Abstract PO-111: Postoperative lung cancer pain over 4 days: Changes in painful body surface area
Bibliographic record
Abstract
Abstract Introduction: It is unknown if the body surface area measure is sensitive to the change in pain over the first four days after lung cancer surgery. Known for cancer health disparities, improving pain outcomes for patients with lung cancer could have implications for reducing disparities. The purpose of this study was to compare body surface area over the first four days post thoracotomy for lung cancer. Methodology: In a repeated measures observational study, 41 lung cancer patients (mean age 60±12 years, 80% male, 100% Turkish) who had thoracotomy surgery reported pain postoperatively for four days. Patients were asked to mark on a body outline the location of the area where they had pain each day using PAINReportIt, a valid and reliable electronic version of the McGill Pain Questionnaire, on an Internet-enabled Surface Pro tablet. The number of sites that the patient marked was counted automatically by PAINReportIt. Then the body surface area percentage (BSA%) was calculated using ImageJ software. Each day patients were asked to rate on a 0-10 scale the pain intensity they were currently having and the least and worst that the pain was in the past 24 hours. These 3 values were used to create the average of pain intensity (API) the patient experienced for each of the four days. Analyses included scatter plots, descriptive statistics, longitudinal analysis of BSA% using linear mixed effects model, and Pearson correlations of BSA% and API. Results: The mean number of pain sites recorded by PAINReportIt for each postop day 1 to 4 was 2.1±0.7, 2.2±0.7, 2.1±0.9, and 1.9±0.7, respectively (p=.152). The mean BSA% on postop days 1 to 4 was 2.1%±1.9%, 2.4%±2.2%, 2.5%±2.7%, and 2.2%±2.4%, respectively. The correlations between postop day 1-4 values were high (r=.68 to r=.86). Longitudinal analysis shows that the time trend was not statistically significant: b=0.023, Std Err=0.094, 5=0.242, p=.81. The API significantly decreased over the 4 postop days: 7.3±1.8, 5.6±1.8, 4.2±1.9, and 3±2.1, respectively (p=.000). The correlations between BSA% and API on each of the 4 postop days were: r=-.56, p<.001, r=-.15, p=.36, r=-.03, p=.85, and r=-.05, p=.78. The negative relationship between BSA% and API was unexpected and scatter plots show that at very high pain and very low pain, BSA%s were low. High BSA% values were mostly observed at moderate pain. This inverse U shape relationship explains the correlations between BSA% and API at different time points. Conclusions: In a sample of patients who had thoracotomy for lung cancer, the BSA% was not sensitive to recovery over the first 4 days after surgery, but the API was. This finding is likely due to the few pain sites and small areas marked on the body outline to represent the pain of the surgical incision and chest tubes. In the post thoracotomy lung cancer population, BSA% is not likely to be a measure that will help reduce cancer health disparities. Citation Format: Mecca M. James, Sevgi D. Dogan, Seda K. Yedir, Rishabh Garg, Yingwei Yao, Sevily Erden, Diana J. Wilkie. Postoperative lung cancer pain over 4 days: Changes in painful body surface area [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-111.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".