Evidence map›Paper›PMID 42082582›Full record

Trial reportScientific reports2026

Network analysis of quality of life and depression in a randomized breast cancer trial with ten-years follow-up.

Sofia Hampf, Eleni Kolokotroni, Carl Blomqvist, Liisa Hakamies-Blomqvist, Georgios Stamatakos, Riikka Huovinen, Pirkko-Liisa Kellokumpu-Lehtinen, Tiina Saarto, Paula Poikonen-Saksela

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Scientific reports, 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

9 authors.

Sofia HampfFaculty of Arts, Psychology and Theology, Åbo Academi University, Turku, Finland.
Eleni KolokotroniIn Silico Oncology and In Silico Medicine Group, Institute of Communication and Computer Systems, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
Carl BlomqvistComprehensive Cancer Center, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.
Liisa Hakamies-BlomqvistComprehensive Cancer Center, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.
Georgios StamatakosIn Silico Oncology and In Silico Medicine Group, Institute of Communication and Computer Systems, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
Riikka HuovinenDepartment of Oncology, Turku University Hospital and Faculty of Medicine, University of Turku, Turku, Finland.
Pirkko-Liisa Kellokumpu-LehtinenFaculty of Medicine and Health Technology, Tampere University and Cancer Center, Tampere University Hospital, Tampere, Finland.
Tiina SaartoComprehensive Cancer Center, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.
Paula Poikonen-SakselaComprehensive Cancer Center, Helsinki University Hospital, University of Helsinki, Helsinki, Finland. paula.poikonen-saksela@hus.fi.

Funding

Syöpäsäätiö 7369
6 · The paper itself

Abstract

Due to the growing amount of breast cancer survivors we must understand their long-term quality of life (QoL) better. Many breast cancer survivors suffer for years from lower functioning capacity and several symptoms, but outcomes regarding their global Quality of Life (gQoL) are less clear. The current study explored the links between functions, symptoms, and gQoL using a network design. We used data from 364 women who had completed adjuvant chemotherapy or started adjuvant endocrine therapy. QoL, symptomatology and functioning were measured by the EORTC QLQ-C30 and BR-23 questionnaires, and depression by the Finnish version of Beck's 13-item depression scale. The multivariate inter-dependence between the symptom scales and gQoL was analyzed via regularized partial correlation networks (graphical LASSO). These networks identify associations, not directionality or causality. Our aim was to explore how the functions and symptoms associate with each other and with gQoL during ten-year follow-up, and to identify the most important scales in the network using centrality analysis. The results showed that three key areas-fatigue and physical functioning, emotional functioning and depression, and social and role functioning-emerged as most central to gQoL across all time points. Interventions targeting these areas may therefore have the greatest potential to improve long-term QoL in breast cancer survivors.

Indexed as

Breast NeoplasmsCancer SurvivorsDepressionQuality of LifeAdultAgedChemotherapy, AdjuvantFemaleFinlandFollow-Up StudiesHumansMiddle AgedSurveys and QuestionnairesBreast cancer survivorsDepressionEORTC QLQ‐C30Network analysisQuality of life

Identifiers

PMID42082582
PMCPMC13333999

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.