 %). Index colonoscopy revealed a median of 1 adenoma (range 1-4), mean diameter of 12.9 ± 7.1 mm, 40 (52.6 %) with villous histology. The mean follow-up duration was 3.3 ± 2 years. Recurrent adenomas developed in 24 (31.6 %), of which 8 (10.5 %) were advanced adenomas; none of these patients developed CRC. One of 66 (1.5 %) adenomas available for immunohistochemical (IHC) testing revealed loss of MLH1 and PMS2.

CONCLUSIONS

IHC screening of advanced adenomas from patients younger than 45 years of age identified potential LS in one of 64 patients. The low yield of IHC screening in this population suggests that universal IHC screening of advanced adenomas from patients younger than 45 years of age for MMR defects is not an efficient strategy for identifying LS subjects.

Change in tumor size by RECIST correlates linearly with overall survival in phase I oncology studies

PURPOSE

RECIST is used to quantify tumor changes during exposure to anticancer agents. Responses are categorized as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). Clinical trials dictate a patient's management options based on the category into which his or her response falls. However, the association between response and survival is not well studied in the early trial setting.

PATIENTS AND METHODS

To study the correlation between response as quantified by RECIST and overall survival (OS, the gold-standard survival outcome), we analyzed 570 participants of 24 phase I trials conducted between October 2004 and May 2009, of whom 468 had quantifiable changes in tumor size. Analyses of Kaplan-Meier estimates of OS by response and null Martingale residuals of Cox models were the primary outcome measures. All analyses are landmark analyses.

RESULTS

Kaplan-Meier analyses revealed strong associations between change in tumor size by RECIST and survival (P = 4.5 × 10(-6) to < 1 × 10(-8)). The relationship was found to be near-linear (R(2) = 0.75 to 0.92) and confirmed by the residual analyses. No clear inflection points were found to exist in the relationship between tumor size changes and survival.

CONCLUSION

RECIST quantification of response correlates with survival, validating RECIST's use in phase I trials. However, the lack of apparent boundary values in the relationship between change in tumor size and OS demonstrates the arbitrary nature of the CR/PR/SD/PD categories and questions emphasis placed on this categorization scheme. Describing tumor responses as a continuous variable may be more informative than reporting categoric responses when evaluating novel anticancer therapies.

Analysis of aging in Caenorhabditis elegans

This chapter is dedicated to the study of aging in Caenorhabditis elegans (C. elegans). The assays are divided into two sections. In the first section, we describe detailed protocols for performing life span analysis in solid and liquid medium. In the second section, we describe various assays for measuring age-related changes. Our laboratory has been involved in several fruitful collaborations with non-C. elegans researchers keen on testing a role for their favorite gene in modulating aging (Carrano et al., 2009; Dong et al., 2007; Raices et al., 2008; Wolff et al., 2006). But even with the guidance of trained worm biologists, this undertaking can be daunting. We hope that this chapter will serve as a worthy compendium for those researchers who may or may not have immediate access to laboratories studying C. elegans.

Statistical Optimization of Pharmacogenomics Association Studies: Key Considerations from Study Design to Analysis

Research in human genetics and genetic epidemiology has grown significantly over the previous decade, particularly in the field of pharmacogenomics. Pharmacogenomics presents an opportunity for rapid translation of associated genetic polymorphisms into diagnostic measures or tests to guide therapy as part of a move towards personalized medicine. Expansion in genotyping technology has cleared the way for widespread use of whole-genome genotyping in the effort to identify novel biology and new genetic markers associated with pharmacokinetic and pharmacodynamic endpoints. With new technology and methodology regularly becoming available for use in genetic studies, a discussion on the application of such tools becomes necessary. In particular, quality control criteria have evolved with the use of GWAS as we have come to understand potential systematic errors which can be introduced into the data during genotyping. There have been several replicated pharmacogenomic associations, some of which have moved to the clinic to enact change in treatment decisions. These examples of translation illustrate the strength of evidence necessary to successfully and effectively translate a genetic discovery. In this review, the design of pharmacogenomic association studies is examined with the goal of optimizing the impact and utility of this research. Issues of ascertainment, genotyping, quality control, analysis and interpretation are considered.

Phase I oncology studies: evidence that in the era of targeted therapies patients on lower doses do not fare worse

PURPOSE

To safely assess new drugs, cancer patients in initial cohorts of phase I oncology studies receive low drug doses. Doses are successively increased until the maximum tolerated dose (MTD) is determined. Because traditional chemotherapy is often more effective near the MTD, ethical concerns have been raised about administration of low drug doses to phase I patients. However, a substantial portion of oncology trials now investigate targeted agents, which may have different dose-response relationships than cytotoxic chemotherapies.

EXPERIMENTAL DESIGN

Twenty-four consecutive trials treating 683 patients between October 1, 2004, and June 30, 2008, at MD Anderson Cancer Center were analyzed. Patients were assigned to a low-dose (<or=25% MTD), medium-dose (25-75% MTD), or high-dose (>or=75% MTD) group, and groups were compared for response rate, time-to-treatment failure, progression-free survival, overall survival, and toxicity. To remove negatively biasing data from the high-dose group, in a second analysis, patients treated above the MTD were excluded (high-dose group, 75-100% MTD). Of the 683 patients, 97.7% received targeted agents.

RESULTS

Even when excluding patients above the MTD, there was an early trend favoring the low- versus high-dose group in time-to-treatment failure, with 32.9% versus 25.2% of patients on therapy at 3 months (P = 0.08). In addition, the low-dose group fared at least as well as the other groups in all other outcomes, including response rate, progression-free survival, overall survival, and toxicity.

CONCLUSIONS

These data may help alleviate concerns that patients who receive low drug doses on contemporary phase I oncology trials fare worse and suggest targeted agents may have different dose-response relationships than cytotoxic chemotherapies.