Efficacy of Chemotherapy in Pain Control of Patients with Cancer at the Early Phase of Their Disease
Bibliographic record
Abstract
Scope: The rationale of the present study is to measure the impact of chemotherapy on the pain caused by the disease. Materials and Methods: The present study was based on the completion of two standardized questionnaires for the assessment of physical symptoms (Brief Pain Inventory—BPI—and the revised Edmonton Symptom Assessment System—ESASr) in three different moments. The research was conducted at the Oncology Institute “Prof. Dr. Ion Chiricuță” Cluj-Napoca between 2022 and 2023. Results: 24 patients were included in the study, and they received different cytostatic treatment regimens, adapted to the underlying pathology. We analyzed the distribution of all symptoms from the ESASr and the total score. In terms of the general situation, if we exclude pain, there is never a difference between Time 2 and 3. Furthermore, in all cases where there is a statistically significant effect, there is a difference between Time 1 and 3. We also analyzed the distribution of activities with which pain interacts in BPI. Regarding the general situation, three patterns of influence of pain on the examined parameters are found: for general activity, mood, ability to work, and sleep, there are significant differences between moments 1 and 2 and 1 and 3, without significant differences between moments 2 and 3. The second pattern identified refers to the lack of effect of pain on the ability to walk and on the relationship with other people. The peculiarity is represented by the influence on the enjoyment of life that was significantly improved only from Time 1 to 3. Conclusions: The present study demonstrated a considerable effect of cytostatic treatment on the management of cancer-related pain, as shown across different evaluations.
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 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 | 0.002 |
| 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) | 0.001 | 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".