Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan

PLoS One. 2012;7(7):e40590. doi: 10.1371/journal.pone.0040590. Epub 2012 Jul 17.


Background: Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surgeon and hospital caseloads and survival rates for major cancers.

Methodology: A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations.

Results: Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P<0.005).

Conclusions: After adjusting for differences in the case mix, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer 5-year survival rates. Payers may implement quality care improvement in low-volume surgeons.

MeSH terms

  • Aged
  • Female
  • General Surgery*
  • Hospitals, High-Volume / statistics & numerical data*
  • Hospitals, Low-Volume / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Neoplasms / mortality*
  • Neoplasms / surgery*
  • Proportional Hazards Models
  • Survival Rate
  • Taiwan / epidemiology
  • Workforce