Abstract
Background
Malignant Pleural Mesothelioma (MPM) is a primary pleural tumor with scarce prognostic data estimates given its rarity. This study aims to explore the epidemiologic and survival predictors amongst patients with MPM, extending from the largest and most recent study conducted between 1973 and 2009.
Methods
3384 patients diagnosed with MPM between 2010 and 2017 were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. Demographics, clinical characteristics, overall mortality (OM), and cancer-specific mortality (CSM) estimates were analyzed. Multivariate Cox model was used to identify independent prognostic factors, where a hazard ratio (HR) greater than 1 denotes adverse prognostic factors.
Results
Our cohort revealed a male predominance (77.16%), with over 80% diagnosed after age 59, peaking between 60 and 79 years old (60.17%). Epithelioid mesothelioma (41.78%), non-Hispanic whites (78.13%), and diagnosis at distant stage (71.60%) were the most common subgroups in their respective categories. 365 patients (10.79%) lacked pleural effusion at diagnosis. In multivariate analyses, higher overall mortality (OM) was associated with male gender (HR = 1.24, 95% CI 1.14–1.37, p < 0.01), age >80 years (HR = 2.17, 95% CI 1.41–3.35, p < 0.01), fibrous mesothelioma (HR = 2.21, 95% CI 1.95–2.51, p < 0.01), and distant stage (HR = 1.55, 95% CI 1.34–1.81, p < 0.01). Higher cancer-specific mortality (CSM) was associated with male gender (HR = 1.25, 95% CI 1.13–1.38, p < 0.01), age >80 years (HR = 2.02, 95% CI 1.29–3.15, p < 0.01), fibrous mesothelioma (HR = 2.24, 95% CI 1.97–2.55, p < 0.01), and distant stage (HR = 1.59, 95% CI 1.36–1.87, p < 0.01). Lower OM and CSM was observed in patients who underwent any type of treatment. Nonmalignant pleural effusion, based on histology, was associated with higher CSM (HR = 1.22, 95% CI 1.05–1.4, p < 0.05).
Conclusion
Fibrous mesothelioma, older age, and distant disease were associated with increased mortality. All intervention strategies were associated with improved survival outcomes. Earlier diagnosis may improve outcomes, as available interventions are associated with lower mortality when feasible at diagnosis. The study paves the way for further prospective and retrospective studies to focus on the identification of patient subsets that may benefit from early mesothelioma screening.
Keywords: Malignant pleural mesothelioma, Uncommon cancers, Tumor epidemiology, Rare malignancies, Rare oncology
1. Introduction
Mesothelioma, primarily arising from the pleural cavity, is linked to asbestos exposure in about two-thirds of cases.1,2 Other implicated factors include ionizing radiation to supra-diaphragmatic fields,3 carbon nanotube exposure, Simian virus 40 (SV40), and BAP1 somatic mutations.4–7 Symptoms include chest pain, cough, hoarseness, etc.8 and disease progression can lead to complications like superior vena cava syndrome, bowel obstruction from mass effect through the diaphragm, arrhythmias, and neurologic deficits with spinal cord compression.9 Initial diagnosis involves contrast-enhanced chest CT, pleural effusion analysis, and biopsy. Treatment typically involves platinum-based chemotherapy with pemetrexed, with or without tumor resection.10 Despite a comprehensive study from 1973 to 2009, gaps exist in understanding baseline epidemiology and independent prognostic factors and determinants of survival in the past decade. To address this, using a large US population-based dataset, we aimed to assess clinical characteristics and independent prognostic factors among MPM patients.
2. Methods
2.1. Study design
A population-based retrospective cohort study utilized the SEER research data, specifically the Nov 2020 submission database (http://www.seer.cancer.gov), from 17 registries, sponsored by the United States National Cancer Institute (US NCI). The SEER Program is a leading source of cancer-related data in the United States, comprising 18 population-based cancer registries, collecting cancer incidence, clinicopathological features, and survival data, for about 28% of the U.S. population.12 The SEER database is a publicly available dataset providing de-identified patient data. Thus, the need for an IRB approval was waived.
2.2. Data selection
2.2.1. Inclusion criteria
All patients with MPM diagnosed from 2010 to 2017 were selected from the SEER database based on (1) Primary site [c38.4] and (2) histological type [ICD-O-3: 9050, 9051, 9052, 9053).
2.2.2. Exclusion criteria
The study excluded patients with unknown age at diagnosis, race, or stage of MPM.
2.3. Study variables
2.3.1. Main exposure
All the variables included in this cohort except the year of diagnosis were used as main predictors of prognosis.
2.3.2. Outcomes
Overall mortality due to any cause at the end of the study was categorized as “yes”, and patients who survived were classified as “no”.
Cancer-specific mortality, referring to patients who died of MPM at the end of the study, was categorized as “yes”, and patients dying of other causes were classified as “no”.
2.3.3. Survival months
Survival time for overall mortality was calculated from diagnosis to death or the last follow-up date (December 31, 2017), as reported in the SEER registry. Similarly, for cancer-specific mortality, survival time was calculated from diagnosis to MPM-related death or the last follow-up date, as recorded in the SEER registry.
2.3.4. Sociodemographic and tumor characteristics
Extracted variables include age at diagnosis, gender, race (White, Black, and others), origin (Non-Hispanic and Hispanic), stage at diagnosis (localized, regional, and distant), geographic residential area, yearly income, marital status, year of diagnosis, surgery, and radiation.
2.4. Statistical analysis
The Cox proportional hazard regression model assumes proportional hazard rates over time. Variables with a p-value <0.1 in the univariate Cox regression model were included in the multivariate Cox proportional analyses to identify independent prognostic factors for overall mortality (OM) and cancer-specific mortality (CSM), where a hazard ratio (HR) greater than 1 indicates adverse prognostic factors. All tests were two-sided, with a 95% confidence interval, and a p-value <0.05 was considered statistically significant. The statistical analysis was conducted using STATA 18.0 software.
3. Results
Patients in our study, as detailed in Table 1, were predominantly male (77.16%), with most diagnoses occurring between 60 and 79 years of age (60.17%). Epithelioid MPM (41.78%) was the prevalent histological group, while biphasic MPM was the least common (9.81%). The majority of patients were married (66.4%) and had distant metastasis at the time of diagnosis (71.6%). Non-Hispanic Whites constituted the majority (78.13%), with a prevalent annual income of $75,000+ (38.03%) and residence in metropolitan areas (60.02%). Feasible surgical resection of the primary tumor was observed in up to a third of patients (26.36%), and approximately half underwent chemotherapy (52.25%). A combination of surgery and radiation was administered to 230 patients (6.80%), and 391 patients (11.55%) underwent radiation. Pleural effusion was absent in up to 10% of patients (see Table 1).
Table 1.
Demographic and Clinicopathologic characteristics of US patients diagnosed with Malignant Pleural mesothelioma between 2010 and 2017.
| Characteristics | N= | % |
|---|---|---|
| Total | 3384 | 100 |
| Gender | ||
| Female | 773 | 22.84 |
| Male | 2611 | 77.16 |
| Age at diagnosis, y.o | ||
| 0–39 | 29 | 0.86 |
| 40–59 | 368 | 10.87 |
| 60–79 | 2036 | 60.17 |
| 80+ | 951 | 28.10 |
| Histologic subtype | ||
| Epithelioid mesothelioma | 1414 | 41.78 |
| Fibrous mesothelioma | 384 | 11.35 |
| Malignant mesothelioma, NOS | 1254 | 37.06 |
| Biphasic mesothelioma | 332 | 9.81 |
| Marital status | ||
| Married | 2248 | 66.43 |
| Single | 357 | 10.55 |
| Divorced/separated | 278 | 8.22 |
| Widowed | 501 | 14.80 |
| Tumor stage | ||
| Localized | 339 | 10.02 |
| Regional by direct extension only | 354 | 10.46 |
| Regional lymph nodes involved only | 101 | 2.98 |
| Regional by both direct extension and lymph node involvement | 167 | 4.93 |
| Distant | 2423 | 71.60 |
| Race | ||
| Non-Hispanic white | 2644 | 78.13 |
| Non-Hispanic black | 163 | 4.82 |
| Hispanic | 418 | 12.35 |
| Other | 159 | 4.70 |
| Living area | ||
| Counties in metropolitan areas of 1 million persons | 2031 | 60.02 |
| Counties in metropolitan areas of 250,000 to 1 million persons | 720 | 21.28 |
| Counties in metropolitan areas of 250,000 persons | 250 | 7.39 |
| Nonmetropolitan counties adjacent to a metropolitan area | 237 | 7.00 |
| Nonmetropolitan counties not adjacent to a metropolitan area | 146 | 4.31 |
| Income per year | ||
| $< $55,000 | 551 | 16.28 |
| $55,000–64,999 | 639 | 18.88 |
| $65,000–74,999 | 907 | 26.80 |
| $75,000+ | 1287 | 38.03 |
| Radiation | ||
| No | 2993 | 88.45 |
| Yes | 391 | 11.55 |
| Chemotherapy | ||
| No | 1616 | 47.75 |
| Yes | 1768 | 52.25 |
| Surgery ± radiation | ||
| No | 3154 | 93.20 |
| Yes | 230 | 6.80 |
| Surgery | ||
| No | 2492 | 73.64 |
| Yes | 892 | 26.36 |
| Pleural effusion | ||
| None | 365 | 10.79 |
| Benign | 726 | 21.45 |
| Malignant | 1308 | 38.65 |
| Pleural effusion, NOS | 985 | 29.11 |
| Year of diagnosis | ||
| 2010 | 430 | 12.71 |
| 2011 | 458 | 13.53 |
| 2012 | 431 | 12.74 |
| 2013 | 431 | 12.74 |
| 2014 | 394 | 11.64 |
| 2015 | 437 | 12.91 |
| 2016 | 401 | 11.85 |
| 2017 | 402 | 11.88 |
Table 2 illustrates the univariate analysis of factors influencing overall mortality (OM) and cancer-specific mortality (CSM). Higher OM was associated with male gender (HR = 1.29, 95% CI 1.19–1.41, p < 0.01), age >80 years (HR = 2.88, 95% CI 1.89–4.41, p < 0.01), age group 60–79 years (HR = 2.01, 95% CI 1.32–3.06, p < 0.01), fibrous epithelioma (HR = 2.39, 95% CI 2.12–2.70, p < 0.01), widowed patients (HR = 1.19, 95% CI 1.07–1.32, p < 0.01), distant metastasis (HR = 1.30, 95% CI 1.15–1.47, p < 0.01), and residence in nonmetropolitan counties not adjacent to a metropolitan area. The aforementioned covariates were associated with higher CSM. Improved OM and CSM was associated with surgical resection of the primary tumor (HR = 0.59, 95% CI 0.54–0.64, p < 0.01), chemotherapy (HR = 0.67, 95% CI 0.62–0.72, p < 0.01), radiation therapy (HR = 0.73, 95% CI 0.66–0.82, p < 0.01), a combination of surgery and radiation (HR = 0.55, 95% CI 0.47–0.63, p < 0.01), and an annual income of $75,000+ (HR = 0.86, 95% CI 0.78–0.96, p < 0.01).
Table 2.
Crude analysis of factors associated with all-cause mortality and MPM related mortality among US patients between 2010 and 2017.
| Characteristics | Overall mortality Crude hazard ratio (95% confidence interval) | MPM-specific mortality Crude hazard ratio (95% confidence interval) |
|---|---|---|
| Gender | ||
| Female | 1 (reference) | 1 (reference) |
| Male | 1.29 (1.19–1.41) ** | 1.31 (1.19–1.43) ** |
| Age at diagnosis, y.o | ||
| 0–39 | 1 (reference) | 1 (reference) |
| 40–59 | 1.37 (0.89–2.11) | 1.35 (0.87–2.10) |
| 60–79 | 2.01 (1.32–3.06) ** | 1.92 (1.25–2.96) ** |
| 80+ | 2.88 (1.89–4.41) ** | 2.72 (1.76–4.19) ** |
| Histologic subtype | ||
| Epithelioid mesothelioma | 1 (reference) | 1 (reference) |
| Fibrous mesothelioma | 2.39 (2.12–2.70) ** | 2.42 (2.14–2.74) ** |
| Malignant mesothelioma, NOS | 1.47 (1.35–1.59) ** | 1.41 (1.29–1.54) ** |
| Biphasic mesothelioma | 1.45 (1.28–1.65) ** | 1.46 (1.28–1.67) ** |
| Marital status | ||
| Married | 1 (reference) | 1 (reference) |
| Single | 1.03 (0.92–1.17) | 1.02 (0.90–1.16) |
| Divorced/separated | 1.05 (0.92–1.19) | 1.03 (0.89–1.19) |
| Widowed | 1.19 (1.07–1.32) ** | 1.16 (1.04–1.29) ** |
| Tumor stage | ||
| Localized | 1 (reference) | 1 (reference) |
| Regional by direct extension only | 0.97 (0.83–1.14) | 1.01 (0.85–1.19) * |
| Regional lymph nodes involved only | 1.25 (0.98–1.59) | 1.22 (0.94–1.58) |
| Regional by both direct extension and lymph node involvement | 1.09 (0.89–1.33) | 1.17 (0.96–1.44) |
| Distant | 1.30 (1.15–1.47) ** | 1.34 (1.18–1.53) ** |
| Race | ||
| Non-Hispanic white | 1 (reference) | 1 (reference) |
| Non-Hispanic black | 1.03 (0.87–1.22) | 1.01 (0.85–1.21) |
| Hispanic | 1.03 (0.92–1.15) | 0.96 (0.86–1.08) |
| Other | 0.99 (0.84–1.19) | 0.95 (0.79–1.14) |
| Living area | ||
| Counties in metropolitan areas of 1 million persons | 1 (reference) | 1 (reference) |
| Counties in metropolitan areas of 250,000 to 1 million persons | 0.99 (0.90–1.08) | 0.99 (0.90–1.09) |
| Counties in metropolitan areas of 250,000 persons | 1.05 (0.91–1.21) | 1.05 (0.91–1.22) |
| Nonmetropolitan counties adjacent to a metropolitan area | 1.14 (0.98–1.31) | 1.18 (1.02–1.37) * |
| Nonmetropolitan counties not adjacent to a metropolitan area | 1.23 (1.03–1.47) * | 1.28 (1.07–1.53) ** |
| Income per year | ||
| $< $55,000 | 1 (reference) | 1 (reference) |
| $55,000–64,999 | 0.95 (0.84–1.07) | 0.95 (0.84–1.08) |
| $65,000–74,999 | 0.92 (0.82–1.03) | 0.9 (0.80–1.01) |
| $75,000+ | 0.86 (0.78–0.96) ** | 0.86 (0.77–0.97) * |
| Surgery ± radiation | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 0.55 (0.47–0.63) ** | 0.55 (0.48–0.64) ** |
| Chemotherapy | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 0.67 (0.62–0.72) ** | 0.69 (0.64–0.74) ** |
| Radiation | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 0.73 (0.66–0.82) ** | 0.75 (0.67–0.84) ** |
| Surgery | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 0.59 (0.54–0.64) ** | 0.58 (0.54–0.64) ** |
| Pleural effusion | ||
| None | 1 (reference) | 1 (reference) |
| Benign | 1.09 (0.96–1.26) | 1.15 (0.99–1.33) |
| Malignant | 1.16 (1.02–1.32) * | 1.21 (1.06–1.38) ** |
| Pleural effusion, NOS | 1.14 (1.01–1.31) * | 1.19 (1.03–1.36) * |
p < 0.01,
p < 0.05.
Multivariate regression analyses, adjusting for covariates in Table 3, revealed higher OM in male patients (HR = 1.24, 95% CI 1.14–1.37, p < 0.01), elderly patients aged >80 years (HR = 2.17, 95% CI 1.41–3.35, p < 0.01), fibrous mesothelioma (HR = 2.21, 95% CI 1.95–2.51, p < 0.01), and patients with distant metastasis (HR = 1.55, 95% CI 1.34–1.81, p < 0.01). CSM mortality was also higher in these groups and amongst patients with pleural effusion with negative cytology (HR = 1.22, 95% CI 1.05–1.4, p < 0.05). Lower OM and CSM were associated with available interventions, such as a combination of surgery and radiation, chemotherapy, and radiation alone.
Table 3.
Multivariate cox proportional hazard regression analyses of factors affecting all-cause mortality and MPM related mortality among US patients between 2010 and 2017.
| Characteristics | Overall mortality Crude hazard ratio (95% confidence interval) | MPM-specific mortality Crude hazard ratio (95% confidence interval) |
|---|---|---|
| Gender | ||
| Female | 1 (reference) | 1 (reference) |
| Male | 1.24 (1.14–1.37) ** | 1.25 (1.13–1.38) ** |
| Age at diagnosis, y.o | ||
| 0–39 | 1 (reference) | 1 (reference) |
| 40–59 | 1.31 (0.84–2.02) | 1.28 (0.82–2.01) |
| 60–79 | 1.78 (1.17–2.74) ** | 1.68 (1.08–2.59) * |
| 80+ | 2.17 (1.41–3.35) ** | 2.02 (1.29–3.15) ** |
| Histologic subtype | ||
| Epithelioid mesothelioma | 1 (reference) | 1 (reference) |
| Fibrous mesothelioma | 2.21 (1.95–2.51) ** | 2.24 (1.97–2.55) ** |
| Malignant mesothelioma, NOS | 1.24 (1.14–1.35) ** | 1.19 (1.09–1.30) ** |
| Biphasic mesothelioma | 1.58 (1.39–1.79) ** | 1.58 (1.39–1.81) ** |
| Marital status | ||
| Married | 1 (reference) | 1 (reference) |
| Single | 1.13 (0.99–1.27) | 1.12 (0.98–1.27) |
| Divorced/separated | 1.13 (0.99–1.29) | 1.11 (0.97–1.28) |
| Widowed | 1.09 (0.98–1.23) | 1.09 (0.97–1.23) |
| Tumor stage | ||
| Localized | 1 (reference) | 1 (reference) |
| Regional by direct extension only | 1.06 (0.9–1.25) | 1.09 (0.92–1.29) |
| Regional lymph nodes involved only | 1.28 (0.99–1.64) | 1.26 (0.97–1.64) |
| Regional by both direct extension and lymph node involvement | 1.39 (1.14–1.71) ** | 1.50 (1.22–1.85) ** |
| Distant | 1.55 (1.34–1.81) ** | 1.59 (1.36–1.87) ** |
| Race | ||
| Non-Hispanic white | 1 (reference) | 1 (reference) |
| Non-Hispanic black | 1.08 (0.91–1.28) | 1.06 (0.89–1.28) |
| Hispanic | 1.11 (0.99–1.24) | 1.03 (0.91–1.16) |
| Other | 1.09 (0.91–1.29) | 1.02 (0.85–1.23) |
| Living area | ||
| Counties in metropolitan areas of 1 million persons | 1 (reference) | 1 (reference) |
| Counties in metropolitan areas of 250,000 to 1 million persons | 0.99 (0.9–1.09) | 0.99 (0.90–1.09) |
| Counties in metropolitan areas of 250,000 persons | 1.05 (0.89–1.24) | 1.05 (0.89–1.24) |
| Nonmetropolitan counties adjacent to a metropolitan area | 1.02 (0.86–1.21) | 1.07 (0.89–1.28) |
| Nonmetropolitan counties not adjacent to a metropolitan area | 1.1 (0.89–1.36) | 1.15 (0.93–1.42) |
| Income per year | ||
| $< $55,000 | 1 (reference) | 1 (reference) |
| $55,000–64,999 | 0.97 (0.85–1.11) | 0.99 (0.87–1.15) |
| $65,000–74,999 | 0.97 (0.84–1.12) | 0.97 (0.84–1.13) |
| $75,000+ | 0.96 (0.84–1.11) | 0.99 (0.85–1.15) |
| Surgery ± radiation | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 0.68 (0.54–0.86) ** | 0.68 (0.53–0.86) ** |
| Chemotherapy | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 0.74 (0.69–0.80) ** | 0.77 (0.71–0.83) ** |
| Radiation | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 1.09 (0.93–1.29) | 1.13 (0.96–1.35) |
| Surgery | ||
| No | 1 (reference) | 1 (reference) |
| Yes | 0.76 (0.69–0.84) ** | 0.73 (0.66–0.81) ** |
| Pleural effusion | ||
| None | 1 (reference) | 1 (reference) |
| Benign | 1.15 (0.99–1.32) | 1.22 (1.05–1.4) * |
| Malignant | 0.97 (0.83–1.13) | 1.02 (0.87–1.21) |
| Pleural effusion, NOS | 0.95 (0.81–1.10) | 0.98 (0.84–1.16) |
p < 0.01,
p < 0.05.
4. Discussion
In this US-based study on malignant pleural mesothelioma (MPM), we observed a male and non-Hispanic White predominance, consistent with existing literature. Over half of our cohort (52.25%) underwent chemotherapy, highlighting its prevalent use. Our findings identified key determinants of mortality, encompassing tumor stage, age, gender, histologic subtype, and pleural fluid cytology.
The observed male and White predominance aligns with existing literature.11 Consistent with prior studies, epithelioid MPM emerged as the predominant histologic subtype, constituting two-thirds of cases (41.78%).13 While pleural effusion typically accompanies the diagnosis, our study revealed a slight deviation, with up to 10% of our cohort lacking pleural effusion at the time of diagnosis.14
Analysis of socioeconomic and demographic factors unveiled that the majority of MPM patients resided in metropolitan areas, with an annual income exceeding $75,000 (38.03%). This association underscores the challenging and delayed diagnosis of MPM, a process necessitating extensive testing that individuals with higher income and those residing in metropolitan areas are more likely to afford and access.15–18
Survival trends aligned with the findings of Taioli's previous research, showcasing improved outcomes in younger patients, females, and those diagnosed at an early stage.11 This trend was noted in univariate analysis. Multivariate analysis further revealed enhanced survival amongst female patients, those with earlier disease stages, and younger patients. Similar to Taioli's study, our analysis demonstrated that all available interventions were associated with lower mortality. Despite these positive associations, the overall prognosis for MPM remains bleak, with overall survival ranging from 9 to 17 months post-diagnosis due to late diagnosis. 19–21 Our investigation emphasizes the critical need to identify patient subsets that could benefit from early MPM screening, given the statistically significant association between early diagnosis and improved outcomes for this malignancy characterized by an otherwise dismal prognosis.
Concerning pleural effusion, our study deviates from historical prognostic patterns. While malignant pleural effusion has been associated with aggressive disease in various malignancies,22 our data reveals that over the past decade, pleural effusion did not impact overall mortality. However, patients with pleural effusion and negative cytology exhibited a higher CSM in various cancers23,24 and no effect on OM, indicating complications of MPM, rather than the disease itself as a driving factor. Notably, advanced MPM can lead to heart failure, and parapneumonic effusion, further complicating the clinical picture.25
4.1. Strengths and limitations
This study's strength lies in its reliance on the largest cancer database in the USA that enabled enrolment of an adequate sample size for such a rare pathologic entity. Despite the valuable insights provided by our study, several limitations exist that can be addressed by further research. Absence of data on immunotherapy and comorbidities coupled with incomplete estimates on chemotherapy in the SEER database are notable shortcomings. Further research looking at these variables can yield important therapeutic and prognostic information.
5. Conclusions
This study assessing the epidemiologic and mortality outcomes amongst MPM patients over the past decade yielded important prognostic information. Treatment improves overall and cancer-specific mortality statistics, but most cases are intercepted at advanced stages, thereby resulting in a dismal prognosis. Pleural effusion as a complication worsens prognosis. Further studies to determine the efficacy of comprehensive monitoring protocols and early intervention strategies could help optimize survival outcomes in these patients.
Footnotes
Statement of ethics: The SEER Dataset was a public-use dataset, of which the informed consent was waived.
Conflict of interest statement: No potential conflict of interest was reported by the authors.
Funding sources: No Funding was received.
Data availability statement
The data used and/or analyzed in this study are available in the Surveillance, Epidemiology, and End Results (SEER) Database of the National Cancer Institute (http://seer.cancer.gov).
References
- 1. Teta MJ, Mink PJ, Lau E, Sceurman BK, Foster ED. US mesothelioma patterns 1973–2002: indicators of change and insights into background rates. Eur J Cancer Prev. 2008;17(6):525–534. doi: 10.1097/CEJ.0b013e3282f0c0a2. [DOI] [PubMed] [Google Scholar]
- 2. Price B. Analysis of current trends in United States mesothelioma incidence. Am J Epidemiol. 1997;145(3):211–218. doi: 10.1093/oxfordjournals.aje.a009093. [DOI] [PubMed] [Google Scholar]
- 3. Tward JD, Wendland MM, Shrieve DC, Szabo A, Gaffney DK. The risk of secondary malignancies over 30 years after the treatment of non-Hodgkin lymphoma. Cancer. 2006;107(1):108–115. doi: 10.1002/cncr.21971. [DOI] [PubMed] [Google Scholar]
- 4. Teta MJ, Lau E, Sceurman BK, Wagner ME. Therapeutic radiation for lymphoma: risk of malignant mesothelioma. Cancer. 2007;109(7):1432–1438. doi: 10.1002/cncr.22526. [DOI] [PubMed] [Google Scholar]
- 5. The Lancet O. Space elevators, tennis racquets, and mesothelioma. Lancet Oncol. 2008;9(7):601. doi: 10.1016/S1470-2045(08)70157-8. [DOI] [PubMed] [Google Scholar]
- 6. Bocchetta M, Eliasz S, De Marco MA, Rudzinski J, Zhang L, Carbone M. The SV40 large T antigen-p53 complexes bind and activate the insulin-like growth factor-I promoter stimulating cell growth. Cancer Res. 2008;68(4):1022–1029. doi: 10.1158/0008-5472.CAN-07-5203. [DOI] [PubMed] [Google Scholar]
- 7. Panou V, Gadiraju M, Wolin A, et al. Frequency of germline mutations in cancer susceptibility genes in malignant mesothelioma. J Clin Oncol. 2018;36(28):2863–2871. doi: 10.1200/JCO.2018.78.5204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Socola F, Loaiza-Bonilla A, Bustinza-Linares E, Correa R, Rosenblatt JD. Recurrent thrombotic thrombocytopenic purpura-like syndrome as a paraneoplastic phenomenon in malignant peritoneal mesothelioma: a case report and review of the literature. Case Rep Oncol Med. 2012;2012:619348. doi: 10.1155/2012/619348. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Bech C, Sørensen JB. Polyneuropathy in a patient with malignant pleural mesothelioma: a paraneoplastic syndrome. J Thorac Oncol. 2008;3(11):1359–1360. doi: 10.1097/JTO.0b013e3181872764. [DOI] [PubMed] [Google Scholar]
- 10. Kindler HL, Ismaila N, Armato SG, 3rd, et al. Treatment of malignant pleural mesothelioma: American Society of clinical oncology clinical practice guideline. J Clin Oncol. 2018;36(13):1343–1373. doi: 10.1200/JCO.2017.76.6394. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Taioli E, Wolf AS, Camacho-Rivera M, et al. Determinants of survival in malignant pleural mesothelioma: a surveillance, epidemiology, and end results (SEER) study of 14,228 patients. PLoS One. 2015;10(12):e0145039. doi: 10.1371/journal.pone.0145039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Duggan MA, Anderson WF, Altekruse S, Penberthy L, Sherman ME. The surveillance, epidemiology, and end results (SEER) Program and pathology: toward strengthening the critical relationship. Am J Surg Pathol. 2016;40(12) doi: 10.1097/PAS.0000000000000749. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Zhang YZ, Brambilla C, Molyneaux PL, et al. Presence of pleomorphic features but not growth patterns improves prognostic stratification of epithelioid malignant pleural mesothelioma by 2-tier nuclear grade. Histopathology. 2020;77(3):423–436. doi: 10.1111/his.14127. [DOI] [PubMed] [Google Scholar]
- 14. Patz EF, Jr, Shaffer K, Piwnica-Worms DR, et al. Malignant pleural mesothelioma: value of CT and MR imaging in predicting resectability. AJR Am J Roentgenol. 1992;159(5):961–966. doi: 10.2214/ajr.159.5.1414807. [DOI] [PubMed] [Google Scholar]
- 15. Tanriverdi O, Meydan N, Barutca S, Ozsan N, Gurel D, Veral A. Anti-Yo antibody-mediated paraneoplastic cerebellar degeneration in a female patient with pleural malignant mesothelioma. Jpn J Clin Oncol. 2013;43(5):563–568. doi: 10.1093/jjco/hyt031. [DOI] [PubMed] [Google Scholar]
- 16. Bangolo AI, Fwelo P, Trivedi C, et al. Interaction between age and gender on survival outcomes in extramedullary multiple myeloma over the past two decades. World J Clin Oncol. 2023;14(4):179–189. doi: 10.5306/wjco.v14.i4.179. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Bangolo A, Fwelo P, Iyer KM, et al. Primary cardiac sarcoma: clinical characteristics and prognostic factors over the past 2 decades. Diseases. 2023;11(2) doi: 10.3390/diseases11020074. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Bangolo A, Fwelo P, Sagireddy S, et al. Interaction between age and primary site on survival outcomes in primary GI melanoma over the past decade. Med Sci (Basel) 2023;11(2) doi: 10.3390/medsci11020032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Vogelzang NJ, Rusthoven JJ, Symanowski J, et al. Phase III study of pemetrexed in combination with cisplatin versus cisplatin alone in patients with malignant pleural mesothelioma. J Clin Oncol. 2003;21(14):2636–2644. doi: 10.1200/JCO.2003.11.136. [DOI] [PubMed] [Google Scholar]
- 20. Ahamad A, Stevens CW, Smythe WR, et al. Promising early local control of malignant pleural mesothelioma following postoperative intensity modulated radiotherapy (IMRT) to the chest. Cancer J. 2003;9(6):476–484. doi: 10.1097/00130404-200311000-00008. [DOI] [PubMed] [Google Scholar]
- 21. Krug LM, Pass HI, Rusch VW, et al. Multicenter phase II trial of neoadjuvant pemetrexed plus cisplatin followed by extrapleural pneumonectomy and radiation for malignant pleural mesothelioma. J Clin Oncol. 2009;27(18):3007–3013. doi: 10.1200/JCO.2008.20.3943. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Kamble R, Wilson CS, Fassas A, et al. Malignant pleural effusion of multiple myeloma: prognostic factors and outcome. Leuk Lymphoma. 2005;46(8):1137–1142. doi: 10.1080/10428190500102845. [DOI] [PubMed] [Google Scholar]
- 23. Porcel JM, Cuadrat I, García-Cerecedo T, Pardina M, Bielsa S. Pleural effusions in diffuse large B-cell lymphoma: clinical and prognostic significance. Lung. 2019;197(1):47–51. doi: 10.1007/s00408-018-0182-y. [DOI] [PubMed] [Google Scholar]
- 24. Sugiura S, Ando Y, Minami H, Ando M, Sakai S, Shimokata K. Prognostic value of pleural effusion in patients with non-small cell lung cancer. Clin Cancer Res. 1997;3(1):47–50. [PubMed] [Google Scholar]
- 25. Heelan RT, Rusch VW, Begg CB, Panicek DM, Caravelli JF, Eisen C. Staging of malignant pleural mesothelioma: comparison of CT and MR imaging. Am J Roentgenol. 1999;172(4):1039–1047. doi: 10.2214/ajr.172.4.10587144. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used and/or analyzed in this study are available in the Surveillance, Epidemiology, and End Results (SEER) Database of the National Cancer Institute (http://seer.cancer.gov).