Assessment of osteopontin in early breast cancer: correlative study in a randomised clinical trial.

INTRODUCTION: Osteopontin (OPN) is a malignancy-associated glycoprotein that contributes functionally to tumor aggressiveness. In metastatic breast cancer, we previously demonstrated that elevated OPN in primary tumor and blood was associated with poor prognosis. METHODS: We measured OPN in plasma by ELISA, and in tumors by immunohistochemistry, in 624 (94%) and 462 (69%), respectively, of 667 postmenopausal women with hormone responsive early breast cancer treated by surgery followed by adjuvant treatment with tamoxifen +/- octreotide in a randomized trial (NCIC CTG MA.14; National Cancer Institute of Canada Clinical Trials Group Mammary.14). RESULTS: Plasma OPN was measured in 2,540 samples; 688 at baseline and 1,852 collected during follow-up. Mean baseline plasma OPN was 46 ng/ml (range 22.6 to 290) which did not differ from normal levels. Mean percentage OPN tumor cell positivity was 33.9 (95% CI: 30.2 to 37.9). There was no correlation between plasma and tumor OPN values. In multivariate analysis, neither was associated with event-free survival (EFS), relapse-free survival (RFS), overall survival (OS), bone RFS or non-bone RFS. An exploratory analysis in patients with recurrence showed higher mean OPN plasma levels 60.7 ng/ml (23.9 to 543) in the recurrence period compared with baseline levels. CONCLUSIONS: The hypothesis that OPN tumor expression would have independent prognostic value in early breast cancer was not supported by multivariate analysis of this study population. Plasma OPN levels in women with hormone responsive early breast cancer in the MA.14 trial were not elevated and there was no evidence for prognostic value of plasma OPN in this defined group of patients. However, our finding of elevated mean OPN plasma level around the time of recurrence warrants further study. TRIAL REGISTRATION: NCT00002864, http://clinicaltrials.gov/show/NCT00002864.

Ductal carcinoma in situ of the breast (DCIS) with heterogeneity of nuclear grade: prognostic effects of quantitative nuclear assessment.

BACKGROUND: Previously, 50% of patients with breast ductal carcinoma in situ (DCIS) had more than one nuclear grade, and neither worst nor predominant nuclear grade was significantly associated with development of invasive carcinoma. Here, we used image analysis in addition to histologic evaluation to determine if quantification of nuclear features could provide additional prognostic information and hence impact prognostic assessments. METHODS: Nuclear image features were extracted from about 200 nuclei of each of 80 patients with DCIS who underwent lumpectomy alone, and received no adjuvant systemic therapy. Nuclear images were obtained from 20 representative nuclei per duct, from each of a group of 5 ducts, in two separate fields, for 10 ducts. Reproducibility of image analysis features was determined, as was the ability of features to discriminate between nuclear grades. Patient information was available about clinical factors (age and method of DCIS detection), pathologic factors (DCIS size, nuclear grade, margin size, and amount of parenchymal involvement), and 39 image features (morphology, densitometry, and texture). The prognostic effects of these factors and features on the development of invasive breast cancer were examined with Cox step-wise multivariate regression. RESULTS: Duplicate measurements were similar for 89.7% to 97.4% of assessed image features. For the pooled assessment with approximately 200 nuclei per patient, a discriminant function with one densitometric and two texture features was significantly (p < 0.001) associated with nuclear grading, and provided 78.8% correct jackknifed classification of a patient's nuclear grade. In multivariate assessments, image analysis nuclear features had significant prognostic associations (p

Disease-specific survival for limited-stage small-cell lung cancer affected by statistical method of assessment.

BACKGROUND: In general, prognosis and impact of prognostic/predictive factors are assessed with Kaplan-Meier plots and/or the Cox proportional hazard model. There might be substantive differences from the results using these models for the same patients, if different statistical methods were used, for example, Boag log-normal (cure-rate model), or log-normal survival analysis. METHODS: Cohort of 244 limited-stage small-cell lung cancer patients, were accrued between 1981 and 1998, and followed to the end of 2005. The endpoint was death with or from lung cancer, for disease-specific survival (DSS). DSS at 1-, 3- and 5-years, with 95% confidence limits, are reported for all patients using the Boag, Kaplan-Meier, Cox, and log-normal survival analysis methods. Factors with significant effects on DSS were identified with step-wise forward multivariate Cox and log-normal survival analyses. Then, DSS was ascertained for patients with specific characteristics defined by these factors. RESULTS: The median follow-up of those alive was 9.5 years. The lack of events after 1966 days precluded comparison after 5 years. DSS assessed by the four methods in the full cohort differed by 0-2% at 1 year, 0-12% at 3 years, and 0-1% at 5 years. Log-normal survival analysis indicated DSS of 38% at 3 years, 10-12% higher than with other methods; univariate 95% confidence limits were non-overlapping. Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction significantly impacted DSS. DSS assessed by the Cox and log-normal survival analysis methods for four clinical risk groups differed by 1-6% at 1 year, 15-26% at 3 years, and 0-12% at 5 years; multivariate 95% confidence limits were overlapping in all instances. CONCLUSION: Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction all significantly impacted DSS. Apparent DSS for patients was influenced by the statistical methods of assessment. This would be clinically relevant in the development or improvement of clinical management strategies.