Multivariate analysis of flow data in breast lesions and validation in a normal clinical setting.

PURPOSE: To improve differentiation between benign and malignant breast lesions by Doppler measurements and to validate results in a normal clinical setting in comparison to study conditions. MATERIALS AND METHODS: Doppler measurements of 458 patients were compared in benign and malignant tumors in a prospective study. In a multivariate analysis a diagnostic score was developed using a logistic regression model and stepwise selection. These results were compared with 272 patients who were examined under routine clinical conditions. RESULTS: Most measurements showed highly significant (p < 0.001) differences between benign and malignant tumors. For each measurement we considered two cut-points to define a diagnostic rule. Despite significant differences, none of the corresponding classification rules exceeded 90 % sensitivity and specificity. Multivariate analysis selected a model including age and the number of arteries and contralateral arteries. Although significant, the last factor barely improved diagnostic accuracy. Therefore, we deleted it from the multivariate model. Based on a simple model including age and the number of tumor arteries, we defined classification rules with high sensitivity and specificity. The RI measurement did not improve the discriminatory power of our score. In the validation study the sensitivity decreased from 89 - 98 % to 58 - 78 % with a specificity of 82 - 92 % vs. 83 - 86 %. CONCLUSION: Color Doppler can be used for breast cancer differentiation. However, in the clinical routine the sensitivity decreases considerably compared with optimized study conditions.

Adding local components to global functions for continuous covariates in multivariable regression modeling.

When global techniques, based on fractional polynomials (FPs), are employed for modeling potentially nonlinear effects of several continuous covariates on a response, accessible model equations are obtained. However, local features might be missed. Therefore, a procedure is introduced, which systematically checks model fits, obtained by the multivariable fractional polynomial (MFP) approach, for overlooked local features. Statistically significant local polynomials are then parsimoniously added. This approach, called MFP + L, is seen to result in an effective control of the Type I error with respect to the addition of local components in a small simulation study with univariate and multivariable settings. Prediction performance is compared with that of a penalized regression spline technique. In a setting unfavorable for FPs, the latter outperforms the MFP approach, if there is much information in the data. However, the addition of local features reduces this performance difference. There is only a small detrimental effect in settings where the MFP approach performs better. In an application example with children's respiratory health data, fits from the spline-based approach indicate many local features, but MFP + L adds only few significant features, which seem to have good support in the data. The proposed approach may be expected to be superior in settings with local features, but retains the good properties of the MFP approach in a large number of settings where global functions are sufficient.

An experimental evaluation of boosting methods for classification.

OBJECTIVES: In clinical medicine, the accuracy achieved by classification rules is often not sufficient to justify their use in daily practice. In order to improve classifiers it has become popular to combine single classification rules into a classification ensemble. Two popular boosting methods will be compared with classical statistical approaches. METHODS: Using data from a clinical study on the diagnosis of breast tumors and by simulation we will compare AdaBoost with gradient boosting ensembles of regression trees. We will also consider a tree approach and logistic regression as traditional competitors. In logistic regression we allow to select non- linear effects by the fractional polynomial approach. Performance of the classifiers will be assessed by estimated misclassification rates and the Brier score. RESULTS: We will show that boosting of simple base classifiers gives classification rules with improved predictive ability. However, the performance of boosting classifiers was not generally superior to the performance of logistic regression. In contrast to the computer-intensive methods the latter are based on classifiers which are much easier to interpret and to use. CONCLUSIONS: In medical applications, the logistic regression model remains a method of choice or, at least, a serious competitor of more sophisticated techniques. Refinement of boosting methods by using optimized number of boosting steps may lead to further improvement.

Radiation therapy and tamoxifen after breast-conserving surgery: updated results of a 2 x 2 randomised clinical trial in patients with low risk of recurrence.

To study the role of radiotherapy and tamoxifen after breast-conserving surgery (BCS) in patients with a favourable prognosis, a clinical trial was initiated by the German Breast Cancer Study Group (GBSG-V). Between 1991 and 1998, 361 patients (pT 1pN0M0, aged 45-75 years, receptor positive, grades I and II) were randomised to radiotherapy (yes/no) and tamoxifen for 2 years (yes/no) in a 2 x 2-factorial design; the exclusion of seven centres (14 patients) left 347 patients for the analysis. First results after a median follow-up of 5.9 years were published. Herein we present updated results after a median follow-up of about 10 years. Hundred and eleven events concerning event-free survival (EFS) have been observed. Since a strong interactive effect between radiotherapy and tamoxifen has been established, the results are presented in terms of the treatment effects for all four treatment groups separately. Mainly due to the presence of local recurrences, the event rate was much higher in the group with BCS only than in the other three groups. No significant difference could be established between the four treatment groups for distant disease-free survival rates (DDFS). Updated results give further evidence that even in patients with a favourable prognosis, the avoidance of radiotherapy and tamoxifen after BCS increases the rate of local recurrences substantially. Rates are about three times higher in the BCS only group. For the two outcomes EFS and DDFS, no important difference could be seen between the three groups with an additional treatment. However, because of the limited sample size with corresponding low power the strength of evidence for such a comparison is weak.

Reporting of prognostic studies of tumour markers: a review of published articles in relation to REMARK guidelines.

BACKGROUND: Poor reporting compromises the reliability and clinical value of prognostic tumour marker studies. We review articles to assess the reporting of patients and events using REMARK guidelines, at the time of guideline publication. METHODS: We sampled 50 prognostic tumour marker studies from higher impact cancer journals between 2006 and 2007. The inclusion criteria were cancer; focus on single biological tumour marker; survival analysis; multivariable analysis; and not gene array or proteomic data. Articles were assessed for the REMARK profile and other REMARK guideline items. We propose a reporting aid, the REMARK profile, motivated by the CONSORT flowchart. RESULTS: In 50 studies assessed for the REMARK profile, the number of eligible patients (56% of articles), excluded patients (54%) and patients in analyses (98%) was reported. Only 50% of articles reported the number of outcome events. In multivariable analyses, 54% and 30% of articles reported patient and event numbers for all variables. Of the studies, 66% used archival samples, indicating a potentially biased patient selection. Only 36% of studies reported clearly defined outcomes. CONCLUSIONS: Good reporting is critical for the interpretability and clinical applicability of prognostic studies. Current reporting of key information, such as the number of outcome events in all patients and subgroups, is poor. Use of the REMARK profile would greatly improve reporting and enhance prognostic research.

Prognostic markers in cancer: the evolution of evidence from single studies to meta-analysis, and beyond.

In oncology, prognostic markers are clinical measures used to help elicit an individual patient's risk of a future outcome, such as recurrence of disease after primary treatment. They thus facilitate individual treatment choice and aid in patient counselling. Evidence-based results regarding prognostic markers are therefore very important to both clinicians and their patients. However, there is increasing awareness that prognostic marker studies have been neglected in the drive to improve medical research. Large protocol-driven, prospective studies are the ideal, with appropriate statistical analysis and clear, unbiased reporting of the methods used and the results obtained. Unfortunately, published prognostic studies rarely meet such standards, and systematic reviews and meta-analyses are often only able to draw attention to the paucity of good-quality evidence. We discuss how better-quality prognostic marker evidence can evolve over time from initial exploratory studies, to large protocol-driven primary studies, and then to meta-analysis or even beyond, to large prospectively planned pooled analyses and to the initiation of tumour banks. We highlight articles that facilitate each stage of this process, and that promote current guidelines aimed at improving the design, analysis, and reporting of prognostic marker research. We also outline why collaborative, multi-centre, and multi-disciplinary teams should be an essential part of future studies.

Reporting recommendations for tumor marker prognostic studies (remark).

Despite years of research and hundreds of reports on tumor markers in oncology, the number of markers that have emerged as clinically useful is pitifully small. Often, initially reported studies of a marker show great promise, but subsequent studies on the same or related markers yield inconsistent conclusions or stand in direct contradiction to the promising results. It is imperative that we attempt to understand the reasons that multiple studies of the same marker lead to differing conclusions. A variety of methodologic problems have been cited to explain these discrepancies. Unfortunately, many tumor marker studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalizability of study results. The development of guidelines for the reporting of tumor marker studies was a major recommendation of the National Cancer Institute - European Organisation for Research and Treatment of Cancer (NCI - EORTC) First International Meeting on Cancer Diagnostics in 2000. As for the successful CONSORT initiative for randomized trials and for the STARD statement for diagnostic studies, we suggest guidelines to provide relevant information about the study design, preplanned hypotheses, patient and specimen characteristics, assay methods, and statistical analysis methods. In addition, the guidelines suggest helpful presentations of data and important elements to include in discussions. The goal of these guidelines is to encourage transparent and complete reporting so that the relevant information will be available to others to help them to judge the usefulness of the data and understand the context in which the conclusions apply.

Investigation on the improvement of prediction by bootstrap model averaging.

OBJECTIVES: We illustrate a recently proposed two-step bootstrap model averaging (bootstrap MA) approach to cope with model selection uncertainty. The predictive performance is investigated in an example and in a simulation study. Results are compared to those derived from other model selection methods. METHODS: In the framework of the linear regression model we use the two-step bootstrap MA, which consists of a screening step to eliminate covariates thought to have no influence on the response, and a model-averaging step. We also apply the full model, variable selection using backward elimination based on Akaike's Information Criterion (AIC), the Bayes Information Criterion (BIC) and the bagging approach. The predictive performance is measured by the mean squared error (MSE) and the coverage of confidence intervals for the true response. RESULTS: We obtained similar results for all approaches in the example. In the simulation the MSE was reduced by all approaches in comparison to the full model. The smallest values are obtained for bootstrap MA. Only the bootstrap MA and the full model correctly estimated the nominal coverage. The backward elimination procedures led to substantial underestimation and bagging to an overestimation of the true coverage. The screening step of bootstrap MA eliminates most of the unimportant factors. CONCLUSION: The new bootstrap MA approach shows promising results for predictive performance. It increases practical usefulness by eliminating unimportant factors in the screening step.

Building multivariable regression models with continuous covariates in clinical epidemiology--with an emphasis on fractional polynomials.

OBJECTIVES: In fitting regression models, data analysts must often choose a model based on several candidate predictor variables which may influence the outcome. Most analysts either assume a linear relationship for continuous predictors, or categorize them and postulate step functions. By contrast, we propose to model possible non-linearity in the relationship between the outcome and several continuous predictors by estimating smooth functions of the predictors. We aim to demonstrate that a structured approach based on fractional polynomials can give a broadly satisfactory practical solution to the problem of simultaneously identifying a subset of 'important' predictors and determining the functional relationship for continuous predictors. METHODS: We discuss the background, and motivate and describe the multivariable fractional polynomial (MFP) approach to model selection from data which include continuous and categorical predictors. We compare our results with those from other approaches in examples. We present a small simulation study to compare the functional form of the relationship obtained by fitting fractional polynomials and splines to a single predictor variable. RESULTS: We illustrate the advantages of the MFP approach over standard techniques of model construction in two real example datasets analyzed with logistic and Cox regression models, respectively. In the simulation study, fractional polynomial models had lower mean square error and more realistic behaviour than comparable spline models. CONCLUSIONS: In many practical situations, the MFP approach can satisfy the aim of finding models that fit the data well and also are simple, interpretable and potentially transportable to other settings.

REporting recommendations for tumour MARKer prognostic studies (REMARK).

Despite years of research and hundreds of reports on tumour markers in oncology, the number of markers that have emerged as clinically useful is pitifully small. Often initially reported studies of a marker show great promise, but subsequent studies on the same or related markers yield inconsistent conclusions or stand in direct contradiction to the promising results. It is imperative that we attempt to understand the reasons that multiple studies of the same marker lead to differing conclusions. A variety of methodological problems have been cited to explain these discrepancies. Unfortunately, many tumour marker studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalisability of the study results. The development of guidelines for the reporting of tumour marker studies was a major recommendation of the US National Cancer Institute and the European Organisation for Research and Treatment of Cancer (NCI-EORTC) First International Meeting on Cancer Diagnostics in 2000. Similar to the successful CONSORT initiative for randomised trials and the STARD statement for diagnostic studies, we suggest guidelines to provide relevant information about the study design, preplanned hypotheses, patient and specimen characteristics, assay methods, and statistical analysis methods. In addition, the guidelines suggest helpful presentations of data and important elements to include in discussions. The goal of these guidelines is to encourage transparent and complete reporting so that the relevant information will be available to others to help them to judge the usefulness of the data and understand the context in which the conclusions apply.

Radiation therapy after breast-conserving surgery; first results of a randomised clinical trial in patients with low risk of recurrence.

To study the role of radiotherapy and tamoxifen after breast-conserving surgery (BCS) in patients with a favourable prognosis, a clinical trial was initiated by the German Breast Cancer Study Group. Between 1991 and 1998, 361 patients (pT1pN0M0, aged 45-75 years, receptor positive, grade I-II) were randomised to radiotherapy (yes/no) and tamoxifen for 2 years (yes/no) in a 2x2 factorial design; the exclusion of seven centres (14 patients) left 347 patients in the analysis. After a median follow-up of 5.9 years, 77 events concerning event-free survival have been observed. Since a strong interactive effect between radiotherapy and tamoxifen has been established, the results are presented in terms of the treatment effects for all four treatment groups separately. Mainly due to the presence of local recurrences, the event rate was about three times higher in the group with BCS only than in the other three groups. No difference could be established between the four treatment groups for distant disease-free survival rates. It is concluded that even in patients with a favourable prognosis, the avoidance of radiotherapy and tamoxifen after BCS increases the rate of local recurrences substantially.

Is treatment with interferon-alpha effective in all patients with metastatic renal carcinoma? A new approach to the investigation of interactions.

The first analysis of the MRC RE01 trial in metastatic renal carcinoma identified a 28% reduction in the hazard of death for patients treated with interferon-alpha compared with medroxyprogesterone acetate (MPA). No subgroup was identified in which treatment with interferon-alpha was more or less effective than MPA. We used a new approach based on fractional polynomials to investigate the updated data from this trial for the possible interaction of treatment with prognostic factors. In the spirit of hypothesis generation, we considered 10 possible prognostic variables, of which white cell count (WCC) was found to influence the effectiveness of interferon treatment. In patients treated with MPA, there was no prognostic effect of WCC, whereas, in patients treated with interferon, the risk of dying increased significantly with WCC level. We defined subgroups of patients based on WCC levels and estimated a hazard ratio of 0.53 in favour of interferon in patients with WCC <6.5 x 10(9), whereas for patients with WCC >10 x 10(9) the risk appears to be similar between the treatment groups, or even slightly raised in the interferon group. Since our results are derived from flexible statistical models, they may be interpreted as a new hypothesis and require validation in independent data.

Quality of life in goserelin-treated versus cyclophosphamide + methotrexate + fluorouracil-treated premenopausal and perimenopausal patients with node-positive, early breast cancer: the Zoladex Early Breast Cancer Research Association Trialists Group.

PURPOSE: To compare quality of life (QoL) in premenopausal and perimenopausal patients with node-positive, early breast cancer treated with the endocrine agent goserelin (Zoladex; AstraZeneca Pharmaceuticals LP, Wilmington, DE) or cyclophosphamide + methotrexate + fluorouracil (CMF). PATIENTS AND METHODS: Patients from 86 centers worldwide were randomly assigned to receive either goserelin (3.6 mg every 28 days for 2 years; n = 514) or CMF (six 28-day cycles; n = 496), and were included in the QoL study. QoL was assessed using a self-administered patient questionnaire that consisted of 39 items from the Rotterdam Symptom Checklist, including dimensions evaluating physical and psychological symptom distress, activities of daily living, hormonal effects, and an assessment of overall QoL. RESULTS: Early benefits were noted during months 3 to 6 of treatment, for goserelin compared with CMF. Significant differences were found for changes in overall QoL (eg, 6.96 +/- 0.88 v 0.69 +/- 0.92 at 6 months; P <.0001) and for physical symptom distress, activity levels, and "effort to cope with illness" dimensions. At 1, 2, and 3 years, there were no significant differences in overall QoL or specific QoL dimensions. Scores for hormonal symptoms were worse with goserelin during the 2-year goserelin treatment period; however, this trend was reversed at 3 years. CONCLUSION: Goserelin offers improved overall QoL during the first 6 months of therapy compared with CMF chemotherapy in premenopausal and perimenopausal patients with early breast cancer. Coupled with equivalent efficacy in estrogen receptor-positive patients, these data support the use of goserelin as an alternative to CMF in premenopausal and perimenopausal patients with estrogen receptor-positive, node-positive early breast cancer.

Bone mineral density in premenopausal women treated for node-positive early breast cancer with 2 years of goserelin or 6 months of cyclophosphamide, methotrexate and 5-fluorouracil (CMF).

The purpose of this study was to compare changes in bone mineral density (BMD) in premenopausal patients with node-positive early breast cancer treated with goserelin (Zoladex) or cyclophosphamide, methotrexate and 5-fluorouracil (CMF). Patients ( n=1640) were randomized to goserelin (3.6 mg every 28 days for 2 years) or CMF (sixx28-day cycles) treatment. In a protocoled sub-study involving 96 patients from eight centers (goserelin: n=53; CMF: n=43), lumbar spine (L2-L4) and femoral neck BMD were assessed by dual X-ray absorptiometry at baseline and then annually for 3 years. At the end of the 2-year goserelin-treatment period, mean BMD losses for goserelin-treated and CMF-treated patients were -10.5% and -6.5% ( P=0.0005) for lumbar spine and -6.4% and -4.5% ( P=0.04) for femoral neck, respectively. At 3 years, partial recovery of BMD was observed in goserelin recipients. In contrast, mean BMD losses for the CMF group indicated persistent BMD loss. No significant differences in BMD were observed between groups at the 3-year assessment of the spine or femoral neck. In the CMF group, based on amenorrhea status at 48 weeks, BMD losses at the lumbar spine were greater for amenorrheic than non-amenorrheic patients. Ovarian suppression resulting in amenorrhea was closely related to BMD loss in both treatment groups. Overall, patients who received CMF did not show recovery of BMD throughout follow-up, whereas partial recovery was observed 1 year after cessation of goserelin therapy, associated with the return of ovarian function in the majority of patients.

Survival analyses from the ZEBRA study. goserelin (Zoladex) versus CMF in premenopausal women with node-positive breast cancer.

The Zoladex Early Breast Cancer Research Association (ZEBRA) trial compared the efficacy and tolerability of goserelin (Zoladex) with cyclophosphamide, methotrexate and 5-fluorouracil (CMF) chemotherapy in pre-/perimenopausal women with node-positive early breast cancer. The results of disease-free survival (DFS) analyses have already been published. Here we present an update including data on overall survival (OS) from the ZEBRA trial at a median follow-up of 7.3 years. In patients with oestrogen receptor (ER)-positive tumours, non-inferiority of goserelin versus CMF for OS was shown; goserelin was again shown to be equivalent to CMF for DFS. This updated analysis has demonstrated that the two treatments are also equivalent for distant disease-free survival (DDFS). In patients with ER-negative disease, goserelin was inferior to CMF for DFS, DDFS and OS. This follow-up analysis confirms the previously reported outcomes from the ZEBRA trial and demonstrates that goserelin offers an effective alternative to CMF chemotherapy for adjuvant therapy of premenopausal patients with ER-positive, node-positive early breast cancer.

Stability of multivariable fractional polynomial models with selection of variables and transformations: a bootstrap investigation.

Sauerbrei and Royston have recently described an algorithm, based on fractional polynomials, for the simultaneous selection of variables and of suitable transformations for continuous predictors in a multivariable regression setting. They illustrated the approach by analyses of two breast cancer data sets. Here we extend their work by considering how to assess possible instability in such multivariable fractional polynomial models. We first apply the algorithm repeatedly in many bootstrap replicates. We then use log-linear models to investigate dependencies among the inclusion fractions for each predictor and among the simplified classes of fractional polynomial function chosen in the bootstrap samples. To further evaluate the results, we define measures of instability based on a decomposition of the variability of the bootstrap-selected functions in relation to a reference function from the original model. For each data set we are able to identify large, reasonably stable subsets of the bootstrap replications in which the functional forms of the predictors appear fairly stable. Despite the considerable flexibility of the family of fractional polynomials and the consequent risk of overfitting when several variables are considered, we conclude that the multivariable selection algorithm can find stable models.

Goserelin versus cyclophosphamide, methotrexate, and fluorouracil as adjuvant therapy in premenopausal patients with node-positive breast cancer: The Zoladex Early Breast Cancer Research Association Study.

PURPOSE: Current adjuvant therapies have improved survival for premenopausal patients with breast cancer but may have short-term toxic effects and long-term effects associated with premature menopause. PATIENTS AND METHODS: The Zoladex Early Breast Cancer Research Association study assessed the efficacy and tolerability of goserelin (3.6 mg every 28 days for 2 years; n = 817) versus cyclophosphamide, methotrexate, and fluorouracil (CMF) chemotherapy (six 28-day cycles; n = 823) for adjuvant treatment in premenopausal patients with node-positive breast cancer. RESULTS: Analysis was performed when 684 events had been achieved, and the median follow-up was 6 years. A significant interaction between treatment and estrogen receptor (ER) status was found (P =.0016). In ER-positive patients (approximately 74%), goserelin was equivalent to CMF for disease-free survival (DFS) (hazard ratio [HR], 1.01; 95% confidence interval [CI], 0.84 to 1.20). In ER-negative patients, goserelin was inferior to CMF for DFS (HR, 1.76; 95% CI, 1.27 to 2.44). Amenorrhea occurred in more than 95% of goserelin patients by 6 months versus 58.6% of CMF patients. Menses returned in most goserelin patients after therapy stopped, whereas amenorrhea was generally permanent in CMF patients (22.6% v 76.9% amenorrheic at 3 years). Chemotherapy-related side effects such as nausea/vomiting, alopecia, and infection were higher with CMF than with goserelin during CMF treatment. Side effects related to estrogen suppression were initially higher with goserelin, but when goserelin treatment stopped, reduced to a level below that observed in the CMF group. CONCLUSION: Goserelin offers an effective, well-tolerated alternative to CMF in premenopausal patients with ER-positive and node-positive early breast cancer.

Duration of adjuvant chemotherapy for breast cancer: a joint analysis of two randomised trials investigating three versus six courses of CMF.

Cyclophosphamide, methotrexate and fluorouracil adjuvant combination chemotherapy for breast cancer is currently used for the duration of six monthly courses. We performed a joint analysis of two studies on the duration of adjuvant cyclophosphamide, methotrexate and fluorouracil in patients with node-positive breast cancer to investigate whether three courses of cyclophosphamide, methotrexate and fluorouracil might suffice. The International Breast Cancer Study Group Trial VI randomly assigned 735 pre- and perimenopausal patients to receive 'classical' cyclophosphamide, methotrexate and fluorouracil for three consecutive cycles, or the same chemotherapy for six consecutive cycles. The German Breast Cancer Study Group randomised 289 patients to receive either three or six cycles of i.v. cyclophosphamide, methotrexate and fluorouracil day 1, 8. Treatment effects were estimated using Cox regression analysis stratified by clinical trial without further adjustment for covariates. The 5-year disease-free survival per cents (+/-s.e.) were 54+/-2% for three cycles and 55+/-2% for six cycles (n=1024; risk ratio (risk ratio: CMFx3/CMFx6), 1.00; 95% confidence interval, 0.85 to 1.18; P=0.99). Use of three rather than six cycles was demonstrated to be adequate in both studies for patients at least 40-years-old with oestrogen-receptor-positive tumours (n=594; risk ratio, 0.86; 95% confidence interval, 0.68 to 1.08; P=0.19). In fact, results slightly favoured three cycles over six for this subgroup, and the 95% confidence interval excluded an adverse effect of more than 2% with respect to absolute 5-year survival. In contrast, three cycles appeared to be possibly inferior to six cycles for women less than 40-years-old (n=190; risk ratio, 1.25; 95% confidence interval, 0.87 to 1.80; P=0.22) and for women with oestrogen-receptor-negative tumours (n=302; risk ratio, 1.15; 95% confidence interval, 0.85 to 1.57; P=0.37). Thus, three initial cycles of adjuvant cyclophosphamide, methotrexate and fluorouracil chemotherapy were as effective as six cycles for older patients (40-years-old) with oestrogen-receptor-positive tumours, while six cycles of adjuvant cyclophosphamide, methotrexate and fluorouracil might still be required for other cohorts. Because endocrine therapy with tamoxifen and GnRH analogues is now available for younger women with oestrogen-receptor-positive tumours, the need for six cycles of cyclophosphamide, methotrexate and fluorouracil is unclear and requires further investigation.

Long-term follow-up of patients in four prospective studies of the German Breast Cancer Study Group (GBSG): A summary of key results.

Evaluation of treatment modalities and prognostic factors in early breast cancer requires a long-term follow-up of patients in prospective studies. The German Breast Cancer Study Group (GBSG) started four nationwide studies in 1983 in which a total of 2,746 patients have been enrolled and followed for about 10 years. Questions that have been addressed in these studies are still relevant today and comprise the role of breast-conserving therapy, the duration of adjuvant chemotherapy, and whether adjuvant radiotherapy is needed. The key results of these studies are highlighted including some important findings on prognosis, e.g., the role of isolated locoregional recurrence and the prognosis of patients with 10 or more positive lymph nodes. The data of all randomized patients were regularly included into the overviews of the Early Breast Cancer Trialists' Collaborative Group; the data of the nonrandomized patients have been used to examine the external validity of treatment comparisons. Overall, it can be concluded that the GBSG studies have made valuable and internationally recognized contributions to the prognosis and treatment of patients with early breast cancer.