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Prognostic models to predict overall and cause-specific survival for patients with middle ear cancer: a population-based analysis.

Shen W, Sakamoto N, Yang L - BMC Cancer (2014)

Bottom Line: Calibration plots showed that the predicted survival reasonably approximated observed outcomes.The resulting models demonstrated good accuracy in predicting overall survival and cause-specific survival.Nomograms should thus be considered as a useful tool for predicting clinical prognosis.

View Article: PubMed Central - PubMed

Affiliation: Epidemiology and Clinical Research Center for Children's Cancer, National Center for Child Health and Development, Tokyo, Japan. yo-r@ncchd.go.jp.

ABSTRACT

Background: The purpose of this study was to evaluate the survival outcome for middle ear cancer and to construct prognostic models to provide patients and clinicians with more accurate estimates of individual survival probability.

Methods: Patients diagnosed with middle ear cancer between 1983 and 2011 were selected for the study from the Surveillance Epidemiology and End Results Program. We used the Kaplan-Meier product limit method to describe overall survival and cause-specific survival. Cox proportional hazards models were fitted to model the relationships between patient characteristics and prognosis. Nomograms for predicting overall survival and cause-specific survival were built using the Cox models established.

Results: The entire cohort comprised 247 patients with malignant middle ear cancer. Median duration of follow-up until censoring or death was 25 months (range, 1-319 months). Five-year overall survival and cause-specific survival were 47.4% (95% Confidence Interval (CI), 41.2% to 54.6%) and 58.0% (95% CI, 51.6% to 65.3%), respectively. In multivariable analysis, age, histological subtype, stage, surgery and radiotherapy were predictive of survival. The bootstrap corrected c-index for model predicting overall and cause-specific survival was 0.73 and 0.74, respectively. Calibration plots showed that the predicted survival reasonably approximated observed outcomes.

Conclusion: The models represent an objective analysis of all currently available data. The resulting models demonstrated good accuracy in predicting overall survival and cause-specific survival. Nomograms should thus be considered as a useful tool for predicting clinical prognosis.

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Related in: MedlinePlus

Flow chart for creation of the Surveillance Epidemiology and End Results (SEER) data set.
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Fig1: Flow chart for creation of the Surveillance Epidemiology and End Results (SEER) data set.

Mentions: The SEER program of the National Cancer Institute is the largest population-based cancer registry in the United States. The SEER registries collect data on patient demographics, primary tumor site, stage, tumor morphology, and treatment for all cancer patients, covering approximately 28% of the US population. For this research, the recently released SEER (1973–2011) database was used for case extraction [5]. All patients diagnosed with middle ear cancer as their first malignancy were selected (site code C30.1). Patients were excluded from the study if the tumor was identified on the death certificate only. Middle ear lymphomas and rhabdomysarcomas were also excluded. Because there is no SEER stage information before 1983, we also excluded patients diagnosed between 1973 and 1982. Detailed data selection is shown in Figure 1.Figure 1


Prognostic models to predict overall and cause-specific survival for patients with middle ear cancer: a population-based analysis.

Shen W, Sakamoto N, Yang L - BMC Cancer (2014)

Flow chart for creation of the Surveillance Epidemiology and End Results (SEER) data set.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4129120&req=5

Fig1: Flow chart for creation of the Surveillance Epidemiology and End Results (SEER) data set.
Mentions: The SEER program of the National Cancer Institute is the largest population-based cancer registry in the United States. The SEER registries collect data on patient demographics, primary tumor site, stage, tumor morphology, and treatment for all cancer patients, covering approximately 28% of the US population. For this research, the recently released SEER (1973–2011) database was used for case extraction [5]. All patients diagnosed with middle ear cancer as their first malignancy were selected (site code C30.1). Patients were excluded from the study if the tumor was identified on the death certificate only. Middle ear lymphomas and rhabdomysarcomas were also excluded. Because there is no SEER stage information before 1983, we also excluded patients diagnosed between 1973 and 1982. Detailed data selection is shown in Figure 1.Figure 1

Bottom Line: Calibration plots showed that the predicted survival reasonably approximated observed outcomes.The resulting models demonstrated good accuracy in predicting overall survival and cause-specific survival.Nomograms should thus be considered as a useful tool for predicting clinical prognosis.

View Article: PubMed Central - PubMed

Affiliation: Epidemiology and Clinical Research Center for Children's Cancer, National Center for Child Health and Development, Tokyo, Japan. yo-r@ncchd.go.jp.

ABSTRACT

Background: The purpose of this study was to evaluate the survival outcome for middle ear cancer and to construct prognostic models to provide patients and clinicians with more accurate estimates of individual survival probability.

Methods: Patients diagnosed with middle ear cancer between 1983 and 2011 were selected for the study from the Surveillance Epidemiology and End Results Program. We used the Kaplan-Meier product limit method to describe overall survival and cause-specific survival. Cox proportional hazards models were fitted to model the relationships between patient characteristics and prognosis. Nomograms for predicting overall survival and cause-specific survival were built using the Cox models established.

Results: The entire cohort comprised 247 patients with malignant middle ear cancer. Median duration of follow-up until censoring or death was 25 months (range, 1-319 months). Five-year overall survival and cause-specific survival were 47.4% (95% Confidence Interval (CI), 41.2% to 54.6%) and 58.0% (95% CI, 51.6% to 65.3%), respectively. In multivariable analysis, age, histological subtype, stage, surgery and radiotherapy were predictive of survival. The bootstrap corrected c-index for model predicting overall and cause-specific survival was 0.73 and 0.74, respectively. Calibration plots showed that the predicted survival reasonably approximated observed outcomes.

Conclusion: The models represent an objective analysis of all currently available data. The resulting models demonstrated good accuracy in predicting overall survival and cause-specific survival. Nomograms should thus be considered as a useful tool for predicting clinical prognosis.

Show MeSH
Related in: MedlinePlus