Abstract
Background: The prognosis for patients with lung cancer bone metastases has improved with the use of novel systemic agents. These patients might need surgery or radiotherapy to alleviate symptoms or maintain function. However, there is currently no disease specific algorithm to guide multidisciplinary decisions. Methods: The inclusion criteria encompassed studies with ≥10 patients offering multivariate analysis data on survival that were published after 2000 until September 2023. Clinical factors were categorized based on their characteristics and the pooled hazard ratios (HRs) for each category were calculated. A treatment algorithm was proposed based on clinical importance and the pooled HRs. Results: Fifteen studies involving 3759 patients with lung cancer bone metastases were included. The median survival ranged between 1.8-28.3 months (median: 12.4). Among the studies involving patients with EGFR+ or treated with TKIs, the median survival ranged between 19.5-28.3 months. The most reported significant factor was ECOG performance (nine studies) followed by chemotherapy use (six studies). In the pooled analyses, the pooled HR [95% confidence interval (CI)] of the EGFR status category was 2.109 (1.345-3.305); the ECOG performance category was 2.007 (1.536-2.622); the visceral metastases category was 2.060 (1.370-3.098); the bone metastases characteristics category (e.g., multiplicity, weight-bearing bone metastases) was 1.910 (1.443-2.527); the body weight category was 1.805 (1.334-2.442); the anti-absorbants category was 1.784 (1.448-2.196); the systemic treatment category was 1.695 (1.407-2.041); the skeletal-related event category was 1.616 (1.063-2.458); the smoking status category was 1.530 (1.306-1.793); the gender category was 1.482 (1.270-1.729); and the histology category was 1.450 (1.186-1.772). Conclusions: Oncological prognoses are influenced by various interrelated factors. Our treatment algorithm supports multidisciplinary strategies for managing NSCLC bone metastases, considering the complex factors influencing prognosis.