Evidence map›Paper›PMID 24320166›Full record

ArticleThe Milbank quarterly2013

The Lake Wobegon effect: are all cancer patients above average?

Jacqueline H Wolf, Kevin S Wolf

Open access · bronzeAbstract readPersonal Narrative
In one paragraph

Article in The Milbank quarterly, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

5 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jacqueline H WolfOhio University.
Kevin S Wolf
Ohio University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextWhen elderly patients face a terminal illness such as lung cancer, most are unaware that what we term in this article "the Lake Wobegon effect" taints the treatment advice imparted to them by their oncologists. In framing treatment plans, cancer specialists tend to intimate that elderly patients are like the children living in Garrison Keillor's mythical Lake Wobegon: above average and thus likely to exceed expectations. In this article, we use the story of our mother's death from lung cancer to investigate the consequences of elderly people's inability to reconcile the grave reality of their illness with the overly optimistic predictions of their physicians.

methodsIn this narrative analysis, we examine the routine treatment of elderly, terminally ill cancer patients through alternating lenses: the lens of a historian of medicine who also teaches ethics to medical students and the lens of an actuary who is able to assess physicians' claims for the outcome of medical treatments.

findingsWe recognize that a desire to instill hope in patients shapes physicians' messages. We argue, however, that the automatic optimism conveyed to elderly, dying patients by cancer specialists prompts those patients to choose treatment that is ineffective and debilitating. Rather than primarily prolong life, treatments most notably diminish patients' quality of life, weaken the ability of patients and their families to prepare for their deaths, and contribute significantly to the unsustainable costs of the U.S. health care system.

conclusionsThe case described in this article suggests how physicians can better help elderly, terminally ill patients make medical decisions that are less damaging to them and less costly to the health care system.

Indexed as

AgedAged, 80 and overCarcinoma, Non-Small-Cell LungFemaleHumansLung NeoplasmsNeoplasmsPalliative CarePhysician-Patient RelationsTerminal CareTreatment Outcomeend-of-life carehospiceNSCLC treatmentphysician/patient communication

Identifiers

PMID24320166
PMCPMC3876187
OpenAlexW2100755190

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.