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Dive into the research topics where C. A. Drukker is active.

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Featured researches published by C. A. Drukker.


European Journal of Cancer | 2013

Prospective cost-effectiveness analysis of genomic profiling in breast cancer

Valesca P. Retèl; Manuela A. Joore; C. A. Drukker; Jolien M. Bueno-de-Mesquita; Michael Knauer; H. van Tinteren; Sabine C. Linn; W.H. van Harten

BACKGROUND The cost-effectiveness of the 70-gene signature (70-GS) (MammaPrint®) has earlier been estimated using retrospective validation data. Based on the prospective 5-year survival data of the microarRAy-prognoSTics-in-breast-cancER (RASTER) study, the aim here was to evaluate the cost-effectiveness reflecting the actual use in clinical practice, including reality-based compliance rates. METHODS Costs and outcomes (quality-adjusted-life-years (QALYs)) were calculated in node-negative (N-) patients included in the RASTER study (n=427). Sensitivity and specificity of the 70-gene and Adjuvant! Online (AO) were based on 5-year distant-disease-free survival (DDFS). Subgroup analyses were performed for two groups for whom benefit of the 70-gene had earlier been reported: (1) ductal, oestrogen receptor-positive (ER+), tumour diameter 10-30 mm, grade II, age 40-70; (2) ductal, oestrogen receptor-positive, tumour diameter 5-30 mm, grade II/III and age 40-70. RESULTS Based on 5-year survival data, the cost-effectiveness of the 70-gene signature versus AO was prospectively confirmed. The total health care costs per patient were €26,786 for the 70-gene and €29,187 for AO. The quality adjusted life years yielded 12.49 and 11.88, respectively. The subgroups retrieved slightly higher life gains and higher costs, but all resulted finally in a favourable position for the 70-gene signature. CONCLUSIONS The use of the 70-gene signature, as judged appropriate by doctors and patients and supported by a low risk 70-gene signature as an oncological safe choice, was also found to be cost-effective.


Pediatric Blood & Cancer | 2009

Paraneoplastic gastro-intestinal anti-Hu syndrome in neuroblastoma

C. A. Drukker; Hugo A. Heij; L.C.D. Wijnaendts; J.I.M.L. Verbeke; G.J.L. Kaspers

The anti‐Hu syndrome is a well‐known paraneoplastic syndrome and may be rarely seen in patients with neuroblastoma. However, it is relatively unknown that anti‐Hu antibodies can cause gastro‐intestinal signs and symptoms. We report on a child with neuroblastoma who presented with gastro‐intestinal disturbances as a result of the anti‐Hu syndrome and summaries two similar case reports reported in literature. Neuroblastoma patients with gastro‐intestinal disturbances, ranging from constipation to a paralytic ileus, might suffer from the gastro‐intestinal anti‐Hu syndrome. The causative antibodies can be determined to diagnose or exclude this syndrome, and successful treatment is possible. Pediatr Blood Cancer 2009;52:396–398.


Genetics in Medicine | 2016

Using a gene expression signature when controversy exists regarding the indication for adjuvant systemic treatment reduces the proportion of patients receiving adjuvant chemotherapy: a nationwide study

A. Kuijer; A.C.M. van Bommel; C. A. Drukker; M. van der Heiden-van der Loo; Carolien H. Smorenburg; Pieter J. Westenend; Sabine C. Linn; E.J.Th. Rutgers; Sjoerd G. Elias; Th. van Dalen

Purpose:The Dutch national guideline advises use of gene-expression signatures, such as the 70-gene signature (70-GS), in case of ambivalence regarding the benefit of adjuvant chemotherapy (CT). In this nationwide study, the impact of 70-GS use on the administration of CT in early breast cancer patients with a dubious indication for CT is assessed.Methods:Patients within a national guideline directed indication area for 70-GS use who were surgically treated between November 2011 and April 2013 were selected from the Netherlands Cancer Registry database. The effect of 70-GS use on the administration of CT was evaluated in guideline- and age-delineated subgroups addressing potential effect of bias by linear mixed-effect modeling and instrumental variable (IV) analyses.Results:A total of 2,043 patients within the indicated area for 70-GS use were included, of whom 298 received a 70-GS. Without use of the 70-GS, 45% of patients received CT. The 70-GS use was associated with a 9.5% decrease in CT administration (95% confidence interval (CI): −15.7 to −3.3%) in linear mixed-effect model analyses and IV analyses showed similar results (−9.9%; 95% CI: −19.3 to −0.4).Conclusion:In patients in whom the Dutch national guidelines suggest the use of a gene-expression profile, 70-GS use is associated with a 10% decrease in the administration of adjuvant CT.Genet Med 18 7, 720–726.Genetics in Medicine (2016); 18 7, 720–726. doi:10.1038/gim.2015.152


Cancer Research | 2013

Abstract P6-06-13: Optimized prediction of clinical outcome by the PREDICT plus tool and the 70-gene signature in early stage node-negative breast cancer

C. A. Drukker; Mv Nijenhuis; Jolien M. Bueno-de-Mesquita; V. Retel; H. van Tinteren; Marc Schmidt; W.H. van Harten; Gabe S. Sonke; L van't Veer; E.J.T. Rutgers; M.J. van de Vijver; Sabine C. Linn

Background Established breast cancer guidelines and online tools use clinico-pathological factors including age, tumor size and grade to evaluate the risk of recurrence and select patients who are eligible to receive adjuvant chemotherapy (ACT). One of the online tools, PREDICT plus, was recently updated and is the first tool to include HER2 status and method of detection in risk assessment. Another tool to better guide AST decisions is the 70-gene signature. The 70-gene signature is a gene-expression classifier that was developed and extensively validated to predict the risk of distant recurrence in breast cancer. In clinical practice, an ad-hoc combination of clinico-pathological guidelines and gene-expression classifiers are used. The aim of this study is to evaluate the combination of the PREDICT plus tool and the 70-gene signature to optimize adjuvant systemic treatment decisions. Methods For 427 patients participating in the RASTER study (cT1-3N0M0) a 70-gene signature result was available. PREDICT risk estimates at 5 (P5) and 10 (P10) years after diagnosis were calculated using the following variables: age, method of detection, tumor size, tumor grade, number of positive nodes, estrogen receptor, and HER2 status. Patients were considered high risk if their survival probability was less than 95% at 5 years and/or 90% at 10 years. Five-year distant-recurrence-free-interval (DRFI) and distant-disease-free-survival (DDFS) probabilities were evaluated between subgroups based on the 70-gene signature and PREDICT plus. Results Median follow-up was 61.6 months. Patients with a low risk 70-gene signature (n = 219) had a 5-year DRFI of 97.0% (CI: 94.7-99.4) compared to 91.7% (CI: 87.9-95.7) for the 70-gene signature high risk patients (n = 208). The 5-year DRFI for patients with a P5 low risk (n = 228) is 96.8% (CI: 94.2-99.4) compared to 91.7% (CI: 87.9-95.7) for P5 high risk (n = 199). The 5-year DRFI for patients with a P10 low risk (n = 168) is 98.0% (CI: 95.7-100) compared to 92.1% (CI: 88.7-95.6) for P10 high risk (n = 259). ACT data, DRFI and DDFS probabilities in all subgroups are shown in table 1. Among the patients who had a low risk according to PREDICT at 5 years, but a high risk at 10 years (n = 60), the 5-year DRFI was 100% when their tumor was tested as low risk based on the 70-gene signature (13% received CT) compared to 84% in case of a high risk result (55% received CT)(p = 0.03). Conclusion Combining PREDICT plus with the 70-gene signature may help to identify early stage node-negative breast cancer patients for whom limited adjuvant systemic treatment might be appropriate and for whom overtreatment can be avoided. Especially in case of a low risk assessment by PREDICT at 5 years but a high risk at 10 years, the 70-gene signature may aid to select those patients at a high risk of recurrence who will benefit most from ACT. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-06-13.


International Journal of Cancer | 2013

A prospective evaluation of a breast cancer prognosis signature in the observational RASTER study

C. A. Drukker; Jolien M. Bueno-de-Mesquita; Valesca P. Retèl; W.H. van Harten; H. van Tinteren; Jelle Wesseling; R. M. H. Roumen; Michael Knauer; L van 't Veer; Gabe S. Sonke; E.J.T. Rutgers; M.J. van de Vijver; Sabine C. Linn


Breast Cancer Research and Treatment | 2014

Long-term impact of the 70-gene signature on breast cancer outcome

C. A. Drukker; H. van Tinteren; Marjanka K. Schmidt; E.J.Th. Rutgers; René Bernards; M.J. van de Vijver; L van 't Veer


Breast Cancer Research and Treatment | 2014

Mammographic screening detects low-risk tumor biology breast cancers.

C. A. Drukker; Marjanka K. Schmidt; E.J.T. Rutgers; Fatima Cardoso; Karla Kerlikowske; Laura Esserman; F.E. van Leeuwen; R. M. Pijnappel; Leen Slaets; Jan Bogaerts; L van 't Veer


Annals of Surgical Oncology | 2013

Guiding Breast-Conserving Surgery in Patients After Neoadjuvant Systemic Therapy for Breast Cancer: A Comparison of Radioactive Seed Localization with the ROLL Technique

M. Donker; C. A. Drukker; Renato A. Valdés Olmos; Emiel J. Th. Rutgers; Claudette E. Loo; Gabe S. Sonke; Jelle Wesseling; Tanja Alderliesten; Marie-Jeanne T. F. D. Vrancken Peeters


Breast Cancer Research and Treatment | 2014

Gene expression profiling to predict the risk of locoregional recurrence in breast cancer: a pooled analysis

C. A. Drukker; Sjoerd G. Elias; Mv Nijenhuis; Jelle Wesseling; Harry Bartelink; P.H.M. Elkhuizen; B. Fowble; Pat W. Whitworth; R. R. Patel; F de Snoo; L. J. van ’t Veer; Peter D. Beitsch; E.J.Th. Rutgers


European Journal of Cancer | 2014

Risk estimations and treatment decisions in early stage breast cancer: Agreement among oncologists and the impact of the 70-gene signature

C. A. Drukker; H.C. van den Hout; Gabe S. Sonke; Etienne Brain; H. Bonnefoi; F. Cardoso; Aron Goldhirsch; Nadia Harbeck; A.H. Honkoop; R Koornstra; H.W.M. van Laarhoven; J.E.A. Portielje; A. Schneeweiss; C.H. Smorenburg; Jacqueline Stouthard; Sabine C. Linn; Marjanka K. Schmidt

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Jelle Wesseling

Netherlands Cancer Institute

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Sabine C. Linn

Netherlands Cancer Institute

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E.J.T. Rutgers

Netherlands Cancer Institute

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H. van Tinteren

Netherlands Cancer Institute

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M.J. van de Vijver

Netherlands Cancer Institute

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W.H. van Harten

Netherlands Cancer Institute

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Gabe S. Sonke

Netherlands Cancer Institute

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L van't Veer

Netherlands Cancer Institute

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