The Outcomes of Surgical and Nonsurgical Treatment in Patients With Spinal Metastases of Lung Cancer: Protocol for a Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Spinal metastases of lung cancer (SMLC) usually have a high degree of malignancy and require multimodality treatment. Patients with SMLC who experience clinical symptoms (eg, local pain, emerging or potential spinal instability, and progressive neurological dysfunction) require surgical treatment. However, there are discrepancies in the comparison of outcomes between surgical treatment and nonsurgical treatment. OBJECTIVE: This paper presents the protocol for a study that aims to compare the clinical outcomes of surgical treatment and nonsurgical treatment for SMLC, explore the prognostic factors of SMLC, and establish a survival prediction model based on these prognostic factors. METHODS: This is a prospective cohort study, with an anticipated sample size of 240 patients (120 patients in the surgical group and 120 patients in the nonsurgical group). We will collect baseline data, including demographic, clinical, and radiological information, as well as data from patient-reported questionnaires. Patients will be followed up at 3, 6, 12, and 24 months after treatment, and survival status will be assessed every 3 months. The primary outcome is the overall survival period. Prognostic factors associated with overall survival will be analyzed by univariate and multivariate Cox proportional hazards regression. Odds ratios with 95% CIs will be presented. Statistical significance is set at P<.05. RESULTS: This study has been approved by our institute's Medical Science Research Ethics Committee (IRB00006761-M2021085) after a careful audit of the design and content. Patient enrollment began in June 2022 at our hospital. Data collection is expected to be completed by early 2026, and the study results will be published by mid-2027. CONCLUSIONS: In this study, we propose to set up a prospective cohort of patients with SMLC to investigate the outcomes between surgical treatment and nonsurgical treatment. We will explore the role of surgical treatment in SMLC and provide guidance to peer surgeons. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2100048151; http://www.chictr.org.cn/showproj.aspx?proj=129450. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/38273.
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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 | 0.043 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".