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Willi Sauerbrei

Publications and source records attributed to Willi Sauerbrei.

15 recordsLinked to original sources
PubMed2006

Dichotomizing continuous predictors in multiple regression: a bad idea.

In medical research, continuous variables are often converted into categorical variables by grouping values into two or more categories. We consider in detail issues pertaining to creating just two groups, a common approach in clinical research. We argue that the simplicity achieved is gained at a cost; dichotomization may create rather than avoid problems, notably a considerable loss of power and residual confounding. In addition, the use of a data-derived 'optimal' cutpoint leads to serious bias. We illustrate the impact of dichotomization of continuous predictor variables using as a detailed case study a randomized trial in primary biliary cirrhosis. Dichotomization of continuous data is unnecessary for statistical analysis and in particular should not be applied to explanatory variables in regression models.

Age Factors↗
PubMed2005

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.

Biomarkers, Tumor↗
PubMed2005

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 methodologic 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 study results. The development of guidelines for the reporting of tumour 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 randomised trials and for the STARD statement for diagnostic studies, we suggest guidelines to provide relevant information about the study design, pre-planned 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.

Biomarkers, Tumor↗
PubMed2005

Prognostic factors. Confusion caused by bad quality design, analysis and reporting of many studies.

In contrast to therapeutic research guidance to design, conduct, analyse and report studies on prognostic factors is less developed and often several deficiencies are stressed. For the assessment of the importance of a factor of interest a systematic review of the corresponding studies would be required, however, this is hardly possible because of many weaknesses in the individual studies. In this article I will discuss several deficiencies of the analysis of prognostic factor studies and shortly discuss problems of reporting and of a summary assessment. By using 3 studies in cancer and a hypotheitcal study as examples I will discuss categorization respectively the determination of a functional form for a continuous factor, sample size, multivariable analysis and data quality. The message of this paper is that serious improvements of prognostic factor studies are required. This can be achieved by a closer collaboration between several disciplines and a closer collaboration at the international level. Specifically, experienced statisticians have to play a central role in the planning, analysis, interpretation and reporting of these studies.

Clinical Trials as Topic↗
PubMed2005

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 why multiple studies of the same marker lead to differing conclusions. A variety of methodological 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 provide helpful suggestions on how to present 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.

Biomarkers, Tumor↗
PubMed2005

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 why multiple studies of the same marker lead to differing conclusions. A variety of methodological 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 Diagnostic 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 provide helpful suggestions on how to present 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.

Biomarkers, Tumor↗
PubMed2004

A new approach to modelling interactions between treatment and continuous covariates in clinical trials by using fractional polynomials.

We consider modelling interaction between a categoric covariate T and a continuous covariate Z in a regression model. Here T represents the two treatment arms in a parallel-group clinical trial and Z is a prognostic factor which may influence response to treatment (known as a predictive factor). Generalization to more than two treatments is straightforward. The usual approach to analysis is to categorize Z into groups according to cutpoint(s) and to analyse the interaction in a model with main effects and multiplicative terms. The cutpoint approach raises several well-known and difficult issues for the analyst. We propose an alternative approach based on fractional polynomial (FP) modelling of Z in all patients and at each level of T. Other prognostic variables can also be incorporated by first constructing a multivariable adjustment model which may contain binary covariates and FP transformations of continuous covariates other than Z. The main step involves FP modelling of Z and testing equality of regression coefficients between treatment groups in an interaction model adjusted for other covariates. Extensive experience suggests that a two-term fractional polynomial (FP2) function may describe the effect of a prognostic factor on a survival outcome quite well. In a controlled trial, this FP2 function describes the prognostic effect averaged over the treatment groups. We refit this function in each treatment group to see if there are substantial differences between groups. Allowing different parameter values for the chosen FP2 function is flexible enough to detect such differences. Within the same algorithm we can also deal with the conceptually different cases of a predefined hypothesis of interaction or searching for interactions. We demonstrate the ability of the approach to detect and display treatment/covariate interactions in two examples from controlled trials in cancer.

Age Factors↗
PubMed2004

Confidence intervals for the effect of a prognostic factor after selection of an 'optimal' cutpoint.

When investigating the effects of potential prognostic or risk factors that have been measured on a quantitative scale, values of these factors are often categorized into two groups. Sometimes an 'optimal' cutpoint is chosen that gives the best separation in terms of a two-sample test statistic. It is well known that this approach leads to a serious inflation of the type I error and to an overestimation of the effect of the prognostic or risk factor in absolute terms. In this paper, we illustrate that the resulting confidence intervals are similarly affected. We show that the application of a shrinkage procedure to correct for bias, together with bootstrap resampling for estimating the variance, yields confidence intervals for the effect of a potential prognostic or risk factor with the desired coverage.

Breast Neoplasms↗
PubMed2004

A new measure of prognostic separation in survival data.

Multivariable prognostic models are widely used in cancer and other disease areas, and have a range of applications in clinical medicine, clinical trials and allocation of health services resources. A well-founded and reliable measure of the prognostic ability of a model would be valuable to help define the separation between patients or prognostic groups that the model could provide, and to act as a benchmark of model performance in a validation setting. We propose such a measure for models of survival data. Its motivation derives originally from the idea of separation between Kaplan-Meier curves. We define the criteria for a successful measure and discuss them with respect to our approach. Adjustments for 'optimism', the tendency for a model to predict better on the data on which it was derived than on new data, are suggested. We study the properties of the measure by simulation and by example in three substantial data sets. We believe that our new measure will prove useful as a tool to evaluate the separation available-with a prognostic model.

Brain Neoplasms↗
PubMed2004

Assessment of breast cancer vascularisation by Doppler ultrasound as a prognostic factor of survival.

Tumor growth and metastasis in breast cancer are correlated to neoangiogenesis, which became a potential candidate as a prognostic factor in this tumor type. Several studies have used immunohistochemical staining to count microvessel density as a marker of neoangiogenesis. This hospital-based retrospective pilot study measured vascularisation of early breast cancer by Doppler ultrasound and determined its value as a prognostic factor of overall survival in 147 women. The number of tumor related arteries were detected by color-coded Doppler ultrasound. We identified < or =10 tumor arteries and >10 tumor arteries in 117 and 30 women, respectively. Only weak correlation was found between the number of tumor arteries and established clinicopathological parameters such as tumor size (r=0.25) and lymph node involvement (r=0.13). In an univariate analysis, the strongest predictors of overall survival were number of tumor arteries [relative risk (RR) 4.60 (1.96-10.78)], positive axillary lymph nodes [RR 4.48 (1.59-12.60)] and angioinvasion [RR 4.26 (1.93-9.37)]. These three parameters were also found to be independent predictors of overall survival in a multivariate analysis [RR 3.21 (1.13-9.10) for positive lymph nodes; RR 2.69 (1.33-5.41) for number of tumor arteries; RR 2.84 (1.27-6.34) for angioinvasion]. Tumor vascularisation detected by Doppler ultrasound appears to be an independent predictor of overall survival in women with early breast cancer.

Adult↗
PubMed2003

Tumor stage and early mortality for surgical resections in lung cancer.

BACKGROUND: Postoperative mortality rates have been published in relation to operative procedure or preexisting pulmonary and extrapulmonary diseases. We analyzed our patients for the effect of the postoperative tumor stage on perioperative mortality. PATIENTS AND METHODS: Retrospective study of all thoracotomies for resections ( n=1281) in primary lung cancer from January 1987 to December 1997. Uni- and multivariate analysis was performed for operative procedure, mortality (30 and 90 days), tumor stage, sex, age, tumor localization, and completeness of resection. Radical resection was achieved in 91.9% of the patients. RESULTS: Overall postoperative deaths occurred in 4% and 7.3% of patients after 30 and 90 days respectively. Depending on the operative procedure the mortality after segmental resection ( n=116) was 0.9% and 1.7%, lobectomy ( n=621) 3.0% and 5.7%, sleeve lobectomy ( n=152) 5.3% and 7.9%, and pneumonectomy ( n=314) 6.7% and 12.5%, respectively. Within 30 and 90 days postoperatively deaths occurred, respectively, in 0.8% and 1.0% of stage I patients ( n=493), 5.4% and 5.4% of stage II ( n=147), 4.9% and 8.8% of stage IIIa ( n=388), 7.2% and 16.6% of stage IIIb ( n=148), 8.9% and 20.5% and of stage IV ( n=114). Multivariate analysis showed postoperative tumor stage to be the factor most closely related to within the first 90 days. CONCLUSIONS: Tumor stage but not type of resection is the strongest predictor of postoperative mortality in these subpopulations.

Adenoma↗
PubMed2003

Multivariate analysis of prognostic factors in patients with glioblastoma.

BACKGROUND: To identify prognostic factors for overall survival in patients with newly diagnosed glioblastoma undergoing radiation therapy. PATIENTS AND METHODS: From January 1980 to June 2000, we treated 432 consecutive patients with glioblastoma at out institution. 17 patients were excluded from the analysis for various reasons. Mean age of the 415 patients who were included in the study was 59 years (19-81 years), Karnofsky performance status (KPS) was > or = 70 in 280 patients. 343 patients underwent resection, 72 had a biopsy. Various fractionation schemes were used (conventional fractionation, n = 112; hypofractionation, n = 94; accelerated hyperfractionation, n = 209). Survival probabilities were estimated using the method of Kaplan and Meier. Multivariate analysis was done with a Cox regression model. RESULTS: By July 2001, 406 patients had died. Medial overall survival was 8.2 months. Of ten factors considered in a proportional hazards model stratified for treatment (fractionation scheme and type of surgery), significant variables in a multivariate model were age (50-64 years vs < 50 years [RR 1.35; 95% CI 1.02-1.78], > or = 65 years vs < 50 years [RR 2.08; 95% CI 1.54-2.81]), performance status (KPS < 70 vs > or = 70 [RR 1.53; 95% CI 1.23-1.90]), and central tumor location (yes vs no [RR 1.39; 95% CI 1.04-1.87]). Blood hemoglobin (Hb) values were available in 318 patients and serum lactate dehydrogenase (LDH) levels in 234 patients. 89 patients were anemic (Hb men < 13 g/dl, women < 12 g/dl), in 80 patients the LDH level was raised beyond the upper limit of the normal range (> 240 U/l). By including the three significant variables, both parameters had an additional significant effect with an estimated relative risk of about 1.4 in their corresponding subgroups. CONCLUSION: Besides established prognostic factors, anemia and raised serum LDH levels may negatively influence outcome in glioblastoma patients. Our results from data-dependent modeling have to be confirmed by independent studies.

Adult↗
PubMed2002

Intraperitoneal adenovirus-mediated suicide gene therapy in combination with either topotecan or paclitaxel in nude mice with human ovarian cancer.

A mouse model of human ovarian cancer was used to investigate the effect of adenovirus-mediated thymidine kinase gene therapy (gt) in combination with chemotherapy. One hundred sixty female CD-1 nu/nu mice were injected intraperitoneally with Ov-ca-2774 cells. Onset of intraperitoneal treatment with either topotecan (6 or 12 mg/kg) or paclitaxel (18 or 36 mg/kg) was on day 4 or 8 and was repeated once after 4 days. Animals scheduled for gt received intraperitoneal application of adv/rsv-tk 1 day prior to chemotherapy and were subsequently treated with ganciclovir (gcv; 10 mg/kg, every 12 hours for 6 days). Survival was chosen as study endpoint. Whereas tumor burden had hardly any effect on survival, the lower dose of either cytotoxic agent was seen to be more effective than the higher one. In the topotecan group, an interaction between topotecan and gt was present. Survival was best for animals treated with low dose of topotecan only, the addition of gt reduced survival time significantly. With the higher dose, gt did not affect survival time. With paclitaxel, only slight effects of gt on the survival times were seen. Due to treatment toxicity, this animal model may be problematic for the evaluation of gt and chemotherapy combinations. The effect of dose varied strongly with time. Mice treated with high-dose chemotherapy had a substantially increased risk of dying in the time period following application, whereas this advantage of the lower dose disappeared later.

Adenoviridae↗