Chronic inflammatory states: their relationship to cancer prognosis and symptoms
Bibliographic record
Abstract
A chronic inflammatory state (CIS) commonly accompanies advanced cancers.Elements of a CIS include aberrant immune system activity and changes in hypothalamic-neuroendocrine control mechanisms.The end result is stimulation of tumour growth and metastases.In addition to tumour stimulation, cancer symptoms may be enhanced.While for most symptoms correlation with a CIS remains tenuous, clearly a CIS is linked to the aetiology of the cancer anorexiacachexia syndrome.To date clinical studies aimed at a CIS are modest, but the increased understanding of the partnership of a CIS, cancer progression and anorexia-cachexia must lead to targeting a CIS in concert with conventional efforts to directly destroy tumour tissue.KEYWORDS Cancer prognosis, chronic inflammation and cancer, autonomic nervous system changes in cancer DEClARATiOn Of inTERESTS No conflict of interests declared.This oncologist through most of his career held the view, perhaps shared by others, that evidence of an immune reaction around a tumour was a favourable finding.Even in those patients with far advanced cancers, this accumulation of myeloid cells, lymphocytes, macrophages and fibroblasts represented a valiant defense against the inevitable.My views changed sharply after reading a 2001 paper by Balkwill and Mantovani 1 which mustered the evidence that rather than attacking an advanced cancer, immune cells were more often complicit in stimulating cancer growth and metastases.We were reminded that chronic inflammation commonly establishes the soil for malignant transformation.Examples include chronic bowel and respiratory conditions and a host of chronic viral illnesses. Chronic inflammatory states
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".