Citations

Object Obesity as a consequence of management of pediatric craniopharyngioma is a well-described phenomenon related to the degree of hypothalamic involvement. However, weight change and obesity have not been analyzed in adult patients. Therefore, the purpose of this study was 1) to evaluate the pattern of postoperative weight gain related to preoperative body mass index (BMI), 2) determine if postoperative weight gain is an issue in adult patients, and 3) develop an objective MR imaging grading system to predict risk of postoperative weight gain and obesity in adults treated for craniopharyngioma. Methods The authors retrospectively screened 296 patients with known craniopharyngioma for the following inclusion criteria: pathologically confirmed craniopharyngioma, index surgery at the authors' institution, and operative weight and height recorded with at least 3 months of follow-up including body weight measurement. Patients aged 18 years or younger were excluded, yielding 28 cases for analysis. Cases of craniopharyngiomas were compared with age- and sex-matched controls (pituitary adenoma patients) to evaluate the pattern and significance of perioperative weight changes. Results Mean age was 46 ± 17 years at surgery, and 64% of the patients were male. Complete resection was achieved in 71% of cases. There was no correlation of preoperative BMI and postoperative weight gain testing in a linear model. Sixty-one percent and 46% of patients had postoperative weight gains greater than 4 and 9%, respectively. Comparing craniopharyngioma patients (cases) to age- and sex-matched controls, the preoperative BMIs were similar (p = 0.93) between cases (mean 28.9 [95% CI 30.9–26.9]) and controls (mean 29.3 [95% CI 31.9–26.7]). However, there was a trend to a greater mean postoperative weight change (percentage) in cases (10.1%) than in controls (5.6%) (p = 0.24). Hypothalamic T2 signal change and irregular contrast enhancement correlated and predicted higher-grade hypothalamic involvement. Furthermore, they can be used to objectively grade hypothalamic involvement as the authors propose. Progressive hypothalamic involvement correlated with larger postoperative weight gains (p = 0.022); however, hypothalamic involvement did not correlate with preoperative BMI (p = 0.5). Conclusions Postoperative weight gain in adult patients undergoing surgery for craniopharyngioma is a significant problem and correlates with hypothalamic involvement, as it does in pediatric patients. Finally, objective MR imaging criteria can be used to predict risk of postoperative weight gain and aid in grading of hypothalamic involvement.

Multiple methods have been proposed to characterize the viscoelastic material properties of soft tissues to differentiate normal from pathological tissue. Shearwave dispersion ultrasound vibrometry is a method that uses the dispersion of the shear wave velocity to characterize tissue shear elasticity and viscosity. It has recently been shown [M. W. Urban and J. F. Greenleaf, Phys. Med. Biol. 54, 5919–5933 (2009)] that the Kramers–Kronig relationships can be applied to shear wave measurements in ex vivo skeletal muscle over a frequency bandwidth of 100–600 Hz. We will describe this process where shear wave attenuation is modeled using a power law, and the shear wave velocity dispersion is predicted by applying the Kramers–Kronig relationships. In this study, we apply this method to shear wave propagation measurements made in different soft tissues such as ex vivo porcine skeletal muscle and kidney and in vivo porcine liver. The shear wave velocity predictions using the Kramers–Kronig relationships agree with the velocity measurements. The mean square error for these tissues ranged from 0.0024–0.0625 m2/s2. The Kramers–Kronig relationships can be used in shear wave propagation measurements in different types of soft tissues. [This work was supported in part by NIH Grants Nos. EB002167 and DK082408.]

Stiff skin syndrome, an autosomal dominant congenital form of scleroderma, is caused by mutations in the domain of fibrillin-1 that mediates integrin binding.

Abstract The need to practice evidence-based medicine is the current prevailing paradigm within the medical community. Evidence to guide practice can and should come from a variety of sources, including clinical trials, observational studies, and meta-analyses of both or either. This paper discusses the relative strengths and weaknesses of data that arise from these various sources. The different types of evidence required to demonstrate “efficacy” versus “effectiveness,” a critical and often overlooked distinction, are discussed. In the genomic age, in which targeted therapies with or without specific biomarkers are emerging in cancer care, new approaches are necessary to generate the evidence required for decision making.

Abstract The optimal design of phase II studies continues to be the subject of vigorous debate, especially studies of newer molecularly targeted agents. The observations that many new therapeutics “fail” in definitive phase III studies, coupled with the numbers of new agents to be tested as well as the increasing costs and complexity of clinical trials, further emphasize the critical importance of robust and efficient phase II design. The Clinical Trial Design Task Force (CTD-TF) of the National Cancer Institute (NCI) Investigational Drug Steering Committee (IDSC) has published a series of discussion papers on phase II trial design in Clinical Cancer Research. The IDSC has developed formal recommendations about aspects of phase II trial design that are the subject of frequent debate, such as endpoints (response versus progression-free survival), randomization (single-arm designs versus randomization), inclusion of biomarkers, biomarker-based patient enrichment strategies, and statistical design (e.g., two-stage designs versus multiple-group adaptive designs). Although these recommendations in general encourage the use of progression-free survival as the primary endpoint, randomization, inclusion of biomarkers, and incorporation of newer designs, we acknowledge that objective response as an endpoint and single-arm designs remain relevant in certain situations. The design of any clinical trial should always be carefully evaluated and justified based on characteristic specific to the situation. Clin Cancer Res; 16(6); 1764–9

AbstractPurpose: Obesity is associated with an increased risk of colon cancer. However, the influence of body mass index (BMI) on the prognosis of colon cancer survivors and its relationship to gender remains unknown.Experimental Design: BMI (kg/m2) was categorized in patients with tumor-node-metastasis stage II and III colon carcinomas (n = 4,381) enrolled in seven randomized trials of 5-fluorouracil–based adjuvant chemotherapy. Cox proportional hazards models were used to determine the association of BMI with disease-free survival (DFS) and overall survival (OS).Results: Among colon cancer patients, 868 (20%) were obese (BMI, ≥30 kg/m2), of which 606 were class 1 (BMI, 30-34 kg/m2) and 262 were class 2,3 (BMI, ≥35 kg/m2). Obese versus normal-weight patients were more likely to be younger, have distal tumors, show intact DNA mismatch repair, and have more lymph node metastases (P < 0.017). In a multivariate analysis, BMI was significantly associated with both DFS (P = 0.030) and OS (P = 0.0017). Men with class 2,3 obesity showed reduced OS compared with normal-weight men [hazard ratio, 1.35; 95% confidence interval, 1.02-1.79; P = 0.039]. Women with class I obesity had reduced OS [hazard ratio, 1.24; 95% confidence interval, 1.01-1.53; P = 0.045] compared with normal-weight women. Overweight status was associated with improved OS in men (P = 0.006), and underweight women had significantly worse OS (P = 0.019). BMI was not predictive of therapeutic benefit.Conclusions: Obesity is an independent prognostic variable in colon cancer survivors and shows gender-related differences. These data suggest that obesity-related biological factors can influence clinical outcome. Clin Cancer Res; 16(6); 1884–93

Purpose To improve the understanding of the appropriate design of phase II oncology clinical trials, we compared error rates in single-arm, historically controlled and randomized, concurrently controlled designs. Patients and Methods We simulated error rates of both designs separately from individual patient data from a large colorectal cancer phase III trials and statistical models, which take into account random and systematic variation in historical control data. Results In single-arm trials, false-positive error rates (type I error) were 2 to 4 times those projected when modest drift or patient selection effects (eg, 5% absolute shift in control response rate) were included in statistical models. The power of single-arm designs simulated using actual data was highly sensitive to the fraction of patients from treatment centers with high versus low patient volumes, the presence of patient selection effects or temporal drift in response rates, and random small-sample variation in historical controls. Increasing sample size did not correct the over optimism of single-arm studies. Randomized two-arm design conformed to planned error rates. Conclusion Variability in historical control success rates, outcome drifts in patient populations over time, and/or patient selection effects can result in inaccurate false-positive and false-negative error rates in single-arm designs, but leave performance of the randomized two-arm design largely unaffected at the cost of 2 to 4 times the sample size compared with single-arm designs. Given a large enough patient pool, the randomized phase II designs provide a more accurate decision for screening agents before phase III testing.

Purpose To define the maximum tolerated dose, toxicities, pharmacokinetics, and pharmacodynamics of 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17DMAG). Methods 17DMAG was given intravenously over 1 hour daily for 5 days (schedule A) or daily for 3 days (schedule B) every 3 weeks. Plasma 17DMAG concentrations were measured by liquid chromatography/mass spectrometry. Heat-shock proteins (HSPs) and client proteins were evaluated at baseline and after treatment on day 1 in peripheral blood mononuclear cells (PBMCs) and in pre- and post-treatment (24 hours) biopsies done during cycle 1 at the recommended phase II dose (n = 7). Results Fifty-six patients were entered: 26 on schedule A; 30 on schedule B. The recommended phase II doses for schedules A and B were 16 mg/m2 and 25 mg/m2, respectively. Grade 3/4 toxicities included liver function test elevation (14%), pneumonitis (9%), diarrhea (4%), nausea (4%), fatigue (4%) and thrombocytopenia (4%). There were no objective responses. Four patients had stable disease. 17DMAG half-life was 24 ± 15 hours. 17DMAG area under the curve (range, 0.7 to 14.7 mg/mL × h) increased linearly with dose. The median HSP90, HSP70, and integrin-linked kinase levels were 87.5% (n = 14), 124% (n = 20), and 99.5% (n = 20) of baseline. Changes in HSPs and client proteins in tumor biopsies were not consistent between baseline and 24 hours nor did they change in the same direction as those in PBMCs collected at the time of biopsy. Conclusion The recommended phase II doses of 17DMAG (16 mg/m2 × 5 days or 25 mg/m2 × 3 days, every 3 weeks) are well tolerated and suitable for further evaluation.

We examined the association of variation in the type 2 diabetes risk-conferringTCF7L2gene with the risk of incident coronary heart disease (CHD) among the lean, overweight, and obese members of the Atherosclerosis Risk in Communities (ARIC) Study cohort. Cox proportional hazard regression analyses were performed using a general model, with the major homozygote as the reference category. For 9,865 whites, a significant increase in the risk of CHD was seen only among lean (BMI<25 kg/m2) individuals homozygous for theTallele of theTCF7L2rs7903146 gene risk variant (hazard ratio 1.42; 95% CI 1.03,1.97;P=.01). No association was found among 3,631 blacks, regardless of BMI status. An attenuated hazard ratio was observed among the nondiabetic ARIC cohort members. This study suggests that body mass modifies the association of theTCF7L2rs7903146 T allele with CHD risk.