Comparison of Adjuvant Therapies Using Quality-Of-Life Considerations

The benefit for patients with operable breast cancer treated with adjuvant systemic therapy is small, if reduction of early mortality within the context of randomized control trials is used for treatment comparison. One might consider that the 75%-85% of patients who die despite treatment are overtreated, as are patients who remain alive even without therapy within a given time frame. Larger treatment benefits in terms of avoided or delayed breast cancer relapse have been demonstrated even at early phases of follow-up in the vast majority of adjuvant trials. Exposure of all patients to adjuvant therapy at a time at which no symptoms of disease are present is detrimental in terms of quality of life. Based on our assumption that the quality of life of the patient is typically altered both by subjective toxic effects of adjuvant treatment and by the appearance of relapse, we developed a method of comparing treatment effects in terms of time without symptoms of disease and toxicity of treatment (TWiST). Because the impact of treatment on relapse rates appears earlier than survival effects in all adjuvant therapy trials, and because the value of time without relapse in terms of the quality of life of the patients is as yet poorly defined, we have generalized our method of comparing treatment attitudes to include individual qualitative judgment values. The experience gained from integrating quality-of-life issues into clinical trials for breast cancer might also be applied to other diseases characterized by a chronic course, toxic treatments, and gains in periods of relative or absolute freedom from toxic effects and progressive diseas

Systemic treatments for women with breast cancer: outcome with relation to screening for the disease

Early detection and proper care of breast cancer are currently the best available approaches to the treatment of patients with the disease. In countries with a breast cancer screening programme, there has been a demonstrated reduction in breast cancer-related mortality. Such reduction has also been observed in Switzerland, a country in which no national programme of screening is available. Although there is no doubt that early diagnosis might have had a major role in reducing breast cancer mortality the magnitude of this effect is unknown. Research with tailored approaches on alternative imaging for early detection of breast cancer in high-risk women and on treatments offered according to proper criteria of responsiveness to therapies is warrante

New treatments for breast cancer: Breakthroughs for patient care or just steps in the right direction?

Three areas of clinical research in breast cancer treatment led to news breaking presentations at the American Society of Clinical Oncology (ASCO) meeting, 1998, in Los Angeles. All three subjects represent important advances in cancer medicine. Prevention: Two related drugs, tamoxifen and raloxifene, were found in placebo controlled trials to significantly reduce the incidence of breast cancer for women at increased risk of developing the disease. Patterns of relapse showed that the reduced rate of breast cancer was exclusively observed for tumors expressing estrogen receptors, while the rate of tumors classified as estrogen-receptor negative was similar for the treatment and the control groups. This may indicate that the observed reduction in breast cancer incidence is due to a treatment effect on occult disease rather than its prevention. We certainly have no adequate information on mortality prevention. Adjuvant therapies: Taxol given every three weeks for four courses following an adjuvant treatment with four courses of doxorubicin and cyclophosphamide (AC) combination was found to be superior to not adding treatment after the four courses of AC in a trial involving 3170 patients. At 22 months of median follow-up, the quoted P-values were P = 0.0077 for disease-free survival and P = 0.039 for overall survival, but these did not cross the prospectively defined interim analysis boundaries for statistical significance at the 0.05 level. The difference was observed early during follow-up, and was exclusively seen in the 40% of patients who had ER-negative primaries and, therefore, did not receive tamoxifen following chemotherapy. One may thus argue that the early difference observed was primarily due to differences in the duration of the treatment regimens in the two groups and the early entry into the trial of patients with particularly aggressive neoplasia (e.g., ER-negative primaries) who would have benefited from a longer duration treatment. Treatment of advanced disease: The use of monoclonal antibodies to c-erb-B2 was found to induce responses in metastatic breast cancer. Patients with tumors expressing c-erb-B2 responded to weekly infusions of this biological agent. It was particularly impressive that the response rate for patients receiving infusion of the monoclonal antibodies together with the cytotoxics was superior to that with chemotherapy alone in a randomized trial. It is important to note that only patients with tumors overexpressing c-erbB-2 (the overall incidence is about 20%) were tested. It must still be demonstrated that the effect of these monoclonal antibodies is indeed confined to cells overexpressing c-erbB-2. Treatment related cardiac tox-icity remains a problem, and the effects of treatment in various subsets of patients need to be defined before starting investigations in the adjuvant setting, which is a clear further objective of this specific research. The significant findings from clinical research opened several new questions, which must be answered before allowing them to be employed in routine patient car

Temperature And Lifetime Measurements In The SSX Wind Tunnel

We describe ion and electron temperature measurements in the Swarthmore Spheromak Experiment (SSX) MHD wind tunnel with the goal of understanding limitations on the lifetime of our Taylor-state plasma. A simple model based on the equilibrium eigenvalue and Spitzer resistivity predicted the lifetime satisfactorily during the first phase of the plasma evolution. We measured an average Tₑ along a chord by taking the ratio of the CIII97.7 nm to CIV155 nm line intensities using a vacuum ultraviolet (VUV) monochromator. We also recorded local measurements of Tₑ and nₑ using a double Langmuir probe in order to inform our interpretation of the VUV data. Our results indicated that the plasma decayed inductively during a large part of the evolution. Ion Doppler spectroscopy measurements suggested that ions cooled more slowly than would be expected from thermal equilibration with the electrons, which maintained a constant temperature throughout the lifetime of the plasma

Subpopulation Treatment Effect Pattern Plot (STEPP) Methods with R and Stata

We introduce the stepp packages for R and Stata that implement the subpopulation treatment effect pattern plot (STEPP) method. STEPP is a nonparametric graphical tool aimed at examining possible heterogeneous treatment effects in subpopulations defined on a continuous covariate or composite score. More pecifically, STEPP considers overlapping subpopulations defined with respect to a continuous covariate (or risk index) and it estimates a treatment effect for each subpopulation. It also produces confidence regions and tests for treatment effect heterogeneity among the subpopulations. The original method has been extended in different directions such as different survival contexts, outcome types, or more efficient procedures for identifying the overlapping subpopulations. In this paper, we also introduce a novel method to determine the number of subjects within the subpopulations by minimizing the variability of the sizes of the subpopulations generated by a specific parameter combination. We illustrate the packages using both synthetic data and publicly available data sets. The most intensive computations in R are implemented in Fortran, while the Stata version exploits the powerful Mata language

The effect of endocrine responsiveness on high-risk breast cancer treated with dose-intensive chemotherapy: results of International Breast Cancer Study Group Trial 15-95 after prolonged follow-up

Background: The role of adjuvant dose-intensive chemotherapy and its efficacy according to baseline features has not yet been established. Patients and methods: Three hundred and forty-four patients were randomized to receive seven courses of standard-dose chemotherapy (SD-CT) or three cycles of dose-intensive epirubicin and cyclophosphamide (epirubicin 200 mg/m2 plus cyclophosphamide 4 mg/m2 with filgrastim and progenitor cell support). All patients were assigned tamoxifen at the completion of chemotherapy. The primary end point was disease-free survival (DFS). This paper updates the results and explores patterns of recurrence according to predicting baseline features. Results: At 8.3-years median follow-up, patients assigned DI-EC had a significantly better DFS compared with those assigned SD-CT [8-year DFS percent 47% and 37%, respectively, hazard ratio (HR) 0.76; 95% confidence interval 0.58-1.00; P = 0.05]. Only patients with estrogen receptor (ER)-positive disease benefited from the DI-EC (HR 0.61; 95% confidence interval 0.39, 0.95; P = 0.03). Conclusions: After prolonged follow-up, DI-EC significantly improved DFS, but the effect was observed only in patients with ER-positive disease, leading to the hypothesis that efficacy of DI-EC may relate to its endocrine effects. Further studies designed to confirm the importance of endocrine responsiveness in patients treated with dose-intensive chemotherapy are encourage

Subpopulation Treatment Effect Pattern Plot (STEPP) methods with R and Stata

We introduce the stepp packages for R and Stata that implement the subpopulation treatment effect pattern plot (STEPP) method. STEPP is a nonparametric graphical tool aimed at examin- ing possible heterogeneous treatment effects in subpopulations defined on a continuous covariate or composite score. More pecifically, STEPP considers overlapping subpopulations defined with respect to a continuous covariate (or risk index) and it estimates a treatment effect for each subpopulation. It also produces confidence regions and tests for treatment effect heterogeneity among the subpopulations. The original method has been extended in different directions such as different survival contexts, outcome types, or more efficient procedures for identifying the overlapping subpopulations. In this paper, we also introduce a novel method to determine the number of subjects within the subpopulations by minimizing the variability of the sizes of the subpopulations generated by a specific parameter combination. We illustrate the packages using both synthetic data and publicly available data sets. The most intensive computations in R are implemented in Fortran, while the Stata version exploits the powerful Mata language