Evidence map›Paper›PMID 23835712›Full record

ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2013

Challenges of guarantee-time bias.

Anita Giobbie-Hurder, Richard D Gelber, Meredith M Regan

Abstract read
In one paragraph

Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 206 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
206citing papers in PubMed, 3 pooled it
–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

206 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Long-Term Outcomes With Nivolumab Plus Ipilimumab or Nivolumab Alone Versus Ipilimumab in Patients With Advanced Melanoma.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
    Trial
  6. Trial
  7. Trial
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Metabolic response by FDG-PET to imatinib correlates with exon 11 KIT mutation and predicts outcome in patients with mucosal melanoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2014
    Trial
  14. Article
  15. Article
  16. Observational
  17. Observational
  18. Interpreting survival differences in head and neck squamous cell carcinoma of unknown primary: time-dependent treatment and biological selection.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Article
  19. Article
  20. Article

146 more citing papers are in PubMed but not listed here.

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

3 authors.

Anita Giobbie-HurderDana-Farber Cancer Institute, Boston, MA, USA. agiohur@jimmy.harvard.edu
Richard D Gelber
Meredith M Regan

Funding

IBCSG STATISTICAL CENTER--A BREAST CANCER STUDY RESOURCEU24CA075362 · NCI · DANA-FARBER CANCER INSTITUTE · PI REGAN, MEREDITH M · 1997 to 2015
$7.5M
NCI NIH HHS CA-75362NCI NIH HHS U24 CA075362
6 · The paper itself

Abstract

The potential for guarantee-time bias (GTB), also known as immortal time bias, exists whenever an analysis that is timed from enrollment or random assignment, such as disease-free or overall survival, is compared across groups defined by a classifying event occurring sometime during follow-up. The types of events associated with GTB are varied and may include the occurrence of objective disease response, onset of toxicity, or seroconversion. However, comparative analyses using these types of events as predictors are different from analyses using baseline characteristics that are specified completely before the occurrence of any outcome event. Recognizing the potential for GTB is not always straightforward, and it can be challenging to know when GTB is influencing the results of an analysis. This article defines GTB, provides examples of GTB from several published articles, and discusses three analytic techniques that can be used to remove the bias: conditional landmark analysis, extended Cox model, and inverse probability weighting. The strengths and limitations of each technique are presented. As an example, we explore the effect of bisphosphonate use on disease-free survival (DFS) using data from the BIG (Breast International Group) 1-98 randomized clinical trial. An analysis using a naive approach showed substantial benefit for patients who received bisphosphonate therapy. In contrast, analyses using the three methods known to remove GTB showed no statistical evidence of a reduction in risk of a DFS event with bisphosphonate therapy.

Indexed as

BiasAmenorrheaBreast NeoplasmsClinical Trials as TopicColorectal NeoplasmsDisease-Free SurvivalFemaleHumansMedical OncologyMutationProportional Hazards ModelsProto-Oncogene ProteinsProto-Oncogene Proteins p21(ras)Randomized Controlled Trials as Topicras ProteinsResearch DesignKRAS protein, humanProto-Oncogene ProteinsProto-Oncogene Proteins p21(ras)ras Proteins

Identifiers

PMID23835712
PMCPMC3732313

What OpenQuestion holds

Textmetadata
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.