Evidence map›Paper›PMID 35146793›Full record

ArticleStatistics in medicine2022

Shared decision making of burdensome surveillance tests using personalized schedules and their burden and benefit.

Anirudh Tomer, Daan Nieboer, Monique J Roobol, Ewout W Steyerberg, Dimitris Rizopoulos

Open access · hybridAbstract read
In one paragraph

Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Anirudh TomerDepartment of Biostatistics, Erasmus University Medical Center, Rotterdam, Zuid-Holland, The Netherlands.ORCID 0000-0002-6058-6715
Daan NieboerDepartment of Public Health, Erasmus University Medical Center, Rotterdam, Zuid-Holland, The Netherlands.
Monique J RoobolDepartment of Urology, Erasmus University Medical Center, Rotterdam, Zuid-Holland, The Netherlands.
Ewout W SteyerbergDepartment of Public Health, Erasmus University Medical Center, Rotterdam, Zuid-Holland, The Netherlands.ORCID 0000-0002-7787-0122
Dimitris RizopoulosDepartment of Biostatistics, Erasmus University Medical Center, Rotterdam, Zuid-Holland, The Netherlands.
Erasmus MC · NLLeiden University Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Benchmark surveillance tests for detecting disease progression (eg, biopsies, endoscopies) in early-stage chronic noncommunicable diseases (eg, cancer, lung diseases) are usually burdensome. For detecting progression timely, patients undergo invasive tests planned in a fixed one-size-fits-all manner (eg, annually). We aim to present personalized test schedules based on the risk of disease progression, that optimize the burden (the number of tests) and the benefit (shorter time delay in detecting progression is better) better than fixed schedules, and enable shared decision making. Our motivation comes from the problem of scheduling biopsies in prostate cancer surveillance. Using joint models for time-to-event and longitudinal data, we consolidate patients' longitudinal data (eg, biomarkers) and results of previous tests, into individualized future cumulative-risk of progression. We then create personalized schedules by planning tests on future visits where the predicted cumulative-risk is above a threshold (eg, 5% risk). We update personalized schedules with data gathered over follow-up. To find the optimal risk threshold, we minimize a utility function of the expected number of tests (burden) and expected time delay in detecting progression (shorter is beneficial) for different thresholds. We estimate these two in a patient-specific manner for following any schedule, by utilizing a patient's predicted risk profile. Patients/doctors can employ these quantities to compare personalized and fixed schedules objectively and make a shared decision of a test schedule.

Indexed as

Decision Making, SharedProstatic NeoplasmsBiopsyDecision MakingDisease ProgressionForecastingHumansMalechronic NCDsinvasive diagnostic testsjoint modelspersonalized schedulesshared decision making

Identifiers

PMID35146793
PMCPMC9305929
OpenAlexW4211174256

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.