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Record W3086232680 · doi:10.1111/ajco.13430

Awareness of and preference for disease prognosis and participation in treatment decisions among advanced cancer patients in Myanmar: Results from the APPROACH study

2020· article· en· W3086232680 on OpenAlexaboutno aff
S. Mon, Wah Wah Myint Zu, Myo Maw, Han Win, Kyaw Zin Thant, Grace Meijuan Yang, Chetna Malhotra, Irene Teo, Eric Finkelstein, Semra Özdemir

Bibliographic record

VenueAsia-Pacific Journal of Clinical Oncology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPreferenceMedicineDiseaseDescriptive statisticsLogistic regressionCancerFamily medicineQuarter (Canadian coin)Stage (stratigraphy)Internal medicine

Abstract

fetched live from OpenAlex

AIM: To investigate prognostic awareness, preference for prognostic information, and perceived and preferred roles in decision making among patients with advanced cancer in Myanmar. METHODS: A cross-sectional survey was administered at the Yangon General Hospital to stage 4 cancer patients who were at least 21 years old and aware of their cancer diagnosis. Patients were asked questions about their prognosis, participation in treatment decisions, sociodemographic and clinical information. Data from 131 patients were analyzed using descriptive statistics and logistic regressions. RESULTS: Only 15% of patients surveyed were aware that their cancer was advanced and only a quarter (26%) of patients knew that treatment intent was noncurative. The likelihood of treatment-intent awareness was higher among patients who were male, high income, and aware that they had advanced cancer. Roughly 60% of patients reported playing an active or collaborative role in treatment decisions, with a strong preference (59%) for the latter. For the majority of patients (69%), perceived and preferred roles in decision making were the same. Sociodemographic characteristics did not predict perceived and preferred roles in decision making. CONCLUSIONS: This is the first effort to analyze prognostic awareness and decision-making practices among advanced cancer patients in Myanmar. Patients had inadequate knowledge on their disease progression and intent of treatment. Yet, the majority of them were keen to be involved in treatment decisions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.596
GPT teacher head0.572
Teacher spread0.024 · 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 teacher head, not a consensus.

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

Citations10
Published2020
Admission routes1
Has abstractyes

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