Evidence map›Paper›PMID 42343706›Full record

SynthesisAnnals of geriatric medicine and research2026

Healthcare Professionals' Perceptions of Decision-Making for Older Patients with Cancer Receiving Systemic Therapy: A Systematic Review and Qualitative Evidence Synthesis.

Kengo Hirayama, Honoka Tsumura, Sunka Kim, Moe Nemoto

Abstract readSystematic Review
In one paragraph

Synthesis in Annals of geriatric medicine and research, 2026. 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

4 authors.

Kengo HirayamaSchool of Nursing, Sapporo City University, Sapporo, Japan. k.hirayama@scu.ac.jp.
Honoka TsumuraDepartment of Nursing, Sapporo-Kosei General Hospital, Sapporo, Japan.
Sunka KimDepartment of Nursing, Hokkaido University Hospital, Sapporo, Japan.
Moe NemotoMedical Sciences Group, Research Support Division, Hokkaido University Library, Sapporo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Decision-making about systemic therapy in older adults with cancer is complex due to frailty, clinical uncertainty, and competing treatment goals. Limited evidence exists synthesizing how healthcare professionals support decision-making in geriatric oncology. This qualitative systematic review searched four databases through November 2025 and conducted citation tracking. Thematic synthesis was performed, and confidence in findings was assessed using GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research). Twelve studies involving 212 healthcare professionals were included. Two analytical and six descriptive themes were identified. Healthcare professionals sought to minimize treatment-related harm while respecting patients' values and life perspectives. Decision-making was shaped by clinical judgment integrating geriatric assessment findings, healthcare professionals' perspectives, ethical considerations regarding beneficence and autonomy, and structural factors such as resource limitations and interprofessional collaboration. These findings highlight the need for clinical expertise, collaboration across oncology, primary care, and geriatric care providers, and system-level support for geriatric-informed care.

Indexed as

Antineoplastic AgentsAttitude of Health PersonnelClinical Decision-MakingDecision MakingHealth PersonnelNeoplasmsAgedHumansQualitative ResearchAntineoplastic AgentsAgedAntineoplastic agentsDecision makingHealth personnelNeoplasms

Identifiers

PMID42343706
PMCPMC13639503

What OpenQuestion holds

Textmetadata
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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.