Distant metastasis in patients with cervical cancer: A systematic review and meta-analysis of incidence rates and common sites.

Int J Gynaecol ObstetMay 22, 2026 (epub)

Yun Yang, Meiping Yu, Minli Zeng

✦ AI-curated · Sources linked

In 30 seconds

This systematic review and random-effects meta-analysis pooled observational studies of non-lymphatic distant organ metastases in patients with cervical cancer, excluding studies limited to patients presenting with stage IVB/M1 disease. Across 42 studies and 238 387 patients, the pooled incidence was 2.91 per 100 patients (95% CI: 2.84-2.97). Bone was the most commonly reported site, followed by lung, brain, and liver. The authors note substantial heterogeneity and present the estimates as descriptive trends rather than precise rates.

Key findings

  • Pooled distant metastasis incidence was 2.91 per 100 cervical cancer patients (95% CI: 2.84-2.97).
  • Bone metastases had a pooled incidence of 3.67 per 100 patients (95% CI: 2.37-5.06), the highest among the reported sites.
  • Pooled incidence was 3.00 per 100 patients for lung, 1.83 for brain, and 1.70 for liver metastases.
  • The Western Pacific region had the highest regional pooled incidence: 4.66 per 100 patients (95% CI: 4.52-4.79).

Why it matters

The review summarizes where non-lymphatic distant metastases are reported in cervical cancer and indicates that bone and lung are prominent sites. This can inform clinical awareness of metastatic patterns, while the substantial heterogeneity cautions against treating pooled estimates as precise predictions for individual patients or populations.

What to keep in mind

The authors report large heterogeneity, so pooled estimates should be interpreted as descriptive trends rather than precise rates. The evidence comes from observational studies.

Source

Published in Int J Gynaecol Obstet. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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