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Record W3010258069 · doi:10.21873/anticanres.14101

Symptom Burden in Patients With Oligometastases at the Start of Palliative Radiotherapy

2020· article· en· W3010258069 on OpenAlexaboutno aff
Carsten Nieder, Thomas A Kämpe

Bibliographic record

VenueAnticancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiation therapyPalliative careRetrospective cohort studyDiseaseAblative casePerformance statusStage (stratigraphy)Internal medicineOverall survivalSurgery

Abstract

fetched live from OpenAlex

BACKGROUND/AIM: Recent studies suggested that patients with oligometastases have a better prognosis compared with those who have widespread dissemination. In both groups, radiotherapy is a commonly applied treatment. Patient-reported symptoms might depend on the burden of disease. Possibly, oligometastatic patients report lower scores for symptoms, such as fatigue or reduced appetite, which tend to worsen as the disease progresses to a later stage. Therefore, we analyzed the symptom scores in two groups of patients with or without oligometastatic disease. PATIENTS AND METHODS: A retrospective study was performed in 83 patients who received palliative, non-ablative radiotherapy for distant metastases. The Edmonton Symptom Assessment Scale (ESAS) was employed to assess the pre-radiotherapy symptoms. RESULTS: The oligometastatic group was smaller than anticipated (n=11). The ESAS score differences were not statistically significant. However, oligometastatic patients reported less fatigue, pain and dry mouth (p<0.2). They also had a better performance status. The median survival of oligometastatic patients was longer (8.1 vs. 5.5 months, p=0.17), in the absence of ablative metastases-directed treatment. CONCLUSION: The oligometastatic state is not a major contributor to the variable patient-reported symptom scores.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.381
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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