Evidence map›Paper›PMID 32535486›Full record

Trial reportBreast (Edinburgh, Scotland)2020

Estimation of historical control rate for a single arm de-escalation study - Application to the POSITIVE trial.

Zhuoxin Sun, Samuel M Niman, Olivia Pagani, Ann H Partridge, Hatem A Azim, Fedro A Peccatori, Monica Ruggeri, Angelo Di Leo, Marco Colleoni, Richard D Gelber and 2 more

Abstract readClinical Trial
In one paragraph

Trial report in Breast (Edinburgh, Scotland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Zhuoxin SunInternational Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, 02215, USA. Electronic address: zhuoxin@jimmy.harvard.edu.
Samuel M NimanInternational Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, 02215, USA. Electronic address: sniman@jimmy.harvard.edu.
Olivia PaganiInstitute of Oncology of Southern Switzerland, Geneva University Hospitals, Swiss Group for Clinical Cancer Research (SAKK), Lugano Viganello, Switzerland. Electronic address: opagani@bluewin.ch.
Ann H PartridgeMedical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA. Electronic address: ahpartridge@partners.org.
Hatem A AzimBreast Cancer Center, Hospital Zambrano Hellion, School of Medicine, Tecnologico de Monterrey, Av. Batallon de San Patricio 112, 66278, San Pedro Garza Garcia, Mexico. Electronic address: hatem.azim@gmail.com.
Fedro A PeccatoriFertility and Procreation Unit, Gynecologic Oncology Program, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy. Electronic address: fedro.peccatori@ieo.it.
Monica RuggeriInternational Breast Cancer Study Group, Program for Young Patients, Coordinating Center, Effingerstrasse 40, 3008, Bern, Switzerland. Electronic address: monica.ruggeri@ibcsg.org.
Angelo Di Leo"Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Via Suor Niccolina 20, Prato, 59100, Italy. Electronic address: angelo.dileo@uslcentro.toscana.it.
Marco ColleoniDivision of Medical Senology, IEO, European Institute of Oncology, IRCCS, Milan, Italy. Electronic address: marco.colleoni@ieo.it.
Richard D GelberInternational Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, Harvard Medical School, Harvard TH Chan School of Public Health, And Frontier Science and Technology Research Foundation, 450 Brookline Ave, Boston, MA, 02215, USA. Electronic address: gelber@jimmy.harvard.edu.
Meredith M ReganInternational Breast Cancer Study Group Statistical Center, Department of Data Sciences, Division of Biostatistics, Dana-Farber Cancer Institute, Harvard Medical School, 450 Brookline Ave, Boston, MA, 02215, USA. Electronic address: mregan@jimmy.harvard.edu.
POSITIVE Steering Committee

Funding

NCTN Lead Academic Participating Site at Dana-Farber/Partners Cancer CareUG1CA233180 · NCI · DANA-FARBER CANCER INST · PI Harold John Burstein · 2019 to 2026
$8.6M
NCI NIH HHS UG1 CA233180
6 · The paper itself

Abstract

backgroundAlthough randomized controlled clinical trials are optimal to evaluate the effect of an experimental therapy, single-arm trials are required whenever randomization is unethical or not feasible, such as de-escalation studies. We propose using prospectively identified historical controls to place results of single-arm, de-escalation trials into context.

methodsPOSITIVE is a prospective, single-arm study in young women with hormone-receptor-positive early breast cancer to determine if temporarily interrupting adjuvant endocrine therapy in order to become pregnant increases the risk of a breast cancer event. After 272 women enrolled in POSITIVE, we identified a cohort of 1499 SOFT/TEXT patients potentially eligible to enroll in POSITIVE who did not interrupt endocrine therapy. Method I used the SOFT/TEXT cohort to calculate annualized hazard rates by a piecewise exponential model. Method II used the SOFT/TEXT cohort to group-match SOFT/TEXT patients to POSITIVE patients; sample sets of SOFT/TEXT patients were randomly drawn 5000 times to obtain sets having patient, disease, and treatment characteristics more balanced with POSITIVE participants.

resultsCompared with SOFT/TEXT, POSITIVE participants were younger, less likely to be overweight/obese, had fewer positive nodes, and fewer received aromatase inhibitor or chemotherapy. The estimated 3-year breast cancer free interval event rates were 9.5% (95% CI: 7.9%,11.1%) for Method I and 9.4% (95% CI: 7.8%,10.9%) for Method II, compared with 5.8% initially assumed when POSITIVE was designed.

conclusionExternal control datasets should be identified before launching single-arm, de-escalation trials and methods applied during their conduct to provide context for interim monitoring and interpretation of the final analysis.

Indexed as

AdolescentAdultAntineoplastic Agents, HormonalBreast NeoplasmsChemotherapy, AdjuvantErb-b2 Receptor Tyrosine KinasesFemaleHistorically Controlled StudyHumansKaplan-Meier EstimateNon-Randomized Controlled Trials as TopicPregnancyProportional Hazards ModelsProspective StudiesRandomized Controlled Trials as TopicWithholding TreatmentAntineoplastic Agents, HormonalErb-b2 Receptor Tyrosine Kinases

Identifiers

PMID32535486
PMCPMC7375555

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.