Influence of Clinical and Histopathological Parameters in the Management of Metastatic Disease of the Spine Secondary to Lung Cancer: A Systematic Review
Bibliographic record
Abstract
Background Determining optimal treatment of metastatic disease of the spine is difficult. Decision making revolves around neurological status, stability, and patient factors; histology the most important as specifically linked to life expectancy. Traditionally, limited life expectancy eliminated surgery as an option, but with minimally invasive techniques this paradigm is changing. Metastatic lung cancer generally has poor life expectancy and most patients are not offered surgery; but are there some patients with lung cancer who would benefit from surgery? Recently, molecular sequencing has led to better specificity than the traditional small cell, non-small cell (NSCLC) dichotomy and thus betters prediction of life expectancy. The purpose of this study is to identify histopathological and clinical parameters related to life expectancy that would help guide optimal surgical decision making for metastatic disease of the spine secondary to lung cancer. Methods A systematic review was conducted to answer the following questions: Q1. Determine the current survival patterns in the lung Ca population. Q2. Identify prognostic factors influencing survival and outcome in patients with lung Ca. Results A total of 20 studies met the preset inclusion criteria. All included studies were retrospective series with a level of evidence of IV. The overall survival of patients with metastatic lung carcinoma is poor ranging from 5 to 17.8 months. Included studies consistently showed a better prognosis for patients with adenocarcinoma. The presence of EGFR mutation was also associated with a mild increase in life expectancy compared with the other histological subtypes. Conclusion Although life expectancy in patients with metastatic lung Ca is still in general not good, a subset of patients with adenocarcinoma and patients with EGFR mutations seem to have a better overall survival. Previously identified clinical and imagiological prognostic factors are still valid, but histology and specific mutations should be factored in the decision making when dealing with patients with lung Ca and MESSC.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".