The Prevalence and Nature of Supportive Care Needs in Lung Cancer Patients
Bibliographic record
Abstract
PURPOSE: In the present work, we set out to comprehensively describe the unmet supportive care and information needs of lung cancer patients. METHODS: This cross-sectional study used the Supportive Care Needs Survey Short Form 34 (34 items) and an informational needs survey (8 items). Patients with primary lung cancer in any phase of survivorship were included. Demographic data and treatment details were collected from the medical charts of participants. The unmet needs were determined overall and by domain. Univariable and multivariable regression analyses were performed to determine factors associated with greater unmet needs. RESULTS: From August 2013 to February 2014, 89 patients [44 (49%) men; median age: 71 years (range: 44-89 years)] were recruited. The mean number of unmet needs was 8 (range: 0-34), and 69 patients (78%) reported at least 1 unmet need. The need proportions by domain were 52% health system and information, 66% psychological, 58% physical, 24% patient care, and 20% sexuality. The top 2 unmet needs were "fears of the cancer spreading" [n = 44 of 84 (52%)] and "lack of energy/tiredness" [n = 42 of 88 (48%)]. On multivariable analysis, more advanced disease and higher MD Anderson Symptom Inventory scores were associated with increased unmet needs. Patients reported that the most desired information needs were those for information on managing symptoms such as fatigue (78%), shortness of breath (77%), and cough (63%). CONCLUSIONS: Unmet supportive care needs are common in lung cancer patients, with some patients experiencing a very high number of unmet needs. Further work is needed to develop resources to address those needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".