Exposure to nonsteroidal anti-inflammatory drugs and weight loss and hospitalization in non-small cell lung cancer patients

Background. Cancer cachexia is a common syndrome complex in cancer, occurring in nearly 80% of patients with advanced cancer and responsible for at least 20% of all cancer deaths. Cachexia is due to increased resting energy expenditure, increased production of inflammatory mediators, and changes in lipid and protein metabolism. Non-steroidal anti-inflammatory drugs (NSAIDs), by virtue of their anti-inflammatory properties, are possibly protective against cancer-related cachexia. Since cachexia is also associated with increased hospitalizations, this outcome may also show improvement with NSAID exposure. ^ Design. In this retrospective study, computerized records from 700 non-small cell lung cancer patients (NSCLC) were reviewed, and 487 (69.57%) were included in the final analyses. Exclusion criteria were severe chronic obstructive pulmonary disease, significant peripheral edema, class III or IV congestive heart failure, liver failure, other reasons for weight loss, or use of research or anabolic medications. Information on medication history, body weight and hospitalizations was collected from one year pre-diagnosis until three years post-diagnosis. Exposure to NSAIDs was defined if a patient had a history of being treated with NSAIDs for at least 50% of any given year in the observation period. We used t-test and chi-square tests for statistical analyses. ^ Results. Neither the proportion of patients with cachexia (p=0.27) nor the number of hospitalizations (p=0.74) differed among those with a history of NSAID use (n=92) and those without (n=395). ^ Conclusions. In this study, NSAID exposure was not significantly associated with weight loss or hospital admissions in patients with NSCLC. Further studies may be needed to confirm these observations.^

Correlation of blood type with thrombosis in pancreatic cancer patients

Objective: The study aimed to identify the risk factors involved in initiating thromboembolism (TE) in pancreatic cancer (PC) patients, with focus on ABO blood type. ^ Methods and Patients: There were 35.7% confirmed cases of TE and 64.3% cases remained free of TE (n=687). There were 12.7% only Pulmonary embolism (PE), 9% only Deep vein thrombosis (DVT), 53.5% only other sites, 3.3% combined PE and DVT, 8.6% combined PE and other sites, 9.8% combined DVT and other sites, and 3.3% all three combined cases. ^ Results: The risk factors for thrombosis identified by multivariate logistic regression were: history of previous anti-thrombotic treatment, tumor site in pancreatic body or tail, large tumor size, maximum glucose category more than 126 and 200 mg/dL. ^ The factors with worse overall survival by multivariate Cox regression and Kaplan Meier analyses were: locally advanced or metastatic stage, worsening performance status, high CA 19-9 levels, and HbA1C levels more than 6 %, at diagnosis. ^ There were 29.1% and 39.1% of the patients with thrombosis in the O and non-O blood type groups respectively. Both Non-O blood type (P=0.02) and the A, B and AB blood types (P= 0.007) were associated with thrombosis as compared to O type. The odds of thrombosis were nearly half in O blood type patients as compared to non-O blood type [OR-0.54 (95% C.I.- 0.37-0.79), P<0.001]. ^ Conclusion: A better understanding of the TE and PC relationship and involved risk factors may provide insights on tumor biology and patient response to prophylactic anticoagulation therapy.^

THE IMPACT OF FAMILY HISTORY ON MEDULLARY THYROID CANCER IN MEN2A PATIENTS

The American Thyroid Association recently classified all MEN2A-associated codons into increasing risk levels A-C and stated that some patients may delay prophylactic thyroidectomy if certain criteria are met. One criterion is a less aggressive family history of MTC but whether families with the same mutated codon have variable MTC aggressiveness is not well described. We developed several novel measures of MTC aggressiveness and compared families with the same mutated codon to determine if there is significant inter-familial variability. Pedigrees of families with MEN2A were reviewed for codon mutated and proportion of RET mutation carriers with MTC. Individuals with MTC were classified as having local or distant MTC and whether they had progressive MTC. MTC status and age were assessed at diagnosis and most advanced MTC stage. For those without MTC, age was recorded at prophylactic thyroidectomy or last follow-up if the patient did not have a thyroidectomy. For each pedigree, the mean age of members without MTC, with MTC, and the proportion of RET mutation carriers with local or distant and progressive MTC were calculated. We assessed differences in these variables using ANOVA and the Fisher’s exact test. Sufficient data for analysis were available for families with mutated codons 609 (92 patients from 13 families), 618 (41 patients from 7 families), and 634 (152 patients from 13 families). The only significant differences found were the mean age of patients without MTC between families with codon 609 and 618 mutations even after accounting for prophylactic thyroidectomy (p=0.006 and 0.001, respectively), and in the mean age of MTC diagnosis between families with codon 618 and 634 mutations even after accounting for symptomatic presentation (p=0.023 and 0.014, respectively). However, these differences may be explained by generational differences in ascertainment of RET carriers and the availability of genetic testing when the proband initially presented.

Baseline quality of life as a predictor of exercise intervention adherence among endometrial cancer survivors

Background: The objective of this analysis is to test whether baseline quality of life (QOL) measurements, body mass index (BMI) and prior exercise behavior are significantly associated with (1) telephone counseling adherence, and (2) activity at the final assessment, in a physical activity promoting intervention among endometrial cancer survivors.^ Methods: One hundred endometrial cancer survivors not currently meeting physical activity guidelines completed baseline QOL and anthropometric assessments to measure general physical and mental health [Medical Outcomes Survey (SF-36)], sleep patterns and sleep quality [Pittsburgh Sleep Quality Index (PSQI)], perceived stress [Perceived Stress Scale (PSS)], cancer-specific concerns of long-term survivors [Quality of Life in Adult Cancer Survivors (QLACS)], and psychological distress [Brief Symptom Inventory-18 (BSI-18)]. Survivors were counseled by telephone during the 6-month intervention and their completion rate determined their adherence. The primary variables of interest included age, baseline BMI, baseline activity level, time since diagnosis, education, treatment received, and the SF-36 physical and mental component scores.^ Results: Final activity was most closely linked with baseline activity (p<.001) and less invasive surgery, being leaner and older, and experiencing less pain and more vitality. Telephone counseling was also predicted well by baseline activity, working less and having better overall cancer-related functioning.^ Conclusion: Above and beyond the QOL measures, baseline activity was the strongest predictor of both final activity and telephone counseling adherence. While education, surgery treatment type and bodily pain were important predictors for final exercise and employment status and cancer-related quality of life were important predictors for telephone counseling adherence, considering adaptive exercise interventions that focus heavily on engaging inactive participants may be a way to produce better exercise-related outcomes in the endometrial cancer survivor population.^

Shifting the focus: Addressing breast cancer disparities at the health care organization level

The purpose of this study was to understand the scope of breast cancer disparities within the Texas Medical Center. The goal was to increase the awareness of breast cancer disparities at the health care organization level, and to foster the development of organizational interventions to reduce breast cancer disparities. The study seeks to answer the following questions: 1. Are hospitals in the Texas Medical Center implementing interventions to reduce breast cancer disparities? 2. What are their interventions for reducing the effects of non clinical factors on breast cancer treatment disparities? 3. What are their measures for monitoring, continuously improving, and evaluating the success of their interventions? ^ This research project was designed as a mixed methods case study. Quantitative breast cancer data for the years 2000-2009 was obtained from the Texas Cancer Registry (TCR). Qualitative data collection and analysis was done by conducting a total of 20 semi-structured interviews of administrators, physicians and nurses at five hospitals (A, B, C, D and E) in the Texas Medical Center (TMC). For quantitative analysis, the study was limited to early stage breast cancer patients: local and regional. The dependent variable was receipt of standard treatment: Surgery (Yes/No), BCS vs Mastectomy, Chemotherapy (Yes/No) and Radiation after BCS (Yes/No). The main independent variable was race: non-Hispanic White (NHW) , non-Hispanic Black (NHB), and Hispanic. Other covariates included age at diagnosis, diagnosis date, percent poverty, grade, stage, and regional nodes. Multivariate logistic regression was used to test the adjusted association between receipt of standard care and race. Qualitative data was analyzed with the Atlas.ti7 software (ATLAS.ti GmbH, Berlin). ^ Though there were significant differences by race for all dependent variables when the data was analyzed as a single group of all hospitals; at the level of the individual hospitals the results were not consistent by race/ethnicity across all dependent variables for hospitals A, B, and E. There were no racial differences in adjusted analysis for receipt of chemotherapy for the individual hospitals of interest in this study. For hospitals C and D, no racial disparities in treatment was observed in adjusted multivariable analysis. All organizations in this study were aware of the body of research which shows that there are disparities in breast cancer outcomes for patient population groups. However, qualitative data analysis found that there were differences in interest among hospitals in addressing breast cancer disparities in their patient population groups. Some organizations were actively implementing directed measures to reduce the breast cancer disparity gap in outcomes for patients, and others were not. Despite the differences in levels of interest, quantitative data analysis showed that organizations in the Texas Medical Center were making progress in reducing the burden of breast cancer disparities in the patient populations being served.^

Intensive care unit utilization among patients with cancer at the end of life

Over the last 2 decades, survival rates in critically ill cancer patients have improved. Despite the increase in survival, the intensive care unit (ICU) continues to be a location where end-of-life care takes place. More than 20% of deaths in the United States occur after admission to an ICU, and as baby boomers reach the seventh and eighth decades of their lives, the volume of patients in the ICU is predicted to rise. The aim of this study was to evaluate intensive care unit utilization among patients with cancer who were at the end of life. End of life was defined using decedent and high-risk cohort study designs. The decedent study evaluated characteristics and ICU utilization during the terminal hospital stay among patients who died at The University of Texas MD Anderson Cancer Center during 2003-2007. The high-risk cohort study evaluated characteristics and ICU utilization during the index hospital stay among patients admitted to MD Anderson during 2003-2007 with a high risk of in-hospital mortality. Factors associated with higher ICU utilization in the decedent study included non-local residence, hematologic and non-metastatic solid tumor malignancies, malignancy diagnosed within 2 months, and elective admission to surgical or pediatric services. Having a palliative care consultation on admission was associated with dying in the hospital without ICU services. In the cohort of patients with high risk of in-hospital mortality, patients who went to the ICU were more likely to be younger, male, with newly diagnosed non-metastatic solid tumor or hematologic malignancy, and admitted from the emergency center to one of the surgical services. A palliative care consultation on admission was associated with a decreased likelihood of having an ICU stay. There were no differences in ethnicity, marital status, comorbidities, or insurance status between patients who did and did not utilize ICU services. Inpatient mortality probability models developed for the general population are inadequate in predicting in-hospital mortality for patients with cancer. The following characteristics that differed between the decedent study and high-risk cohort study can be considered in future research to predict risk of in-hospital mortality for patients with cancer: ethnicity, type and stage of malignancy, time since diagnosis, and having advance directives. Identifying those at risk can precipitate discussions in advance to ensure care remains appropriate and in accordance with the wishes of the patient and family.^

Study on the effect of metformin in patients of metastatic renal cell cancer with diabetes receiving tyrosine kinase inhibitor therapy

Objective: The primary objective of our study was to study the effect of metformin in patients of metastatic renal cell cancer (mRCC) and diabetes who are on treatment with frontline therapy of tyrosine kinase inhibitors. The effect of therapy was described in terms of overall survival and progression free survival. Comparisons were made between group of patients receiving metformin versus group of patients receiving insulin in diabetic patients of metastatic renal cancer on frontline therapy. Exploratory analyses were also done comparing non-diabetic patients of metastatic renal cell cancer receiving frontline therapy compared to diabetic patients of metastatic renal cell cancer receiving metformin therapy. ^ Methods: The study design is a retrospective case series to elaborate the response rate of frontline therapy in combination with metformin for mRCC patients with type 2 diabetes mellitus. The cohort was selected from a database, which was generated for assessing the effect of tyrosine kinase inhibitor therapy associated hypertension in metastatic renal cell cancer at MD Anderson Cancer Center. Patients who had been started on frontline therapy for metastatic renal cell carcinoma from all ethnic and racial backgrounds were selected for the study. The exclusion criteria would be of patients who took frontline therapy for less than 3 months or were lost to follow-up. Our exposure variable was treatment with metformin, which comprised of patients who took metformin for the treatment of type 2 diabetes at any time of diagnosis of metastatic renal cell carcinoma. The outcomes assessed were last available follow-up or date of death for the overall survival and date of progression of disease from their radiological reports for time to progression. The response rates were compared by covariates that are known to be strongly associated with renal cell cancer. ^ Results: For our primary analyses between the insulin and metformin group, there were 82 patients, out of which 50 took insulin therapy and 32 took metformin therapy for type 2 diabetes. For our exploratory analysis, we compared 32 diabetic patients on metformin to 146 non-diabetic patients, not on metformin. Baseline characteristics were compared among the population. The time from the start of treatment until the date of progression of renal cell cancer and date of death or last follow-up were estimated for survival analysis. ^ In our primary analyses, there was a significant difference in the time to progression of patients receiving metformin therapy vs insulin therapy, which was also seen in our exploratory analyses. The median time to progression in primary analyses was 1259 days (95% CI: 659-1832 days) in patients on metformin therapy compared to 540 days (95% CI: 350-894) in patients who were receiving insulin therapy (p=0.024). The median time to progression in exploratory analyses was 1259 days (95% CI: 659-1832 days) in patients on metformin therapy compared to 279 days (95% CI: 202-372 days) in non-diabetic group (p-value <0.0001). ^ The median overall survival was 1004 days in metformin group (95% CI: 761-1212 days) compared to 816 days (95%CI: 558-1405 days) in insulin group (p-value<0.91). For the exploratory analyses, the median overall survival was 1004 days in metformin group (95% CI: 761-1212 days) compared to 766 days (95%CI: 649-965 days) in the non-diabetic group (p-value<0.78). Metformin was observed to increase the progression free survival in both the primary and exploratory analyses (HR=0.52 in metformin Vs insulin group and HR=0.36 in metformin Vs non-diabetic group, respectively). ^ Conclusion: In laboratory studies and a few clinical studies metformin has been proven to have dual benefits in patients suffering from cancer and type 2-diabetes via its action on the mammalian target of Rapamycin pathway and effect in decreasing blood sugar by increasing the sensitivity of the insulin receptors to insulin. Several studies in breast cancer patients have documented a beneficial effect (quantified by pathological remission of cancer) of metformin use in patients taking treatment for breast cancer therapy. Combination of metformin therapy in patients taking frontline therapy for renal cell cancer may provide a significant benefit in prolonging the overall survival in patients with metastatic renal cell cancer and diabetes. ^