Comparing Decision on Aesthetics After Breast Cancer Locoregional Treatment. (CINDERELLA)

Comparing Decision on Match of Expectations and Aesthetics Using a Conventional Versus a Cloud-based Healthcare Platform Approach in Breast Cancer Patients Proposed for Locoregional Treatment: A Prospective Randomized Trial

Breast cancer is the most commonly diagnosed cancer, with an estimated 2.3 million new cases per year globally. Approximately 90% of these patients will undergo breast surgery with/without radiation (locoregional treatment). Different surgical techniques can be offered to the patient, each leading to completely different aesthetic outcomes. Moreover, the aesthetic outcome could be completely different for patients undergoing the same surgery based on individual patient factors (e.g., age, body habitus). In the CINDERELLA trial, the investigators will be using the (Breast Locoregional (BreLO) AI system (an artificial intelligence-based tool for the classification of aesthetic outcomes and matching data and photographs) integrated into CANKADO (a cloud-based healthcare platform) to create an easy-to-use application that can be used on any electronic device, to simulate visually to the patient the aesthetic outcome of a certain surgery or radiation treatment. In the CINDERELLA trial, the investigators plan to compare whether the application helped fulfil the expectations and lead to a better quality of life compared with the classical approach. In the classical approach (control arm), doctors usually propose a locoregional treatment and explain theoretically how the result will be. Nurses help by explaining further details about the surgery and possible outcomes. In most centres, no photographic evaluation is done, and expectations are not measured. The CINDERELLA trial will help overcome miscommunication and potential boundaries in the patient's or physician's understanding of the potential outcomes of locoregional breast cancer treatment.

Study Overview

• Status: Recruiting
• Conditions: Breast Cancer
• Intervention / Treatment: Device: Artificial Intelligence and Digital Health Arm

Detailed Description

The CINDERELLA clinical trial will be an open, prospective randomized trial that Champalimaud Foundation will coordinate. Five clinical centres agreed to participate in the trial. The trial will be designed and reported according to the latest SPIRIT-AI and CONSORT-AI guidelines.

The randomization will be made by adopting a dynamical approach following the Minimization Method. Assignment of the recruited patients to the study arms will take into account the stratification of the participants (younger and older than 50 / breast-conserving or mastectomy / mastectomy with or without radiotherapy), aiming to reduce bias and confounding by assuring the balance of the group.

After being proposed to the trial and checked for all the eligibility criteria, patients will be given the complete patient information before signing the informed consent.

For the five centres, a minimum of 515 patients should be enrolled in each arm of the study. After randomization, the patient will either follow:

1. - The intervention arm with the CINDERELLA APProach with the introduction and access to CANKADO with the BreLO AI system. The Expectations Questionnaire, Healthcare Professionals Multidimensional Evaluation Questionnaire and standard patient-reported outcomes measures (PROMs) (EQ-5D-5L and BREAST Q ICHOM) will be filed electronically. Standard photographic capture will be taken at this point. After the photographic capture, the BreLO-AI will match the patient biometrics and images with the more identical case existing in the BreLO repository and already classified by the BCCT.core into excellent, good, fair and poor. The new patient can then visualize the results. In case of doubts, queries will be answered through the app or, if needed, by phone call or booking another appointment. Questionnaires and Photographs will be repeated after wound healing is complete, six months and one year after the end of treatment (surgery or radiotherapy if radiotherapy was done).
2. - The control arm with the Conventional approach with a theoretical explanation by the doctor/nurse of the proposed locoregional treatment and possible outcomes. The Expectations Questionnaire, Healthcare Professionals Multidimensional Evaluation Questionnaire and standard PROMs (EQ-5D-5L and BREAST Q ICHOM) will be filed electronically. Standard photographic capture will be taken at this point. In case of doubts, the patient will book another appointment with the doctor/nurse, as usually done in routine practice. Questionnaires and Photographs will be repeated after healing is complete, six months and one year after the end of treatment (surgery or radiotherapy if radiotherapy was done).

Digital Photography (same protocol for all participating centres) - a similar protocol for image capture will exist for all centres. The standalone photography with an automatic robot will be progressively implemented (www.photorobot.com).

DATA COLLECTION

PATIENT-RELATED FACTORS

• Date of birth, Weight / Height / BMI, Thoracic perimeter, Bra size and cup
• Education degree, Profession, Hobbies
• Marital status, Pregnancies and offspring
• Breast-feeding, Menopausal status
• Smoking
• Connective tissue diseases
• Confirmed Pathogenic Germline Variant

TUMOUR-RELATED FACTORS

• Unilateral (unifocal, multifocal, multicentric) Bilateral
• Histological type according to World Health Organization (WHO) classification (e.g., invasive ductal carcinoma, lobular carcinoma) (size in mm) staging ER, PR, Her2, Ki67, cTNM - pTNM / ypTNM

TREATMENT-RELATED FACTORS

*Type of Surgery/ Type of Reconstruction: (data collection regarding surgery should also include acellular dermal matrice (ADM) if used - type and placement) TYPE OF SURGERY: C1 - Conservative surgery - unilateral or bilateral, C2 - Conservative surgery with bilateral reduction (uni or bilateral), C3 - Conservative surgery with LD or LICAP/TDAP, C4 - Conservative surgery with bilateral breast augmentation, M1 - Mastectomy with unilateral reconstruction with implant, M2 - Mastectomy with unilateral reconstruction with autologous flap, M3 - Mastectomy with bilateral reconstruction with implants, M4 - Mastectomy with bilateral reconstruction with autologous flaps, M5 - Mastectomy with unilateral reconstruction with implant and contralateral symmetrisation with implant (augmentation), M6 - Mastectomy with unilateral reconstruction with implant and contralateral symmetrisation with reduction, M7 - Mastectomy with unilateral reconstruction with autologous flap and contralateral symmetrisation with reduction, M8 - Mastectomy with unilateral reconstruction with autologous flap and contralateral symmetrisation with implant (augmentation).

STATISTICAL ANALYSIS

An extensive descriptive analysis will be performed to characterize the groups in detail and the outcomes of the study at baseline as well as in the following points of data collection. Concerning the primary objectives, models of the class of generalized linear mixed models (in particular, multinomial regression models for ordinal data) will be estimated to evaluate the effect of the training and the women's characteristics on their evaluation of the aesthetic results of the surgery at each time and along time through longitudinal analysis. The Wilcoxon signed rank test for pairs will also be used to evaluate the effect of training on the level of agreement of the expectations and the final result. Weighted Cohen's k will be calculated for both groups (train and control) and compared using a statistical test and/or bootstrap techniques to assess the improvement in the ability to classify the aesthetic result of their surgery provided by training. A measure of similarity between self-evaluation and the BCCT.core will be computed for each participant, and a beta regression model will be estimated to assess the effect of training, controlling variables that can play as confounders, such as women's and disease characteristics at each time point and in a longitudinal perspective. Concerning the secondary objectives, the patient-reported outcome measures administered will be scored according to the official guidelines provided by the developers of the instruments. Besides the descriptive statistics, the outcomes will be compared between groups using adequate statistical tests. Again, models of the class of the general linear mixed models will be used.

• Study Type: Interventional
• Enrollment (Estimated): 1030
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Maria-Joao Cardoso, MD, PhD; Phone Number: +351 966484826; Email: maria.joao.cardoso@fundacaochampalimaud.pt

Study Locations

• Germany
  • Heidelberg, Germany, 69120
    • Recruiting
    • Universitätsklinikum Heidelberg
    • Contact: Martina Manns; Phone Number: +49 6221 568438; Email: Martina.Manns@med.uni-heidelberg.de
    • Principal Investigator: Joerg Heil, MD, PhD
• Israel
  • Ramat Gan, Israel, 52621
    • Recruiting
    • Sheba Medical Center
    • Contact: Michaela Ofir; Email: michaela.smiloviciofir@sheba.health.gov.il
    • Principal Investigator: Orit Kaidar-Person, MD, PhD
    • Sub-Investigator: Dov Zippel
    • Sub-Investigator: Nama Hermann
    • Sub-Investigator: Josef Haik
• Italy
  • Milano, Italy, 20132
    • Recruiting
    • IRCCS Ospedale San Raffaele
    • Contact: Thierry Touvier; Email: touvier.thierry@hsr.it
    • Principal Investigator: Oreste Gentilini, MD, PhD
    • Sub-Investigator: Rosa di Mico
• Poland
  • Pomeranian
    • Gdańsk, Pomeranian, Poland, 80-210
      • Recruiting
      • Copernicus Mamma Centrum, Wojewodzkie Centrum Onkologii, Copernicus Podmiot Leczniczy
      • Principal Investigator: Pawel Kabata, MD, PhD
      • Contact: Pawel Kabata, MD, PhD; Email: pawel.kabata@iplpk.onmicrosoft.com
    • Gdańsk, Pomeranian, Poland, 80-210
      • Recruiting
      • Gdanski Uniwersytet Medyczny
      • Principal Investigator: Maciej Bobowicz, MD, PhD
      • Contact: Mateusz Kirjak; Email: m.kirjak@gumed.edu.pl
      • Sub-Investigator: Elzbieta Senkus-Konefka, MD, PhD
• Portugal
  • Lisboa, Portugal, 1400-038
    • Recruiting
    • Champalimaud Research and Clinical Centre, Champalimaud Foundation
    • Contact: Maria-Joao Cardoso, MD, PhD; Email: maria.joao.cardoso@fundacaochampalimaud.pt
    • Contact: Eduard-Alexandru Bonci, MD, PhD; Email: eduard.bonci@research.fchampalimaud.org
    • Principal Investigator: Maria-Joao Cardoso, MD, PhD
    • Sub-Investigator: Carlos Mavioso, MD
    • Sub-Investigator: Pedro Gouveia, MD, PhD
    • Sub-Investigator: David Pinto, MD
    • Sub-Investigator: Rogelio Andrés-Luna, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion :

• More than 18 years old
• Written informed consent
• Primary breast cancer in situ or invasive without evidence of systemic disease - non Stage IV or locally advanced non-operable breast cancer.
• Eastern Cooperative Oncology Group (ECOG) performance status 0 or 1
• Uni or Bilateral surgery even if prophylactic in one side
• Capacity to use a web-based app autonomously or with home-based support

Exclusion:

• Mastectomy without reconstruction
• Pregnancy or lactation
• Previous radiation to breast/chest (e.g., lymphoma)
• Previous ipsilateral breast surgery due to malignant disease.
• Other neoplasm in the last 5 years (excluding basal cell carcinoma of the skin and adequately treated carcinoma in situ of the cervix)
• Severe skin disease that will contra-indicate the use of radiotherapy
• Prophylactic surgery

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Artificial Intelligence and Digital Health Arm; Using an Artificial Intelligence approach integrated in a cloud-based healthcare platform CANKADO to give the patient complete information about the proposed type of locoregional treatment and access to photographs and data of patients with similar characteristics previously treated with the same technique. All interaction will be through the CANKADO Platform.	Device: Artificial Intelligence and Digital Health Arm; A previous large database repository of images having thousands of pre and postoperative photographs of breast cancer patients proposed for locoregional treatment with clinical and biometric data will be matched using artificial intelligence within the CANKADO platform. Patients proposed for breast cancer locoregional treatment will have access to the software installed, and they will have access to all the information about the type of treatment they will receive. All the questions and questionnaires will be filled out online, and they can visualise the expected outcome from excellent to poor.; Other Names: Artificial Intelligence and cloud-based digital health platform
Other: Control Comparator; The standard approach of proposing patients for locoregional treatment with or without printed or digital materials and hypothetic visualization of results.	Device: Artificial Intelligence and Digital Health Arm; A previous large database repository of images having thousands of pre and postoperative photographs of breast cancer patients proposed for locoregional treatment with clinical and biometric data will be matched using artificial intelligence within the CANKADO platform. Patients proposed for breast cancer locoregional treatment will have access to the software installed, and they will have access to all the information about the type of treatment they will receive. All the questions and questionnaires will be filled out online, and they can visualise the expected outcome from excellent to poor.; Other Names: Artificial Intelligence and cloud-based digital health platform

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Agreement about the aesthetic outcome between the objective evaluation and self- evaluation measured after treatment in both the intervention and the control arm	Agreement about the aesthetic outcome between the AI evaluation tool (BCT.core software) and self- evaluation after treatment (Cohen's Kappa and weighted Kappa Statistics) in both the intervention and the control arm.	12 months after locoregional treatment (surgery or radiotherapy in case adjuvant radiotherapy is done)
Agreement between patients expectations before and after treatment in both the intervention and the control arm	Agreement between patient's expectations about the aesthetic outcome measured before and after treatment, evaluated at 12 months after treatment (Cohen's Kappa and weighted Kappa Statistics) both the intervention and the control arm.	12 months after locoregional treatment (surgery or radiotherapy in case adjuvant radiotherapy is done)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Patient's body image satisfaction after surgery measured through the BREAST-Q - International Consortium for Health Outcomes Measurement (ICHOM) questionnaire	Body image perception and satisfaction using the BREAST-Q ICHOM questionnaire. The scale scores from 0 lowest to 100 highest (body image satisfaction) in both the intervention and the control arm.	12 months after locoregional treatment (surgery or radiotherapy in case adjuvant radiotherapy is done)
Resource consumption a) time spent in hospital b) number of appointments c) duration until treatment d) out of pocket expenditure, additional care sought by patients	Resource consumption (cost per patient evaluated by the amount of appointments between the surgical proposal by the surgeon and the end of the trial) in both the intervention and control arm.	12 months after locoregional treatment (surgery or radiotherapy in case adjuvant radiotherapy is done
Patient's general health-related quality of life evaluated in both the intervention and control arm with the EQ-5D-5L questionnaire	How results impact in patients general quality of life evaluated in both the intervention and control arm with the EQ-5D-5L questionnaire. The scale scores from 0 lowest to 100 highest. A high scale score represents a high/healthy level of functioning.	12 months after locoregional treatment (surgery or radiotherapy in case adjuvant radiotherapy is done)

Collaborators and Investigators

• Sponsor: Fundacao Champalimaud
• Collaborators: European Commission; Cankado GmbH; Bocconi University; INESC TEC - Institute for Systems and Computer Engineering, Technology and Science (Porto, Portugal); FCiências.ID - Associação para a Investigação e Desenvolvimento de Ciências (Lisbon, Portugal)
• Investigators: Principal Investigator: Maria-Joao Cardoso, PhD, Champalimaud Foundation

Publications and helpful links

General Publications

• Fisher B, Anderson S, Bryant J, Margolese RG, Deutsch M, Fisher ER, Jeong JH, Wolmark N. Twenty-year follow-up of a randomized trial comparing total mastectomy, lumpectomy, and lumpectomy plus irradiation for the treatment of invasive breast cancer. N Engl J Med. 2002 Oct 17;347(16):1233-41. doi: 10.1056/NEJMoa022152.
• Veronesi U, Cascinelli N, Mariani L, Greco M, Saccozzi R, Luini A, Aguilar M, Marubini E. Twenty-year follow-up of a randomized study comparing breast-conserving surgery with radical mastectomy for early breast cancer. N Engl J Med. 2002 Oct 17;347(16):1227-32. doi: 10.1056/NEJMoa020989.
• Pusic AL, Klassen AF, Scott AM, Klok JA, Cordeiro PG, Cano SJ. Development of a new patient-reported outcome measure for breast surgery: the BREAST-Q. Plast Reconstr Surg. 2009 Aug;124(2):345-353. doi: 10.1097/PRS.0b013e3181aee807.
• Cardoso JS, Cardoso MJ. Towards an intelligent medical system for the aesthetic evaluation of breast cancer conservative treatment. Artif Intell Med. 2007 Jun;40(2):115-26. doi: 10.1016/j.artmed.2007.02.007. Epub 2007 Apr 8.
• Harris JR, Levene MB, Svensson G, Hellman S. Analysis of cosmetic results following primary radiation therapy for stages I and II carcinoma of the breast. Int J Radiat Oncol Biol Phys. 1979 Feb;5(2):257-61. doi: 10.1016/0360-3016(79)90729-6. No abstract available.
• Pilleron S, Soto-Perez-de-Celis E, Vignat J, Ferlay J, Soerjomataram I, Bray F, Sarfati D. Estimated global cancer incidence in the oldest adults in 2018 and projections to 2050. Int J Cancer. 2021 Feb 1;148(3):601-608. doi: 10.1002/ijc.33232. Epub 2020 Aug 17.
• Kim MK, Kim T, Moon HG, Jin US, Kim K, Kim J, Lee JW, Kim J, Lee E, Yoo TK, Noh DY, Minn KW, Han W. Effect of cosmetic outcome on quality of life after breast cancer surgery. Eur J Surg Oncol. 2015 Mar;41(3):426-32. doi: 10.1016/j.ejso.2014.12.002. Epub 2014 Dec 19.
• Zehra S, Doyle F, Barry M, Walsh S, Kell MR. Health-related quality of life following breast reconstruction compared to total mastectomy and breast-conserving surgery among breast cancer survivors: a systematic review and meta-analysis. Breast Cancer. 2020 Jul;27(4):534-566. doi: 10.1007/s12282-020-01076-1. Epub 2020 Mar 12.
• Ong WL, Schouwenburg MG, van Bommel ACM, Stowell C, Allison KH, Benn KE, Browne JP, Cooter RD, Delaney GP, Duhoux FP, Ganz PA, Hancock P, Jagsi R, Knaul FM, Knip AM, Koppert LB, Kuerer HM, McLaughin S, Mureau MAM, Partridge AH, Reid DP, Sheeran L, Smith TJ, Stoutjesdijk MJ, Vrancken Peeters MJTFD, Wengstrom Y, Yip CH, Saunders C. A Standard Set of Value-Based Patient-Centered Outcomes for Breast Cancer: The International Consortium for Health Outcomes Measurement (ICHOM) Initiative. JAMA Oncol. 2017 May 1;3(5):677-685. doi: 10.1001/jamaoncol.2016.4851.
• Ciani O, Federici CB. Value Lies in the Eye of the Patients: The Why, What, and How of Patient-reported Outcomes Measures. Clin Ther. 2020 Jan;42(1):25-33. doi: 10.1016/j.clinthera.2019.11.016. Epub 2020 Jan 10.
• Fitzal F, Krois W, Trischler H, Wutzel L, Riedl O, Kuhbelbock U, Wintersteiner B, Cardoso MJ, Dubsky P, Gnant M, Jakesz R, Wild T. The use of a breast symmetry index for objective evaluation of breast cosmesis. Breast. 2007 Aug;16(4):429-35. doi: 10.1016/j.breast.2007.01.013. Epub 2007 Mar 26.
• Cardoso MJ, Cardoso J, Amaral N, Azevedo I, Barreau L, Bernardo M, Christie D, Costa S, Fitzal F, Fougo JL, Johansen J, Macmillan D, Mano MP, Regolo L, Rosa J, Teixeira L, Vrieling C. Turning subjective into objective: the BCCT.core software for evaluation of cosmetic results in breast cancer conservative treatment. Breast. 2007 Oct;16(5):456-61. doi: 10.1016/j.breast.2007.05.002. Epub 2007 Jul 2.
• Heil J, Dahlkamp J, Golatta M, Rom J, Domschke C, Rauch G, Cardoso MJ, Sohn C. Aesthetics in breast conserving therapy: do objectively measured results match patients' evaluations? Ann Surg Oncol. 2011 Jan;18(1):134-8. doi: 10.1245/s10434-010-1252-4. Epub 2010 Aug 10.
• Cardoso MJ, Cardoso JS, Oliveira HP, Gouveia P. The breast cancer conservative treatment. Cosmetic results - BCCT.core - Software for objective assessment of esthetic outcome in breast cancer conservative treatment: A narrative review. Comput Methods Programs Biomed. 2016 Apr;126:154-9. doi: 10.1016/j.cmpb.2015.11.010. Epub 2015 Dec 9.
• Cardoso JS, Silva W, Cardoso MJ. Evolution, current challenges, and future possibilities in the objective assessment of aesthetic outcome of breast cancer locoregional treatment. Breast. 2020 Feb;49:123-130. doi: 10.1016/j.breast.2019.11.006. Epub 2019 Nov 21.
• Ciani O, Salcher-Konrad M, Meregaglia M, Smith K, Gorst SL, Dodd S, Williamson PR, Fattore G. Patient-reported outcome measures in core outcome sets targeted overlapping domains but through different instruments. J Clin Epidemiol. 2021 Aug;136:26-36. doi: 10.1016/j.jclinepi.2021.03.003. Epub 2021 Mar 6.
• van Egdom LSE, Pusic A, Verhoef C, Hazelzet JA, Koppert LB. Machine learning with PROs in breast cancer surgery; caution: Collecting PROs at baseline is crucial. Breast J. 2020 Jun;26(6):1213-1215. doi: 10.1111/tbj.13804. Epub 2020 Mar 11.
• Pfob A, Sidey-Gibbons C, Schuessler M, Lu SC, Xu C, Dubsky P, Golatta M, Heil J. Contrast of Digital and Health Literacy Between IT and Health Care Specialists Highlights the Importance of Multidisciplinary Teams for Digital Health-A Pilot Study. JCO Clin Cancer Inform. 2021 Jun;5:734-745. doi: 10.1200/CCI.21.00032.
• Brunet J, Price J. A scoping review of measures used to assess body image in women with breast cancer. Psychooncology. 2021 May;30(5):669-680. doi: 10.1002/pon.5619. Epub 2021 Jan 21.
• Flitcroft K, Brennan M, Spillane A. Women's expectations of breast reconstruction following mastectomy for breast cancer: a systematic review. Support Care Cancer. 2017 Aug;25(8):2631-2661. doi: 10.1007/s00520-017-3712-x. Epub 2017 May 4.
• Fuzesi S, Becetti K, Klassen AF, Gemignani ML, Pusic AL. Expectations of breast-conserving therapy: a qualitative study. J Patient Rep Outcomes. 2019 Dec 27;3(1):73. doi: 10.1186/s41687-019-0167-5.
• Biganzoli L, Marotti L, Hart CD, Cataliotti L, Cutuli B, Kuhn T, Mansel RE, Ponti A, Poortmans P, Regitnig P, van der Hage JA, Wengstrom Y, Rosselli Del Turco M. Quality indicators in breast cancer care: An update from the EUSOMA working group. Eur J Cancer. 2017 Nov;86:59-81. doi: 10.1016/j.ejca.2017.08.017. Epub 2017 Sep 28.
• Cano SJ, Klassen AF, Scott AM, Pusic AL. A closer look at the BREAST-Q((c)). Clin Plast Surg. 2013 Apr;40(2):287-96. doi: 10.1016/j.cps.2012.12.002.
• Preuss J, Lester L, Saunders C. BCCT.core - can a computer program be used for the assessment of aesthetic outcome after breast reconstructive surgery? Breast. 2012 Aug;21(4):597-600. doi: 10.1016/j.breast.2012.05.012. Epub 2012 Jun 17.
• Berger VW, Bour LJ, Carter K, Chipman JJ, Everett CC, Heussen N, Hewitt C, Hilgers RD, Luo YA, Renteria J, Ryeznik Y, Sverdlov O, Uschner D; Randomization Innovative Design Scientific Working Group. A roadmap to using randomization in clinical trials. BMC Med Res Methodol. 2021 Aug 16;21(1):168. doi: 10.1186/s12874-021-01303-z.

Study record dates

Study Major Dates

• Study Start (Actual): August 8, 2023
• Primary Completion (Estimated): December 1, 2024
• Study Completion (Estimated): December 1, 2025

Study Registration Dates

• First Submitted: October 26, 2021
• First Submitted That Met QC Criteria: January 18, 2022
• First Posted (Actual): January 19, 2022

Study Record Updates

• Last Update Posted (Actual): March 21, 2024
• Last Update Submitted That Met QC Criteria: March 20, 2024
• Last Verified: March 1, 2024

More Information

Terms related to this study

• Keywords: Surgery; Quality of life; Satisfaction; Breast cancer; Outcomes; Artificial Intelligence; Expectations; Radiation; Aesthetics; Digital Platform
• Additional Relevant MeSH Terms: Skin Diseases; Neoplasms; Neoplasms by Site; Breast Diseases; Breast Neoplasms
• Other Study ID Numbers: CINDERELLA

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No