Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer

Purpose: To determine whether CT texture features can yield prognostic information in addition to conventional prognostic factors in stage III non-small cell lung cancer (NSCLC).Methods: We conducted a retrospective review of 91 patients with stage III NSCLC treated with definitive chemoradiation. All patients received a four-dimensional (4D) CT simulation, where we utilized the average image (average-CT) and an expiratory image (T50-CT), and a diagnostic contrast enhanced CT image (CE-CT). A penalized cox regression model was used for covariate selection and model development. Models incorporating texture features from the 3 image types and clinical factors were compared to models incorporating clinical factors alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Stratification into low-risk and high-risk groups was based on a patient’s predicted outcome being greater or less than the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients. The concordance correlation coefficient (CCC) was used to assess texture feature reproducibility and classification accuracy was used to assess reproducibility of texture features within the context of our models.         Results: Models incorporating both texture and clinical features demonstrated a significant improvement in stratification compared to models using clinical features alone in cross-validated Kaplan-Meier curves in terms of OS (p = 0.046), LRC (p = 0.01), and FFDM (p = 0.005). The average CCC was 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility uncertainties within our model yielded 80.4 (SD = 3.7), 78.3 (SD = 4.0), and 78.8 (SD = 3.9) percent classification accuracy for OS, LRC, and FFDM, respectively.    Conclusion: Pretreatment tumor texture may provide prognostic information in additional to routinely obtained clinical features. Reproducibility of CE-CT appears inferior to average-CT and T50-CT; however model classification accuracy rates of ~80% were still achieved.----------------------Cite this article as: Fried DV, Tucker SL, Zhou S, Liao ZX, Ibbott GS, Court LE.   Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer. Int J Cancer Ther Oncol 2014; 2(2):020223. DOI: 10.14319/ijcto.0202.2

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer

Purpose: To determine whether CT texture features can yield prognostic information in addition to conventional prognostic factors in stage III non-small cell lung cancer (NSCLC).Methods: We conducted a retrospective review of 91 patients with stage III NSCLC treated with definitive chemoradiation. All patients received a four-dimensional (4D) CT simulation, where we utilized the average image (average-CT) and an expiratory image (T50-CT), and a diagnostic contrast enhanced CT image (CE-CT). A penalized cox regression model was used for covariate selection and model development. Models incorporating texture features from the 3 image types and clinical factors were compared to models incorporating clinical factors alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Stratification into low-risk and high-risk groups was based on a patient’s predicted outcome being greater or less than the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients. The concordance correlation coefficient (CCC) was used to assess texture feature reproducibility and classification accuracy was used to assess reproducibility of texture features within the context of our models.         Results: Models incorporating both texture and clinical features demonstrated a significant improvement in stratification compared to models using clinical features alone in cross-validated Kaplan-Meier curves in terms of OS (p = 0.046), LRC (p = 0.01), and FFDM (p = 0.005). The average CCC was 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility uncertainties within our model yielded 80.4 (SD = 3.7), 78.3 (SD = 4.0), and 78.8 (SD = 3.9) percent classification accuracy for OS, LRC, and FFDM, respectively.    Conclusion: Pretreatment tumor texture may provide prognostic information in additional to routinely obtained clinical features. Reproducibility of CE-CT appears inferior to average-CT and T50-CT; however model classification accuracy rates of ~80% were still achieved.----------------------Cite this article as: Fried DV, Tucker SL, Zhou S, Liao ZX, Ibbott GS, Court LE.   Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer. Int J Cancer Ther Oncol 2014; 2(2):020223. DOI: 10.14319/ijcto.0202.23</p

Risk Factors for Hospitalization and Medical Intensive Care Unit (MICU) Admission Among HIV-Infected Veterans

OBJECTIVE: With improved survival of HIV-infected persons on antiretroviral therapy and growing prevalence of non-AIDS diseases, we asked whether the VACS Index, a composite measure of HIV-associated and general organ dysfunction predictive of all-cause mortality, predicts hospitalization and medical intensive care unit (MICU) admission. We also asked whether AIDS and non-AIDS conditions increased risk after accounting for VACS Index score. METHODS: We analyzed data from the Veterans Aging Cohort Study (VACS), a prospective study of HIV-infected Veterans receiving care between 2002–2008. Data were obtained from the electronic medical record, VA administrative databases and patient questionnaires, and were used to identify comorbidities and calculate baseline VACS Index scores. The primary outcome was first hospitalization within 2 years of VACS enrollment. We used multivariable Cox regression to determine risk factors associated with hospitalization and logistic regression to determine risk factors for MICU admission, given hospitalization. RESULTS: 1141/3410 (33.5%) patients were hospitalized within 2 years; 203/1141 (17.8%) included a MICU admission. Median VACS Index scores were 25 (no hospitalization), 34 (hospitalization only) and 51 (MICU). In adjusted analyses, a 5-point increment in VACS Index score was associated with 10% higher risk of hospitalization and MICU admission. In addition to VACS Index score, Hispanic ethnicity, current smoking, hazardous alcohol use, chronic obstructive pulmonary disease, hypertension, diabetes and prior AIDS-defining event predicted hospitalization. Among those hospitalized, VACS Index score, cardiac disease and prior cancer predicted MICU admission. CONCLUSIONS: The VACS Index predicted hospitalization and MICU admission as did current smoking, hazardous alcohol use, and AIDS and certain non-AIDS diagnoses