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Abstract P6-08-11: Count us, know us, join us global survey: Comparing the feelings and needs of advanced breast cancer patients in the United States with patients in Latin America, Europe, and Asia

2013· article· en· W2000238659 on OpenAlexaboutno aff
Hailey Miller, Deana Percassi

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerLatin AmericansFeelingFamily medicineCancerGeneral partnershipGlobal healthPolitical sciencePublic healthInternal medicinePsychologyPathology

Abstract

fetched live from OpenAlex

Abstract Background: Advanced breast cancer (stage III and stage IV/metastatic) (ABC) is the most serious form of breast cancer, with nearly 250,000 people across the globe living with the disease. Because ABC often metastasizes to the brain, bone, or liver, it has important health implications, requires life-long treatment, and is usually fatal. Support needs for this patient group are unique, yet rarely met. Hoping to identify new approaches to meeting the needs of this community, a global survey was commissioned by Novartis Oncology in partnership with the global advocacy community. Method: Harris Interactive conducted an online survey between October 2012 and March 2013. It was completed by 1,273 female metastatic breast cancer patients ages 21+ from 12 countries (United States [US], Canada, Mexico, Brazil, Argentina, United Kingdom, Germany, Russia, India, Lebanon, Taiwan, and Hong Kong). Total sample data are not weighted and are representative only of the individuals surveyed. A global post-weight was applied to ensure that all countries received an equal weight in the global and regional data. Results: Patients in the US (70%) are more likely than patients in most other countries surveyed to feel isolated from the non-metastatic community (40% globally). In addition, US patients (73%) are significantly more likely than their counterparts in most other countries to often feel that no one understands what they are going through (63% globally). Patients in the US (53%) are also more likely than those in most other countries to say that support from friends and family has diminished since their initial advanced diagnosis (41% globally), and employed US patients (34%) are more likely than those in many other countries to believe their colleagues look at them differently as a result of their metastatic breast cancer (17% globally). Women in the US were most likely to be actively seeking information (97%) compared with patients in other countries (77% globally). Although more US women patients are active information seekers, they are most likely to be unsatisfied with the information that is currently available compared to patients in the other countries (31%; 51% globally). Conclusions: Despite the significant amount of attention paid to breast cancer in the US and the resources available, many US women with metastatic breast cancer feel more alone and isolated than do their counterparts in most other countries surveyed. These US women are also significantly more likely than their counterparts in other countries to often feel as though no one understands what they are going through. More needs to be done to help women in the US feel supported emotionally throughout their entire ABC journey. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-08-11.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.024
GPT teacher head0.322
Teacher spread0.298 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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