Abstract P6-08-03: Informational needs and psychosocial assessment of patients in their first year after metastatic breast cancer diagnosis
Bibliographic record
Abstract
Abstract Background: Psychosocial distress is common after a diagnosis of breast cancer. Little is known about the informational needs and the psychosocial adjustment of patients diagnosed with metastatic breast cancer (MBC) within the first year of their diagnosis. Methods: Patients with MBC from a single academic institution completed a cross-sectional self-administered paper survey. The survey included demographics, the Medical Outcomes Study Short Form-36 (SF-36), the Hospital Anxiety and Depression Scale (HADS), and Toronto Informational Needs Questionnaire-Breast Cancer (TINQ). Medical history was obtained by chart review. The Spearman correlation coefficient assessed the relationship between TINQ and the following: age at MBC diagnosis, disease free interval (DFI), time between survey completion and MBC diagnosis, number of lines of therapy, and HADS. Results: Fifty-two (90%, 50F 2M) patients completed the survey. Median age at MBC diagnosis was 52 yrs (range 22–81). Thirty-nine (75%) patients had completed college, 92% were Caucasian. Median time between MBC diagnosis and survey completion was 6 months (range 1–12). Sixteen (31%) patients had de novo stage 4 disease. At time of survey completion, 36 (69%) patients were on 1st line therapy with some patients were receiving their 4th line of therapy. SF-36 scores were lower in all 8 subscales compared to the general population. In particular, role limitations due to physical health (Norm-based transformation mean score 39.3, SD=12.1), social functioning (Mean 41.8, SD=12.7), role limitations due to emotional problems (Mean 43.3, SD=13.3), vitality (Mean 44.1, SD=10.8) and general health (Mean 44.3, SD=12.1) were diminished. The Physical and Mental Component Summary norm-based transformation scores were 43.2 (SD = 11.7) and 45.4 (SD = 11.3) respectively.9/48 (19%) patients met criteria for anxiety, and 4/48 (8%) patients met criteria for depression by HADS criteria (scores > 11). TINQ scores range from 51 to 255, with 35/52 (69%) having a total score > 200, suggesting high informational need. Of the 5 subscales, treatment information was most important, followed by information about disease, physical care, psychosocial needs and investigative tests. The most important informational issues for patients were: if there was cancer anywhere else in their body (Mean score 4.78), how to deal with side effects (Score 4.78), and if there were ways to prevent treatment side effects (Score 4.77), with a score of 5=extremely important, and 1= not important. Only DFI correlated with TINQ (Spearman coefficient −0.413, p = 0.011), with patients who had a shorter DFI having greater informational needs. Age at MBC diagnosis, time of completion of survey, number of lines and HADS were not significant. Conclusion: Based on this study, patients with recently diagnosed MBC have high informational needs and poor psychosocial adjustment. The overall quality of life appears to be worse in this population of patients compared to the general population. There is also a subset of patients who are dealing with significant anxiety and depression. Additional research, education, and supportive care services aimed at meeting the informational and psychosocial needs of women living with MBC are warranted. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P6-08-03.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".