Evidence map›Paper›PMID 29445516›Full record

ArticleBMJ innovations2017

Does this treatment work for me? The patient's role in assessing medical care.

Duncan V Neuhauser, Jennifer Chu

Abstract read
In one paragraph

Article in BMJ innovations, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Duncan V NeuhauserDepartment of Epidemiology and Biostatistic, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
Jennifer ChuDepartment of Physical Medicine and Rehabilitation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID 0000-0003-3065-9132

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Randomised clinical trials are designed to determine whether a particular treatment is appropriate to make a significant difference to the health of a defined population and to aid its approval for use. For an accurate, cheap and simple assessment to see if a treatment benefits an individual person, all that is needed is a pen, paper, simple pocket calculator and daily recording of a few variables. It requires the ability to read and write and to understand addition and division. Factorial design of experiments is used to show the impact of several variables and their interaction on the person's health status. An example of a 75-year-old man with an enlarged prostate is used here to illustrate this approach. This person was able to understand and reduce side effects, lower the costs of medication by 83% and improve measured health status by 28%. A multivariate model for this person was then created with about 450 person-days of data.

Indexed as

accessiblediagnosticsglobal healthreverse innovations

Identifiers

PMID29445516
PMCPMC5754871

What OpenQuestion holds

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LicenceCC BY-NC
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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.