Evidence map›Paper›PMID 27034177›Full record

ArticleInternational journal of radiation oncology, biology, physics2016

Comparison of Mammographic Changes Across Three Different Fractionation Schedules for Early-Stage Breast Cancer.

Sibo Tian, Lina F Paster, Sinae Kim, Laurie Kirstein, Bruce G Haffty, Adam Ferro, Judith Amorosa, Sharad Goyal

Abstract readComparative Study
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 29% of its field
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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
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

8 authors at 1 institution in 2 countries.

Sibo TianDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey and Rutgers Robert Wood Johnson Medical School, Rutgers, New Jersey.
Lina F PasterDepartment of Radiology, Rutgers Robert Wood Johnson Medical School, Rutgers, New Jersey.
Sinae KimBiometrics Division, Rutgers Cancer Institute of New Jersey, and Department of Biostatistics, Rutgers School of Public Health, Rutgers, New Jersey.
Laurie KirsteinDivision of Surgical Oncology, Rutgers Cancer Institute of New Jersey and Rutgers Robert Wood Johnson Medical School, Rutgers, New Jersey.
Bruce G HafftyDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey and Rutgers Robert Wood Johnson Medical School, Rutgers, New Jersey.
Adam FerroDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey and Rutgers Robert Wood Johnson Medical School, Rutgers, New Jersey.
Judith AmorosaDepartment of Radiology, Rutgers Robert Wood Johnson Medical School, Rutgers, New Jersey.
Sharad GoyalDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey and Rutgers Robert Wood Johnson Medical School, Rutgers, New Jersey. Electronic address: goyalsh@rutgers.edu.
Rutgers, The State University of New Jersey · US

Funding

TRANSCRIPTIONAL PROFILINGP30CA072720 · NCI · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI Shridar Ganesan · 1997 to 2026
$94.5M
NCI NIH HHS P30 CA072720
6 · The paper itself

Abstract

purposeAs the use of hypofractionated breast radiation therapy (RT) increases, so will the need for long-term data on post-RT mammographic changes. The purpose of the present study was to longitudinally compare the incidence of common mammographic sequelae seen after breast conserving surgery and RT in patients treated with accelerated partial breast irradiation (APBI), hypofractionated whole breast irradiation (HWBI), and conventionally fractionated whole breast irradiation (WBI). METHODS AND MATERIALS: Patients treated with either APBI or HWBI after breast conserving therapy and with ≥3 mammograms of the treated breast were identified. They were matched 1:1 by age ±5 years to patients treated with WBI. The mammograms were evaluated for common post-RT breast findings by a mammographer who was unaware of the treatment. The outcomes were analyzed using a cumulative logistic regression model; P<.05 indicated statistically significance.

resultsOf 89 patients treated with RT from 2006 to 2011, 29 had received APBI, 30 had received HWBI, and 30 had received WBI. Their median age was 60 years (range 33-83). A total of 605 mammograms were evaluated, with a median follow-up of 48 months. The treatment technique did not affect the severity of architectural distortion when the groups were evaluated longitudinally. The likelihood of finding skin thickening decreased with increasing follow-up duration (odds ratio 0.6; P<.001) adjusted for fractionation schemes. No differences were seen with respect to changes in skin thickening, fluid collections, or calcifications among the treatment groups, after adjustment for the follow-up time. The clinical characteristics, including age, race, T stage, and chemotherapy use, were not linked to the likelihood of finding several mammographic phenomena over time.

conclusionsAlthough specific post-treatment imaging findings evolved over time, RT fractionation did not alter the relative incidence or severity of architectural distortion, skin thickening, fluid collections, or calcifications. These findings will be useful to both radiologists and radiation oncologists when counseling patients regarding follow-up studies after RT.

Indexed as

Dose Fractionation, RadiationMammographyAdultAgedAged, 80 and overBreast NeoplasmsFemaleHumansLogistic ModelsMiddle AgedNeoplasm Staging

Identifiers

PMID27034177
PMCPMC5767466
OpenAlexW2256202869

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.