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Non-linear transfor...
Non-linear transformations of age at diagnosis, tumor size, and number of positive lymph nodes in prediction of clinical outcome in breast cancer
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- Forsare, Carina (author)
- Lund University,Lunds universitet,Individuell Bröstcancerbehandling,Forskargrupper vid Lunds universitet,Personalized Breast Cancer Treatment,Lund University Research Groups,Lund Univ, Sweden
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- Bak, Martin (author)
- Odense University Hospital,Odense Univ Hosp, Denmark
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- Falck, Anna Karin (author)
- Helsingborg Hospital,Helsingborg Hosp, Sweden
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- Grabau, Dorthe (author)
- Lund University,Lunds universitet,Kirurgi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Surgery (Lund),Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital,Lund Univ, Sweden
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- Killander, Fredrika (author)
- Lund University,Lunds universitet,Tumörmikromiljö,Sektion I,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Tumor microenvironment,Section I,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital,Lund Univ, Sweden; Skane Univ Hosp, Sweden
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- Malmström, Per (author)
- Lund University,Lunds universitet,Bröstcancer-genetik,Sektion I,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Breastcancer-genetics,Section I,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital,Lund Univ, Sweden; Skane Univ Hosp, Sweden
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- Rydén, Lisa (author)
- Lund University,Lunds universitet,Skåne University Hospital,Lund Univ, Sweden; Skane Univ Hosp, Sweden
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- Stål, Olle (author)
- Linköpings universitet,Linköping University,Avdelningen för Kirurgi, Ortopedi och Onkologi,Medicinska fakulteten,Region Östergötland, Onkologiska kliniken US
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- Sundqvist, Marie (author)
- Kalmar County Hospital,Cty Hosp, Sweden
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- Bendahl, Pär Ola (author)
- Lund University,Lunds universitet,Individuell Bröstcancerbehandling,Forskargrupper vid Lunds universitet,Personalized Breast Cancer Treatment,Lund University Research Groups,Lund Univ, Sweden
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- Fernö, Mårten (author)
- Lund University,Lunds universitet,Individuell Bröstcancerbehandling,Forskargrupper vid Lunds universitet,Personalized Breast Cancer Treatment,Lund University Research Groups,Lund Univ, Sweden
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(creator_code:org_t)
- 2018-12-07
- 2018
- English.
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In: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 18:1
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Abstract
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- Background: Prognostic factors in breast cancer are often measured on a continuous scale, but categorized for clinical decision-making. The primary aim of this study was to evaluate if accounting for continuous non-linear effects of the three factors age at diagnosis, tumor size, and number of positive lymph nodes improves prognostication. These factors will most likely be included in the management of breast cancer patients also in the future, after an expected implementation of gene expression profiling for adjuvant treatment decision-making. Methods: Four thousand four hundred forty seven and 1132 women with primary breast cancer constituted the derivation and validation set, respectively. Potential non-linear effects on the log hazard of distant recurrences of the three factors were evaluated during 10 years of follow-up. Cox-models of successively increasing complexity: dichotomized predictors, predictors categorized into three or four groups, and predictors transformed using fractional polynomials (FPs) or restricted cubic splines (RCS), were used. Predictive performance was evaluated by Harrell's C-index. Results: Using FP-transformations, non-linear effects were detected for tumor size and number of positive lymph nodes in univariable analyses. For age, non-linear transformations did, however, not improve the model fit significantly compared to the linear identity transformation. As expected, the C-index increased with increasing model complexity for multivariable models including the three factors. By allowing more than one cut-point per factor, the C-index increased from 0.628 to 0.674. The additional gain, as measured by the C-index, when using FP- or RCS-transformations was modest (0.695 and 0.696, respectively). The corresponding C-indices for these four models in the validation set, based on the same transformations and parameter estimates from the derivation set, were 0.675, 0.700, 0.706, and 0.701. Conclusions: Categorization of each factor into three to four groups was found to improve prognostication compared to dichotomization. The additional gain by allowing continuous non-linear effects modeled by FPs or RCS was modest. However, the continuous nature of these transformations has the advantage of making it possible to form risk groups of any size.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
Keyword
- Breast cancer
- Categorical
- Continuous
- Fractional polynomials
- Prognostic
- Splines
- Breast cancer; Prognostic; Categorical; Continuous; Fractional polynomials; Splines
Publication and Content Type
- art (subject category)
- ref (subject category)
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BMC Cancer
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Forsare, Carina
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Bak, Martin
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Falck, Anna Kari ...
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Grabau, Dorthe
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Killander, Fredr ...
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Malmström, Per
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Rydén, Lisa
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Stål, Olle
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Sundqvist, Marie
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Bendahl, Pär Ola
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Fernö, Mårten
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Cancer and Oncol ...
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BMC Cancer
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Lund University
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Linköping University