EDITORIAL COMMENTARY
Editorial Commentary: Be Careful about Drawing Big Conclusions from Big Data Frank C. Detterbeck, MD The article by Hamaji and Burt (Long-Term Outcomes of Surgical and Nonsurgical Management of Stage IV Thymoma: A Population-Based Analysis of 282 Patients, this issue) is an analysis of the outcomes of 282 patients with metastatic thymoma from the surveillance, epidemiology, and end results (SEER) database from 1988-2000. The study encompasses both surgically managed (39%) and nonsurgically managed patients, in contrast to most singleinstitution series that involve primarily a surgical cohort only and are much smaller. Surgical management involved a variety of procedures, ranging from complete (R0) resection to an array of partial resections (but excluding a biopsy only). Overall survival (OS) was better in the surgically managed patients (5-year OS of 69% vs 26% and 10-year OS of 35% vs 19%). Among the surgically managed patients, OS was better for complete vs incomplete resection (5-year OS of 78% vs 50% and 10-year OS of 47% vs 21%). The SEER database provides data on age, sex, race, and the use of radiotherapy but not on comorbidities or the use of chemotherapy. The SEER database also has limited information on tumor burden (we only know these patients had “discontinuous metastases” that may have involved pleural nodules, lymph nodes, or distant metastases). Histologic
information was incomplete (missing in 52% of the surgical and 72% of the nonsurgical patients). Multivariate analysis of available factors in the surgical cohort did not reveal any significant factors, including the type of procedure. A strength of this article is the sample size— thymoma is a rare disease, and metastatic patients are a small subgroup. The only database with a larger number of patients is the International Thymic malignancy Interest Group (ITMIG) database.1 The ITMIG database demonstrated 5- and 10-year OS for Masaoka stages IVa and IVb of 80% and 60% (all patients) and 85% and 75% for R0 resected patients, respectively.2 In general, the Hamaji and Burt results are similar, although slightly worse as one would expect from a population-based series such as SEER, and recognizing that the ITMIG database is heavily weighted toward surgically managed patients. But the study by Hamaji and Burt also has weaknesses. The SEER database does not provide sufficient detail about the tumor burden, comorbidities, and treatments received. We cannot disentangle the effect of patient selection and competing causes of death from the treatment effect. A schematic depiction of factors determining prognosis is shown in Figure 1. If we have limited information about the
Tumor Factors:
Patient Factors:
Environment:
Tumor Burden, Histologic Type, Genomic factors
Co-morbidities, Competing causes of death, Values
Healthcare System Access, Quality, Geographic factors
Clinical Setting: Treatment Given (Surgery, Radiation, Chemotherapy) Quality (R0/R1/R2 resection, response, compliance)
Figure 1. Schematic of factors influencing a measure of prognosis, such as overall survival.
Division of thoracic surgery, Department of Surgery, Yale University, New Haven, CT Be Careful about Drawing Big Conclusions from Big Data.
4
1043-0679/$-see front matter ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1053/j.semtcvs.2015.02.008
SEER ANALYSIS OF STAGE IV THYMOMA various factors, we have to be cautious about attributing an observation to a particular factor that we are focused on. Although the study by Hamaji and Burt is well done, we have to remain critical and not overinterpret the results. For example, does the study suggest that resection is beneficial or is it all a matter of patient selection?. There was no significant difference in OS or cancer-specific survival between completely and incompletely resected patients. Does this tell us that incomplete resection is worthwhile or does it suggest that surgery itself is not useful, so the resection type does not matter either? There was a
high proportion of Asians in this study (17%)—what effect does this have? It is difficult to make progress in a rare disease such as thymoma. Studies such as the current one are important but have limitations in providing sound guidance that we can confidently apply clinically to specific patients. This underscores the importance of the effort of ITMIG to provide infrastructure for collaboration and the value of the contributions of the global ITMIG community to collect data with sufficient detail to better disentangle the impact of various factors.
1. Huang J, Ahmad U, Catlin A, Detterbeck F. study of a rare tumor. J Thorac Oncol 2015;10: Committee ObotIID, Development of the interna573-8. tional thymic malignancy interest group interna- 2. Detterbeck F, Stratton K, Giroux D, et al: The tional database: An unprecedented resource for the ITMIG/IASLC thymic epithelial tumors staging
Seminars in Thoracic and Cardiovascular Surgery Volume 27, Number 1
project: Proposal for an evidence-based stage classification system for the forthcoming (8th) edition of the TNM Classification of malignant tumors. J Thorac Oncol 9:S65-S72, 2014(9 suppl 2)
5
Editorial Commentary: Be Careful about Drawing Big Conclusions from Big Data Frank C. Detterbeck, MD The article by Hamaji and Burt (Long-Term Outcomes of Surgical and Nonsurgical Management of Stage IV Thymoma: A Population-Based Analysis of 282 Patients, this issue) is an analysis of the outcomes of 282 patients with metastatic thymoma from the surveillance, epidemiology, and end results (SEER) database from 1988-2000. The study encompasses both surgically managed (39%) and nonsurgically managed patients, in contrast to most singleinstitution series that involve primarily a surgical cohort only and are much smaller. Surgical management involved a variety of procedures, ranging from complete (R0) resection to an array of partial resections (but excluding a biopsy only). Overall survival (OS) was better in the surgically managed patients (5-year OS of 69% vs 26% and 10-year OS of 35% vs 19%). Among the surgically managed patients, OS was better for complete vs incomplete resection (5-year OS of 78% vs 50% and 10-year OS of 47% vs 21%). The SEER database provides data on age, sex, race, and the use of radiotherapy but not on comorbidities or the use of chemotherapy. The SEER database also has limited information on tumor burden (we only know these patients had “discontinuous metastases” that may have involved pleural nodules, lymph nodes, or distant metastases). Histologic
information was incomplete (missing in 52% of the surgical and 72% of the nonsurgical patients). Multivariate analysis of available factors in the surgical cohort did not reveal any significant factors, including the type of procedure. A strength of this article is the sample size— thymoma is a rare disease, and metastatic patients are a small subgroup. The only database with a larger number of patients is the International Thymic malignancy Interest Group (ITMIG) database.1 The ITMIG database demonstrated 5- and 10-year OS for Masaoka stages IVa and IVb of 80% and 60% (all patients) and 85% and 75% for R0 resected patients, respectively.2 In general, the Hamaji and Burt results are similar, although slightly worse as one would expect from a population-based series such as SEER, and recognizing that the ITMIG database is heavily weighted toward surgically managed patients. But the study by Hamaji and Burt also has weaknesses. The SEER database does not provide sufficient detail about the tumor burden, comorbidities, and treatments received. We cannot disentangle the effect of patient selection and competing causes of death from the treatment effect. A schematic depiction of factors determining prognosis is shown in Figure 1. If we have limited information about the
Tumor Factors:
Patient Factors:
Environment:
Tumor Burden, Histologic Type, Genomic factors
Co-morbidities, Competing causes of death, Values
Healthcare System Access, Quality, Geographic factors
Clinical Setting: Treatment Given (Surgery, Radiation, Chemotherapy) Quality (R0/R1/R2 resection, response, compliance)
Figure 1. Schematic of factors influencing a measure of prognosis, such as overall survival.
Division of thoracic surgery, Department of Surgery, Yale University, New Haven, CT Be Careful about Drawing Big Conclusions from Big Data.
4
1043-0679/$-see front matter ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1053/j.semtcvs.2015.02.008
SEER ANALYSIS OF STAGE IV THYMOMA various factors, we have to be cautious about attributing an observation to a particular factor that we are focused on. Although the study by Hamaji and Burt is well done, we have to remain critical and not overinterpret the results. For example, does the study suggest that resection is beneficial or is it all a matter of patient selection?. There was no significant difference in OS or cancer-specific survival between completely and incompletely resected patients. Does this tell us that incomplete resection is worthwhile or does it suggest that surgery itself is not useful, so the resection type does not matter either? There was a
high proportion of Asians in this study (17%)—what effect does this have? It is difficult to make progress in a rare disease such as thymoma. Studies such as the current one are important but have limitations in providing sound guidance that we can confidently apply clinically to specific patients. This underscores the importance of the effort of ITMIG to provide infrastructure for collaboration and the value of the contributions of the global ITMIG community to collect data with sufficient detail to better disentangle the impact of various factors.
1. Huang J, Ahmad U, Catlin A, Detterbeck F. study of a rare tumor. J Thorac Oncol 2015;10: Committee ObotIID, Development of the interna573-8. tional thymic malignancy interest group interna- 2. Detterbeck F, Stratton K, Giroux D, et al: The tional database: An unprecedented resource for the ITMIG/IASLC thymic epithelial tumors staging
Seminars in Thoracic and Cardiovascular Surgery Volume 27, Number 1
project: Proposal for an evidence-based stage classification system for the forthcoming (8th) edition of the TNM Classification of malignant tumors. J Thorac Oncol 9:S65-S72, 2014(9 suppl 2)
5
