Publications

CONTEXT

Little is known about the phenotypic and molecular characteristics associated with changes over time in fatigue and lack of energy in patients with breast cancer.

OBJECTIVES

The aim of this study was to identify subgroups (i.e., latent classes) of women with distinct fatigue and energy trajectories; evaluate for differences in phenotypic characteristics between the latent classes for fatigue and energy; and evaluate for associations between polymorphisms in genes for pro- and anti-inflammatory cytokines, their receptors, and their transcriptional regulators and latent class membership.

METHODS

Patients were enrolled before and followed for six months after breast cancer surgery. Latent class analyses were done to identify subgroups of patients with distinct fatigue and energy trajectories. Candidate gene analyses were done to identify cytokine genes associated with these two symptoms.

RESULTS

For both fatigue and lack of energy, two distinct latent classes were identified. Phenotypic characteristics associated with the higher fatigue class were younger age, higher education, lower Karnofsky Performance Status score, higher comorbidity, higher number of lymph nodes removed, and receipt of chemotherapy (CTX). Polymorphisms in interleukin (IL) 1β and IL10 were associated with membership in the higher fatigue class. Phenotypic characteristics associated with the lower energy class included: a lower Karnofsky Performance Status score and a higher comorbidity score. A polymorphism in IL1R1 was associated with membership in the lower energy class.

CONCLUSION

Within each latent class, the severity of fatigue and decrements in energy were relatively stable over the first six months after breast cancer surgery. Distinct phenotypic characteristics and genetic polymorphisms were associated with membership in the higher fatigue and lower energy classes.

OBJECTIVES

Primary objective: to use advanced nonparametric techniques to determine risk factors for readmission after colorectal cancer surgery in elderly adults.

SECONDARY OBJECTIVE

to compare this methodology with traditional parametric methods.

DESIGN

Using data from the American College of Surgeons National Surgical Quality Improvement Program (NSQIP), nonparametric techniques were used to evaluate the risk of readmission in elderly adults undergoing surgery for colorectal cancer in 2011 and 2012.

SETTING

More than 200 hospitals participating in the NSQIP database.

PARTICIPANTS

Individuals aged 65 and older who underwent surgery for colorectal cancer in 2011 and 2012 (N = 2,117).

MEASUREMENTS

Age-stratified robust nonparametric predictive model (classification and regression tree (CART) analysis) of 30-day readmission for elderly adults undergoing surgery for colorectal cancer.

RESULTS

Recent chemotherapy was the most important predictor of readmission in participants aged 65 to 74, with 20% of those with recent chemotherapy and 11% of with no recent chemotherapy being readmitted. Participants aged 75 to 84 who had recently undergone chemotherapy had a readmission rate of 23%, whereas those with no chemotherapy had a readmission rate of 9%. Being underweight was the greatest predictor of readmission (30%) in participants aged 85 and older. These methods were found to be more robust than traditional logistic regression.

CONCLUSION

Specific age-related preoperative factors help predict readmission in elderly adults undergoing colorectal cancer surgery. Results of the nonparametric CART analysis are better than traditional regression analysis and help physicians to clinically stratify based on age. This model may help identify individuals in whom intervention may be helpful in reducing readmission after surgery.

New therapeutic approaches are urgently needed to improve survival outcomes for patients with necrotizing pneumonia caused by Staphylococcus aureus One such approach is adjunctive treatment with intravenous immunoglobulin (IVIG), but clinical practice guidelines offer conflicting recommendations. In a preclinical rabbit model, prophylaxis with IVIG conferred protection against necrotizing pneumonia caused by five different epidemic strains of community-associated methicillin-resistant S. aureus (MRSA) as well as a widespread strain of hospital-associated MRSA. Treatment with IVIG, either alone or in combination with vancomycin or linezolid, improved survival outcomes in this rabbit model. Two specific IVIG antibodies that neutralized the toxic effects of α-hemolysin (Hla) and Panton-Valentine leukocidin (PVL) conferred protection against necrotizing pneumonia in the rabbit model. This mechanism of action of IVIG was uncovered by analyzing loss-of-function mutant bacterial strains containing deletions in 17 genes encoding staphylococcal exotoxins, which revealed only Hla and PVL as having an impact on necrotizing pneumonia. These results demonstrate the potential clinical utility of IVIG in the treatment of severe pneumonia induced by S. aureus.