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Marazzi F, Barone R, Masiello V, Magri V, Mulè A, Santoro A, Cacciatori F, Boldrini L, Franceschini G, Moschella F, Naso G, Tomao S, Gambacorta MA, Mantini G, Masetti R, Smaniotto D, Valentini V. Oncotype DX Predictive Nomogram for Recurrence Score Output: The Novel System ADAPTED01 Based on Quantitative Immunochemistry Analysis. Clin Breast Cancer 2020; 20:e600-e611. [PMID: 32565110 DOI: 10.1016/j.clbc.2020.04.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 04/21/2020] [Accepted: 04/23/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE Oncotype DX (ODX) predicts breast cancer recurrence risk, guiding the choice of adjuvant treatment. In many countries, access to the test is not always available. We used correlation between phenotypical tumor characteristics, quantitative classical immunohistochemistry (IHC), and recurrence score (RS) assessed by ODX to develop a decision supporting system for clinical use. PATIENTS AND METHODS Breast cancer patients who underwent ODX testing between 2014 and 2018 were retrospectively included in the study. The data selected for analysis were age, menopausal status, and pathologic and IHC features. IHC was performed with standardized quantitative methods. The data set was split into two subsets: 70% for the training set and 30% for the internal validation set. Statistically significant features were included in logistic models to predict RS ≤ 25 or ≤ 20. Another set was used for external validation to test reproducibility of prediction models. RESULTS The internal set included 407 patients. Mean (range) age was 53.7 (31-80) years, and 222 patients (54.55%) were > 50 years old. ODX results showed 67 patients (16.6%) had RS between 0 and 10, 272 patients between 11 and 25 (66.8%), and 68 patients > 26 (16.6%). Logistic regression analysis showed that RS score (for threshold ≤ 25) was significantly associated with estrogen receptor (P = .004), progesterone receptor (P < .0001), and Ki-67 (P < .0001). Generalized linear regression resulted in a model that had an area under the receiver operating characteristic curve (AUC) of 92.2 (sensitivity 84.2%, specificity 80.1%) and that was well calibrated. The external validation set (183 patients) analysis confirmed the model performance, with an AUC of 82.3 and a positive predictive value of 91%. A nomogram was generated for further prospective evaluation to predict RS ≤ 25. CONCLUSION RS was related to quantitative IHC in patients with RS ≤ 25, with a good performance of the statistical model in both internal and external validation. A nomogram for enhancing clinical approach in a cost-effective manner was developed. Prospective studies must test this application in clinical practice.
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Affiliation(s)
- Fabio Marazzi
- UOC di Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy
| | | | - Valeria Masiello
- UOC di Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy.
| | - Valentina Magri
- Breast Unit, Division of Medical Oncology, Department of Radiological Oncological and Pathological Sciences, "Sapienza" University of Rome, Rome, Italy
| | - Antonino Mulè
- UOC di Anatomia Patologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy
| | - Angela Santoro
- UOC di Anatomia Patologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy
| | - Federica Cacciatori
- UOC di Anatomia Patologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy
| | - Luca Boldrini
- UOC di Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy
| | - Gianluca Franceschini
- UOC di Chirurgia Senologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy; Università Cattolica del Sacro Cuore, Istituto di Radiologia, Rome, Italy
| | - Francesca Moschella
- UOC di Chirurgia Senologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy
| | - Giuseppe Naso
- Breast Unit, Division of Medical Oncology, Department of Radiological Oncological and Pathological Sciences, "Sapienza" University of Rome, Rome, Italy
| | - Silverio Tomao
- Breast Unit, Division of Medical Oncology, Department of Radiological Oncological and Pathological Sciences, "Sapienza" University of Rome, Rome, Italy
| | - Maria Antonietta Gambacorta
- UOC di Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy; Università Cattolica del Sacro Cuore, Istituto di Radiologia, Rome, Italy
| | - Giovanna Mantini
- UOC di Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy; Università Cattolica del Sacro Cuore, Istituto di Radiologia, Rome, Italy
| | - Riccardo Masetti
- UOC di Chirurgia Senologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy; Università Cattolica del Sacro Cuore, Istituto di Radiologia, Rome, Italy
| | - Daniela Smaniotto
- UOC di Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy; Università Cattolica del Sacro Cuore, Istituto di Radiologia, Rome, Italy
| | - Vincenzo Valentini
- UOC di Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Dipartimento di Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Rome, Italy; Università Cattolica del Sacro Cuore, Istituto di Radiologia, Rome, Italy
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Marazzi F, Masiello V, Barone R, Magri V, Mulé A, Santoro A, Cacciatori F, Boldrini L, Franceschini G, Moschella F, Naso G, Tomao S, Mantini G, Masetti R, Smaniotto D, Valentini V. OncotypeDX® predictive nomogram for recurrence score output: A machine learning system based on quantitative immunochemistry analysis - ADAPTED01. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz240.085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Marazzi F, Mulè A, Masiello V, Masetti R, Barone R, Franceschini G, Cacciatori F, Moschella F, Cannatà C, Boldrini L, Mantini G, Smaniotto D, Valentini V. EP-1325 Personalized Medicine in breast cancer: a nomogram from prognostic score to deescalate radiotherapy. Radiother Oncol 2019. [DOI: 10.1016/s0167-8140(19)31745-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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