Evidence map›Paper›PMID 37753320›Full record

ReviewJournal of hospice and palliative care2023

Prediction of Survival in Patients with Advanced Cancer: A Narrative Review and Future Research Priorities.

Yusuke Hiratsuka, Jun Hamano, Masanori Mori, Isseki Maeda, Tatsuya Morita, Sang-Yeon Suh

Open access · diamondAbstract readReview
In one paragraph

Review in Journal of hospice and palliative care, 2023. 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
1.7field-weighted citation impact, top 17% 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, 6 citations in OpenAlex.

  1. Article
  2. When would I be surprised? Variability in predicted probability of survival for being "surprised" and "not surprised" to the surprise question.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  3. Review
  4. Review
  5. 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

6 authors at 4 institutions in 2 countries.

Yusuke HiratsukaDepartment of Palliative Medicine, Takeda General Hospital, Aizu Wakamatsu, Japan.ORCID https://orcid.org/0000-0003-2334-3893
Jun HamanoDepartment of Palliative and Supportive Care, Institute of Medicine, University of Tsukuba, Tsukuba, Japan.ORCID https://orcid.org/0000-0003-0304-9881
Masanori MoriDepartment of Palliative and Supportive Care, Seirei Mikatahara General Hospital, Hamamatsu, Japan.ORCID https://orcid.org/0000-0002-5489-9395
Isseki MaedaDepartment of Palliative Care, Senri Chuo Hospital, Toyonaka, Japan.ORCID https://orcid.org/0000-0002-0018-3359
Tatsuya MoritaDepartment of Palliative and Supportive Care, Seirei Mikatahara General Hospital, Hamamatsu, Japan.ORCID https://orcid.org/0000-0002-7257-7429
Sang-Yeon SuhDepartment of Family Medicine, Dongguk University Ilsan Hospital, Goyang, Korea.ORCID https://orcid.org/0000-0002-6145-1150
Seirei Mikatabara General Hospital · JPDongguk University · KRTohoku University · JPUniversity of Tsukuba · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper aimed to summarize the current situation of prognostication for patients with an expected survival of weeks or months, and to clarify future research priorities. Prognostic information is essential for patients, their families, and medical professionals to make end-of-life decisions. The clinician's prediction of survival is often used, but this may be inaccurate and optimistic. Many prognostic tools, such as the Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and Prognosis in Palliative Care Study, have been developed and validated to reduce the inaccuracy of the clinician's prediction of survival. To date, there is no consensus on the most appropriate method of comparing tools that use different formats to predict survival. Therefore, the feasibility of using prognostic scales in clinical practice and the information wanted by the end users can determine the appropriate prognostic tool to use. We propose four major themes for further prognostication research: (1) functional prognosis, (2) outcomes of prognostic communication, (3) artificial intelligence, and (4) education for clinicians.

Indexed as

Artificial intelligenceDecision makingEducationPrognosisSurvival analysis

Identifiers

PMID37753320
PMCPMC10519719
OpenAlexW4323046621

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.