Abstract
Background:
The incidence of cholangiocarcinoma and gallbladder cancer has been increasing and decreasing respectively in the United States, whereas their mortality has been declining since 1980, which suggests improved overall survival of biliary tract cancers (BTC). We aimed to investigate temporal trends of BTC stages and survival and their associations with demographic factors.
Methods:
A total of 55,163 BTC patients collected from 2000 to 2018 from the National Cancer Institute Surveillance, Epidemiology, and End Results 18 registry were included in this study. We assessed the temporal trend of BTC stages with diagnosis years using the annual percentage of change (APC) in the proportion of the stages. We estimated the association of BTC survival and stages with diagnosis years and demographic factors using the Cox regression models.
Results:
While localized BTC proportion remained little changed from 2006 to 2018, the proportion of regional and distant BTCs significantly decreased (APC=−2.3%) and increased (APC=2.7%), respectively, through the years. The overall and cancer-specific survival increased from 41.0% and 47.3% in 2000–2004 to 51.2% and 53.8% in 2015–2018, respectively. BTC patients who were older, black, unmarried, or had lower socioeconomic status had significantly poorer overall survival.
Conclusions:
We found that distant and regional BTC significantly increased and decreased, respectively, and the BTC survival significantly improved over time. Age, sex, race, SES, and marital status were significantly associated with overall survival and less evidently with cancer-specific survival of BTC patients.
Impact:
Our findings suggest that demographic factors were associated with BTC stages and BTC survival.
Keywords: biliary tract cancer, survival, stage, temporal trend
Introduction
Biliary tract cancers (BTCs) originate in the ductal epithelium of the biliary tree and include gallbladder cancer, intrahepatic bile duct (IBD) cancer, extrahepatic bile duct cancer(EBD), and ampullary cancer 1. BTCs are rare but among the most fatal cancers in Europe and North America 2. The 5-year survival is lower than 10% for gallbladder cancer 3 and about 12% for IBD and EBD 4.
Recent studies using the Surveillance, Epidemiology, and End Results (SEER) database investigated the temporal trends in incidence and mortality of cholangiocarcinoma 4,5 and gallbladder cancer 6,7 in the United States. The incidence of cholangiocarcinoma, particularly IBD cancer, has been increasing, whereas the incidence of gallbladder cancer has decreased over the past five decades. On the other hand, the mortality of both cholangiocarcinoma and gallbladder cancer has been declining since 1980, suggesting that the overall survival of BTC has improved over recent decades.
A recent study 4 evaluated prognostic factors for the overall survival of patients with IBD or EBD diagnosed from 1973–2008 in the United States and found that overall survival improved over time. However, prognostic factors for other BTCs are still understudied.
Considering the increasing incidence, decreasing mortality, and better overall survival of cholangiocarcinoma patients over time, it is speculated that early detection or improved treatment may have played a role in this temporal trend, although the surveillance programs for detecting early-stage cancer have not been established in BTCs. To this end, this study aimed to assess the temporal trend of BTC stages at the diagnosis and the association of BTC stages with BTC survival, to assess whether the previously reported significant associations of demographic factors for cholangiocarcinoma have continued beyond 2008, and to assess whether these demographic factors also affect the survival of other types of BTCs including gallbladder cancer and ampullary cancer.
Materials And Methods
Data source and study population
The patients of BTCs of this study, including IBD cancer (ICD-O-3 site C22.1), gallbladder cancer (C23.9), EBD cancer (C24.0), ampullary cancer (C24.1), overlapping lesion of biliary tract (C24.8) and not otherwise specified biliary tract cancer (C24.9), were collected from 2000 to 2018 from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) 18 registry with data from 18 geographic areas since 2000 [Surveillance Epidemiology and End Results (RRID:SCR_006902)]. SEER is commonly judged as the gold standard for reliable and quality data among the US cancer registries. SEER currently collects and publishes cancer incidence and survival data from population-based cancer registries covering approximately 48 percent of the U.S. population. Demographic variables (age at diagnosis, year of diagnosis, race, sex, neighborhood socioeconomic status, and marital status) and cancer stages were obtained from the registry. Patients’ age at diagnosis was categorized into five groups: <50, 50–59, 60–69, 70–79, and >=80 years. Patients’ race was categorized as non-Hispanic whites (NHW), non-Hispanic Blacks (NHB), Hispanics, American Indians/Alaska Natives (AI/AN), Asians and Pacific Islanders (API)], and unknown race. Socioeconomic Status (SES) was classified into five quintiles, lowest (group 1), lower-middle (group 2), middle (group 3), higher-middle (group 4), and highest (group 5) based on the Yost score. The Yost score is a composite index of socioeconomic status based on principal component analysis of block group level census variables such as education, income, and occupation 8. Cancer summary stages are classified as “localized” if there is no sign that cancer has spread outside of the bile ducts, “regional” if cancer has spread outside the bile ducts to nearby structures or lymph nodes, or “distant” if cancer has spread to distant parts of the body, such as the lungs. The information on BTC summary stages is available for patients diagnosed in 2006 or later.
Statistical analysis
The primary endpoint of this study was all causes of death and cancer-specific death. The latter was defined as a death with the BTCs listed as the primary cause of death. We estimated cancer-specific survival instead of relative survival because it can be performed using the same standard survival analysis method for overall survival with the flexibility to address potential confounding bias9. Survival times were measured in months and were censored at the date of a patient being lost to follow-up, the date of death, or on December 31, 2018, whichever occurred first. Cancer-specific survival times were also censored at the date of death from causes not considered as deaths due to the BTCs.
Survival rates and 95% confidence intervals (CIs) were calculated using the Kaplan-Meier method. We chose to report 1-year survival because the median survival time of all BTC patients in this analysis was only 0.75 years (the interquartile range: 0.25 to 1.83 years), and the 5-year survival analysis was not available for patients diagnosed in 2015 or later. To evaluate the temporal trend of BTC stages, we fitted the least-squares regression model for the natural logarithm of the proportion of BTC stages by the year of diagnosis. The annual percentage of change (APC) in the proportion of BTC stages was estimated as the natural exponential of the regression coefficient minus 110. The odds ratios (ORs) and 95% CIs for the association between demographic factors and BTC stages were estimated with the multivariate multinormal logistic regression models. Hazard ratios (HRs) and 95% (CIs) for overall and cancer-specific survival associated with demographic factors and cancer stages were estimated using multivariate Cox proportional hazards models. The model proportional assumption was evaluated by visually checking the Schoenfeld residual plots and log-log survival plots for each variable included in the models. We carried out a stratified Cox procedure to handle covariates that did not appear to satisfy the proportional assumption11.
Data availability
The data used in this study are publicly available which can be accessed at https://www.cdc.gov/cancer/uscs/public-use/obtain-data.htm.
Results
Included in this analysis were 55,163 BTC patients who were diagnosed from 2000 to 2018 and had survival times > 0 months. The median age at diagnosis of these patients was 70 years old. As shown in Table 1, the majority (74.7%) of the patients were NHW, followed by API (11.4%), NHB (9.3%), Hispanic (3.6%), and AI/AN (0.8%). Of all BTC patients, 16,447 had gallbladder cancer, 12,844 had IBD cancer, 13,941 had EBD cancer, 9,102 had ampullary cancer, 183 had overlapping lesions of the biliary tract, and 2,646 cases’ diagnoses were not specified. The BTC patients had poor survival with the 1-year crude overall and cancer-specific survival rates (95% CI) being 44.6% (44.2%–45.0%) and 52.3% (51.9%–52.8), respectively. The overall and cancer-specific survival increased from 41.0% and 47.3% in 2000–2004 to 51.2% and 53.8% in 2015–2018, respectively. Patients who were diagnosed in earlier years vs later years, who were older vs younger at diagnosis, who had lower SES vs higher SES, who were not being married vs. married, and who were female vs. male had lower crude overall and cancer-specific survival rates. NHB patients among all races, patients with distant stage among all stages, and IBD cancer patients among all cancer types had the lowest crude overall and cancer-specific survival rates.
Table 1.
Frequencies and 1-year crude survival rates of BTCs
| 1-year Overall survival | 1-year Cancer-specific survival | ||||
|---|---|---|---|---|---|
| Total | No of death | Survival (95% CI) | No of death | Survival (95% CI) | |
| Year of diagnosis | |||||
| 2000–2004 | 10976 | 10,167 | 0.410(0.401–0.420) | 7203 | 0.512(0.502–0.522) |
| 2005–2009 | 12778 | 11,513 | 0.431(0.423–0.440) | 8714 | 0.512(0.503–0.521) |
| 2010–2014 | 16189 | 13,730 | 0.459(0.451–0.467) | 10942 | 0.528(0.520–0.536) |
| 2015–2018 | 15220 | 9,304 | 0.473(0.464–0.482) | 7695 | 0.538(0.529–0.547) |
| Age at diagnosis | |||||
| 1–49 | 4052 | 2847 | 0.573(0.558–0.589) | 2512 | 0.611(0.595–0.627) |
| 50–59 | 8599 | 6479 | 0.526(0.515–0.537) | 5491 | 0.568(0.557–0.579) |
| 60–69 | 14257 | 11023 | 0.495(0.487–0.504) | 8903 | 0.556(0.548–0.565) |
| 70–79 | 15618 | 12914 | 0.429(0.421–0.437) | 9610 | 0.516(0.508–0.525) |
| >=80 | 12637 | 11451 | 0.318(0.310–0.326) | 8038 | 0.431(0.422–0.441) |
| Sex | |||||
| Female | 29670 | 24065 | 0.438(0.432–0.444) | 18958 | 0.508(0.502–0.514) |
| Male | 25493 | 20649 | 0.456(0.449–0.462) | 15596 | 0.542(0.535–0.548) |
| Race | |||||
| NHW | 41190 | 33521 | 0.445(0.440–0.450) | 25710 | 0.524(0.519–0.530) |
| API | 6274 | 4884 | 0.477(0.465–0.490) | 3930 | 0.541(0.528–0.554) |
| NHB | 5145 | 4174 | 0.421(0.407–0.435) | 3278 | 0.496(0.482–0.511) |
| Hispanic | 1973 | 1712 | 0.431(0.410–0.454) | 1294 | 0.515(0.492–0.538) |
| AI/AN | 442 | 369 | 0.415(0.371–0.464) | 304 | 0.459(0.413–0.510) |
| Unknown | 139 | 54 | 0.690(0.609–0.782) | 38 | 0.758(0.682–0.842) |
| Socioeconomic status | |||||
| Group 5 | 13227 | 10446 | 0.491(0.482–0.500) | 8066 | 0.565(0.556–0.574) |
| Group 4 | 11307 | 9125 | 0.450(0.440–0.459) | 7098 | 0.525(0.515–0.535) |
| Group 3 | 9678 | 7919 | 0.437(0.427–0.447) | 6130 | 0.514(0.504–0.525) |
| Group 2 | 9069 | 7406 | 0.425(0.415–0.436) | 5681 | 0.506(0.495–0.517) |
| Group 1 | 8443 | 6976 | 0.409(0.399–0.420) | 5407 | 0.490(0.478–0.501) |
| Unknown | 3439 | 2842 | 0.429(0.413–0.446) | 2172 | 0.510(0.492–0.528) |
| Marital status | |||||
| Married | 30070 | 23862 | 0.463(0.477–0.488) | 18546 | 0.556(0.550–0.562) |
| Single | 7041 | 5560 | 0.436(0.424–0.448) | 4400 | 0.508(0.496–0.521) |
| Separated/Divorced | 5111 | 4139 | 0.432(0.418–0.446) | 3329 | 0.500(0.486–0.515) |
| Widowed | 10583 | 9320 | 0.352(0.343–0.362) | 6896 | 0.446(0.435–0.456) |
| Unknown/unmarried | 2358 | 1833 | 0.465(0.445–0.486) | 1383 | 0.548(0.527–0.570) |
| Stage | |||||
| Localized | 7245 | 4578 | 0.627(0.616–0.639) | 3193 | 0.712(0.701–0.723) |
| Regional | 16037 | 11430 | 0.600(0.592–0.608) | 8814 | 0.664(0.657–0.672) |
| Distant | 14755 | 13072 | 0.251(0.244–0.259) | 11324 | 0.301(0.293–0.310) |
| Unknown | 17126 | 15634 | 0.391(0.384–0.399) | 11223 | 0.493(0.485–0.501) |
| BTC types | |||||
| Intrahepatic bile duct | 12844 | 10633 | 0.384(0.376–0.393) | 9233 | 0.435(0.425–0.444) |
| Gallbladder | 16447 | 13203 | 0.441(0.433–0.449) | 10307 | 0.507(0.498–0.516) |
| Extrahepatic bile duct | 13941 | 12088 | 0.403(0.395–0.412) | 8872 | 0.507(0.498–0.516) |
| Ampulla of Vater | 9102 | 6137 | 0.673(0.663–0.683) | 4044 | 0.761(0.752–0.770) |
| Overlapping lesion | 183 | 167 | 0.349(0.286–0.427) | 120 | 0.438(0.366–0.524) |
| Not otherwise specified | 2646 | 2486 | 0.222(0.207–0.239) | 1978 | 0.303(0.284–0.323) |
Of 17,126 cases with unknown tumor stage as listed in Table 1, 13,394 were diagnosed before 2006. The other 3,732 cases diagnosed in 2006 or later had missing information on tumor stage, thus, were excluded from the analysis for the stages (Figure 1 and Table 2). Figure 1 illustrates the temporal trends in proportions of different BTC summary stages among all BTC patients, based on years of diagnosis since 2006. While the proportion of localized BTCs remained little changed (from 20.6% in 2006 to 21.0% in 2018, APC=−0.3%, P=0.630), the proportion of regional and distant BTCs significantly decreased (from 47.0% in 2006 to 34.2% in 2018, APC=−2.3%, P=5.18E-6) and increased (from 32.4% in 2006 to 44.8% in 2018, APC=2.7%, P=4.60E-6), respectively. We further analyzed the temporal changes of the proportions of summary stages by BTC types and found that the patterns of changes were similar for all types of BTCs.
Figure 1.
Temporal trend of proportions of different BTC summary stages. While the proportion of localized BTCs remained little changed over the time, the proportion of regional and distant BTCs significantly decreased and increased, respectively. Data are from the SEER 18 registry.
Table 2.
OR and 95% CI for the association of demographic factors with caner summary stages among all BTC cases combined
| Localized | Regional | Distant | Distant vs Localized | Regional vs Localized | |||
|---|---|---|---|---|---|---|---|
| N=7245 | N=16037 | N=14755 | OR (95% CI)* | P | OR (95% CI)* | P | |
| Year of diagnosis | |||||||
| 2006–2009 | 1876 | 4346 | 3019 | 1.00 (reference) | 1.00 (reference) | ||
| 2010–2014 | 2608 | 6336 | 5790 | 1.36 (1.26 – 1.47) | 6.80E-16 | 1.04 (0.96 – 1.11) | 3.30E-01 |
| 2015–2018 | 2761 | 5355 | 5946 | 1.31 (1.22 – 1.41) | 7.07E-13 | 0.82 (0.76 – 0.88) | 4.93E-08 |
| Age at diagnosis | |||||||
| <50 | 430 | 1100 | 1263 | 1.00 (reference) | 1.00 (reference) | ||
| 50–59 | 946 | 2671 | 2778 | 0.98 (0.86 – 1.12) | 8.03E-01 | 1.11 (0.97 – 1.27) | 1.25E-01 |
| 60–69 | 1753 | 4461 | 4475 | 0.84 (0.75 – 0.96) | 7.27E-03 | 1.00 (0.89 – 1.14) | 9.44E-01 |
| 70–79 | 2025 | 4654 | 4017 | 0.66 (0.58 – 0.74) | 2.93E-11 | 0.91 (0.80 – 1.03) | 1.27E-01 |
| >=80 | 2091 | 3151 | 2222 | 0.35 (0.31 – 0.40) | 1.11E-56 | 0.59 (0.52 – 0.67) | 1.42E-15 |
| Sex | |||||||
| Female | 3707 | 8364 | 8146 | 1.00 (reference) | 1.00 (reference) | ||
| Male | 3538 | 7673 | 6609 | 0.81 (0.76 – 0.86) | 3.17E-12 | 0.92 (0.87 – 0.98) | 5.58E-03 |
| Race | |||||||
| NHW | 5650 | 12407 | 11376 | 1.00 (reference) | 1.00 (reference) | ||
| API | 857 | 1936 | 1643 | 0.92 (0.84 – 1.01) | 6.68E-02 | 1.00 (0.91 – 1.09) | 9.37E-01 |
| NHB | 657 | 1501 | 1592 | 1.13 (1.02 – 1.25) | 1.52E-02 | 1.03 (0.93 – 1.14) | 5.42E-01 |
| AI/AN | 54 | 136 | 116 | 0.98 (0.70 – 1.36) | 8.97E-01 | 1.11 (0.81 – 1.53) | 5.12E-01 |
| Hispanic | 0 | 0 | 0 | NA | NA | NA | NA |
| Unknown | 27 | 57 | 28 | 0.46 (0.27 – 0.79) | 4.64E-03 | 0.97 (0.61 – 1.55) | 9.14E-01 |
| Socioeconomic status | |||||||
| Group 5 | 1146 | 2394 | 2236 | 1.00 (reference) | 1.00 (reference) | ||
| Group 4 | 1140 | 2553 | 2389 | 0.96 (0.88 – 1.04) | 3.36E-01 | 0.95 (0.87 – 1.03) | 2.11E-01 |
| Group 3 | 1276 | 2661 | 2601 | 0.93 (0.85 – 1.02) | 1.30E-01 | 0.87 (0.79 – 0.95) | 1.36E-03 |
| Group 2 | 1517 | 3411 | 3078 | 0.94 (0.86 – 1.03) | 1.84E-01 | 0.92 (0.84 – 1.01) | 7.74E-02 |
| Group 1 | 1797 | 4228 | 3712 | 0.83 (0.76 – 0.92) | 1.67E-04 | 0.84 (0.77 – 0.93) | 3.90E-04 |
| Unknown | 369 | 790 | 739 | 0.92 (0.79 – 1.06) | 2.54E-01 | 0.95 (0.85 – 1.07) | 4.41E-01 |
| Marital status | |||||||
| 1Married | 3921 | 9114 | 8198 | 1.00 (reference) | 1.00 (reference) | ||
| 2Single | 913 | 2139 | 2134 | 0.99 (0.90 – 1.08) | 7.81E-01 | 0.97 (0.89 – 1.06) | 5.71E-01 |
| 3Separated/Divorced | 658 | 1480 | 1550 | 1.03 (0.93 – 1.14) | 5.39E-01 | 0.93 (0.84 – 1.03) | 1.87E-01 |
| 4Widowed | 1419 | 2614 | 2285 | 1.02 (0.93 – 1.11) | 7.19E-01 | 0.94 (0.86 – 1.02) | 1.31E-01 |
| 5Unknown/unmarried | 334 | 690 | 588 | 0.83 (0.72 – 0.96) | 1.12E-02 | 0.90 (0.79 – 1.03) | 1.36E-01 |
OR and 95% CI were derived from the multinomial logistic regression models, with adjustment for other demographic factors listed in the table.
Using multivariate multinomial logistic regression models, we analyzed the associations of BTC summary stages with demographic factors with mutual adjustment (Table 2). Using the localized BTCs as the reference, which remained little change in proportion from 2000–2018, we found BTC patients diagnosed in later years were more likely to be diagnosed as distant and less likely to be regional, consistent with secular trends of BTC summary stages shown in Figure 1. Patients with older age were less likely to be diagnosed with distant BTC, and only patients with very old age (>=80) were less likely to be diagnosed with regional BTC. Male patients compared with female patients were less likely to be diagnosed with distant or regional BTCs, and so were the patients with the lowest SES.
Table 3 shows the association of diagnosis years with the overall and cancer-specific survival of BTCs with adjustment for the demographic factors listed in Table 2 by BTC types and summary stages. Compared with the years 2000–2004, the overall survival was significantly improved for BTC patients diagnosed in later years [HR (95% CI): 0.96 (0.93 – 0.98) for 2005–2009; 0.91 (0.89 – 0.94) for 2010–2014; and 0.88 (0.86 – 0.91) for 2015–2018] in all BTC patients. Contrary to the findings for the overall survival, improvements in cancer-specific survival for the BTC patients who were diagnosed in later years became not significant for both 2005–2009 and 2010–2014 and less significant for 2015–2018 [HR (95% CI): 0.96 (0.93 – 0.99)]. This association pattern holds for each type of BTCs. When the analysis was stratified by the BTC stages, the reference group was changed to the diagnosis years 2006–2009 because information on BTC summary stages was not available for patients diagnosed before 2006. We found that BTC patients diagnosed in later years had better overall survival and cancer-specific survival across all BTC stages.
Table 3.
HR and 95% CI* for the association of diagnosis years with the survival of BTCs, by BTC types and summary stages
| BTC types | Summary stages | |||||||
|---|---|---|---|---|---|---|---|---|
| All | IBD | Gallbladder | EBD | Ampullary | Localized | Regional | Distant | |
| Overall survival | ||||||||
| 2000–2004 | Reference | Reference | Reference | Reference | Reference | |||
| 2005–2009 | 0.96 (0.93 – 0.98) | 0.89 (0.83 – 0.95) | 0.91 (0.86 – 0.95) | 1.01 (0.96 – 1.07) | 0.92 (0.86 – 0.99) | Reference** | Reference** | Reference** |
| 2010–2014 | 0.91 (0.89 – 0.94) | 0.80 (0.75 – 0.85) | 0.86 (0.82 – 0.91) | 0.97 (0.92 – 1.02) | 0.80 (0.74 – 0.86) | 0.93 (0.87–1.00) | 0.91 (0.87–0.95) | 0.85 (0.81–0.89) |
| 2015–2018 | 0.88 (0.86 – 0.91) | 0.75 (0.70 – 0.80) | 0.84 (0.80 – 0.89) | 0.93 (0.87 – 0.98) | 0.73 (0.67 – 0.79) | 0.81 (0.75–0.88) | 0.87 (0.83–0.91) | 0.83 (0.79–0.87) |
| Cancer-specific survival | ||||||||
| 2000–2004 | Reference | Reference | Reference | Reference | Reference | |||
| 2005–2009 | 0.98 (0.95 – 1.01) | 1.00 (0.93 – 1.07) | 0.98 (0.93 – 1.04) | 1.06 (1.00 – 1.13) | 0.93 (0.86 – 1.02) | Reference** | Reference** | Reference** |
| 2010–2014 | 0.98 (0.95 – 1.01) | 0.94 (0.88 – 1.01) | 0.96 (0.91 – 1.02) | 1.00 (0.94 – 1.06) | 0.80 (0.73 – 0.87) | 0.98 (0.90–1.06) | 0.91 (0.86–0.95) | 0.84 (0.80–0.89) |
| 2015–2018 | 0.96 (0.93 – 0.99) | 0.88 (0.82 – 0.94) | 0.93 (0.87 – 0.99) | 0.96 (0.89 – 1.02) | 0.77 (0.69 – 0.85) | 0.85 (0.77–0.93) | 0.89 (0.84–0.94) | 0.83 (0.79–0.87) |
HR and 95% CI were derived from the Cox proportional models, with adjustment for the demographic factors listed in Table 2.
BTC patients diagnosed from 2006 through 2009 were served as the reference.
The associations of cancer summary stages and demographic factors with the overall survival of BTCs are presented in Table 4. Compared with patients with localized BTCs, patients with regional [HR (95% CI): 1.24(1.19–1.28)] and distant [HR (95% CI): 3.36(3.24–3.48)] BTCs had much higher overall mortality after adjustment for the demographic factors listed in the table. BTC patients who were older or had lower SES had significantly poorer overall survival than patients who were younger or had higher SES. Compared with NHW patients, NHB patients had significantly poorer overall survival [HR (95% CI): 1.05 (1.01–1.08)], while API [HR (95% CI): 0.94 (0.91 – 0.97)] and AI/AN [HR (95% CI): 0.95 (0.90 – 1.00)] patients had significantly better overall survival. Compared with married patients, all those who were single, separated/divorced, or widowed had significantly poorer overall survival. Stratified analyses by BTC types demonstrated that the association patterns remained similar across different BTC types except for sex, which showed higher overall survival for male patients with EBD cancer but lower overall survival for male patients with all other BTC cancers compared with female patients.
Table 4.
HR and 95% CI* for the association of caner summary stages and demographic factors and with the overall survival of BTCs
| All | IBD | Gallbladder | EBD | Ampullary | |
|---|---|---|---|---|---|
| Stage | |||||
| Localized | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Regional | 1.24 (1.19 – 1.28) | 1.79 (1.68 – 1.91) | 2.28 (2.09 – 2.48) | 0.95 (0.89 – 1.02) | 1.13 (1.03 – 1.24) |
| Distant | 3.36 (3.24 – 3.48) | 2.91 (2.74 – 3.10) | 7.31 (6.70 – 7.98) | 2.51 (2.35 – 2.69) | 2.81 (2.53 – 3.13) |
| Year of diagnosis | |||||
| 2000–2004 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 2005–2009 | 0.96 (0.93 – 0.98) | 0.89 (0.83 – 0.95) | 0.91 (0.86 – 0.95) | 1.01 (0.96 – 1.07) | 0.92 (0.86 – 0.99) |
| 2010–2014 | 0.91 (0.89 – 0.94) | 0.80 (0.75 – 0.85) | 0.86 (0.82 – 0.91) | 0.97 (0.92 – 1.02) | 0.80 (0.74 – 0.86) |
| 2015–2018 | 0.88 (0.86 – 0.91) | 0.75 (0.70 – 0.80) | 0.84 (0.80 – 0.89) | 0.93 (0.87 – 0.98) | 0.73 (0.67 – 0.79) |
| Age at diagnosis | |||||
| 1–49 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 50–59 | 1.18 (1.12 – 1.23) | 1.19 (1.09 – 1.29) | 1.16 (1.07 – 1.26) | 1.17 (1.07 – 1.28) | 1.38 (1.21 – 1.57) |
| 60–69 | 1.30 (1.25 – 1.36) | 1.27 (1.17 – 1.37) | 1.26 (1.16 – 1.36) | 1.34 (1.22 – 1.46) | 1.67 (1.48 – 1.89) |
| 70–79 | 1.54 (1.47 – 1.60) | 1.49 (1.38 – 1.61) | 1.44 (1.33 – 1.56) | 1.58 (1.45 – 1.72) | 2.31 (2.05 – 2.61) |
| >=80 | 2.06 (1.97 – 2.15) | 2.11 (1.94 – 2.30) | 1.77 (1.64 – 1.92) | 2.14 (1.96 – 2.34) | 3.82 (3.37 – 4.33) |
| Sex | |||||
| Female | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Male | 1.05 (1.03 – 1.08) | 1.13 (1.09 – 1.18) | 1.09 (1.05 – 1.13) | 0.93 (0.89 – 0.97) | 1.14 (1.08 – 1.21) |
| Race | |||||
| NHW | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| API | 0.94 (0.91 – 0.97) | 0.97 (0.91 – 1.03) | 0.95 (0.89 – 1.01) | 0.92 (0.87 – 0.97) | 0.91 (0.84 – 0.99) |
| NHB | 1.05 (1.01 – 1.08) | 1.06 (0.98 – 1.14) | 1.04 (0.99 – 1.10) | 1.05 (0.98 – 1.13) | 1.16 (1.06 – 1.28) |
| Hispanic | 0.95 (0.90 – 1.00) | 0.97 (0.85 – 1.11) | 0.97 (0.90 – 1.05) | 1.07 (0.96 – 1.20) | 0.89 (0.78 – 1.02) |
| AI/AN | 1.08 (0.98 – 1.20) | 1.27 (1.02 – 1.57) | 1.02 (0.86 – 1.21) | 0.96 (0.76 – 1.21) | 1.05 (0.75 – 1.47) |
| Unknown | 0.46 (0.35 – 0.60) | 0.53 (0.30 – 0.91) | 0.50 (0.32 – 0.77) | 0.57 (0.29 – 1.13) | 0.35 (0.17 – 0.73) |
| Socioeconomic status | |||||
| Group 5 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Group 4 | 1.07 (1.04 – 1.10) | 1.12 (1.06 – 1.18) | 1.06 (1.00 – 1.11) | 1.08 (1.03 – 1.14) | 1.07 (0.99 – 1.16) |
| Group 3 | 1.12 (1.09 – 1.16) | 1.12 (1.05 – 1.18) | 1.05 (1.00 – 1.11) | 1.18 (1.11 – 1.24) | 1.20 (1.11 – 1.31) |
| Group 2 | 1.13 (1.09 – 1.16) | 1.21 (1.14 – 1.29) | 1.06 (1.01 – 1.13) | 1.15 (1.08 – 1.21) | 1.21 (1.12 – 1.32) |
| Group 1 | 1.18 (1.15 – 1.22) | 1.23 (1.15 – 1.31) | 1.10 (1.04 – 1.17) | 1.28 (1.20 – 1.36) | 1.34 (1.23 – 1.46) |
| Unknown | 1.12 (1.07 – 1.17) | 1.08 (0.99 – 1.18) | 1.14 (1.05 – 1.23) | 1.09 (1.01 – 1.18) | 1.28 (1.15 – 1.44) |
| Marital status | |||||
| 1Married | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 2Single | 1.15 (1.12 – 1.19) | 1.09 (1.03 – 1.16) | 1.14 (1.08 – 1.20) | 1.23 (1.16 – 1.31) | 1.21 (1.12 – 1.32) |
| 3Separated/Divorced | 1.15 (1.11 – 1.19) | 1.06 (0.99 – 1.13) | 1.11 (1.05 – 1.18) | 1.24 (1.17 – 1.33) | 1.27 (1.16 – 1.39) |
| 4Widowed | 1.13 (1.10 – 1.16) | 1.14 (1.07 – 1.21) | 1.10 (1.05 – 1.16) | 1.17 (1.11 – 1.24) | 1.15 (1.07 – 1.24) |
| 5Unknown/unmarried | 1.01 (0.96 – 1.06) | 1.06 (0.96 – 1.17) | 1.00 (0.91 – 1.09) | 0.98 (0.90 – 1.08) | 1.03 (0.90 – 1.18) |
HR and 95% CI were derived from the Cox proportional models, with adjustment for other demographic factors listed in the table.
When cancer-specific survival was used as the outcome variable (Table 5), the BTC stages remained the strongest prognostic factor for the cancer-specific survival of BTC patients. Compared with patients with localized BTCs, HR (95% CI) for patients with regional and distant stages were 1.34(1.29–1.40)] and 3.89(3.74–4.05). However, the significant associations between demographic factors and cancer-specific survival were generally weaker than those for the overall survival. Stratified analyses by BTC types showed that male patients with IBD and ampullary cancer had poorer cancer-specific survival than female patients. In comparison, female EBD patients had poorer cancer-specific survival than male patients. The association patterns for other demographic factors and cancer summary stages remained consistent among different BTC types.
Table 5.
HR and 95% CI* for the association of caner summary stages and demographic factors and with the cancer-specific survival of BTCs
| All | IBD | Gallbladder | EBD | Ampullary | |
|---|---|---|---|---|---|
| Stage | |||||
| Localized | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Regional | 1.34 (1.29 – 1.40) | 1.90 (1.78 – 2.04) | 3.26 (2.91 – 3.66) | 1.00 (0.93 – 1.09) | 1.40 (1.24 – 1.58) |
| Distant | 3.89 (3.74 – 4.05) | 3.17 (2.97 – 3.38) | 11.29 (10.06 – 12.67) | 2.78 (2.57 – 3.02) | 3.68 (3.20 – 4.20) |
| Year of diagnosis | |||||
| 2000–2004 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 2005–2009 | 0.99 (0.96 – 1.02) | 1.00 (0.93 – 1.07) | 0.98 (0.93 – 1.04) | 1.06 (1.00 – 1.13) | 0.93 (0.86 – 1.02) |
| 2010–2014 | 0.98 (0.95 – 1.01) | 0.94 (0.88 – 1.01) | 0.96 (0.91 – 1.02) | 1.00 (0.94 – 1.06) | 0.80 (0.73 – 0.87) |
| 2015–2018 | 0.96 (0.93 – 0.99) | 0.88 (0.82 – 0.94) | 0.93 (0.87 – 0.99) | 0.96 (0.89 – 1.02) | 0.77 (0.69 – 0.85) |
| Age at diagnosis | |||||
| 1–49 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 50–59 | 1.11 (1.06 – 1.16) | 1.12 (1.03 – 1.21) | 1.13 (1.04 – 1.24) | 1.10 (1.00 – 1.22) | 1.23 (1.07 – 1.42) |
| 60–69 | 1.16 (1.11 – 1.21) | 1.16 (1.08 – 1.26) | 1.18 (1.08 – 1.28) | 1.17 (1.06 – 1.28) | 1.31 (1.14 – 1.50) |
| 70–79 | 1.26 (1.20 – 1.31) | 1.33 (1.22 – 1.44) | 1.23 (1.13 – 1.34) | 1.26 (1.14 – 1.38) | 1.64 (1.43 – 1.88) |
| >=80 | 1.54 (1.47 – 1.62) | 1.79 (1.64 – 1.96) | 1.34 (1.22 – 1.46) | 1.60 (1.45 – 1.77) | 2.59 (2.25 – 2.99) |
| Sex | |||||
| Female | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Male | 0.99 (0.97 – 1.02) | 1.12 (1.07 – 1.17) | 1.03 (0.99 – 1.08) | 0.88 (0.84 – 0.92) | 1.09 (1.02 – 1.17) |
| Race | |||||
| NHW | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| API | 0.98 (0.95 – 1.02) | 0.98 (0.92 – 1.04) | 0.99 (0.92 – 1.05) | 0.99 (0.93 – 1.05) | 1.02 (0.92 – 1.13) |
| NHB | 1.04 (1.00 – 1.08) | 1.06 (0.98 – 1.16) | 1.04 (0.98 – 1.11) | 1.04 (0.95 – 1.12) | 1.17 (1.04 – 1.32) |
| Hispanic | 0.99 (0.93 – 1.05) | 0.94 (0.81 – 1.09) | 0.98 (0.90 – 1.08) | 1.13 (1.00 – 1.29) | 1.03 (0.88 – 1.21) |
| AI/AN | 1.14 (1.01 – 1.27) | 1.28 (1.02 – 1.61) | 1.03 (0.85 – 1.24) | 1.09 (0.85 – 1.40) | 1.16 (0.77 – 1.73) |
| Unknown | 0.41 (0.29 – 0.56) | 0.47 (0.25 – 0.87) | 0.36 (0.20 – 0.63) | 0.74 (0.36 – 1.52) | 0.30 (0.11 – 0.80) |
| Socioeconomic status | |||||
| Group 5 | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| Group 4 | 1.08 (1.04 – 1.11) | 1.10 (1.04 – 1.17) | 1.03 (0.97 – 1.10) | 1.12 (1.05 – 1.19) | 1.14 (1.04 – 1.26) |
| Group 3 | 1.12 (1.08 – 1.16) | 1.13 (1.06 – 1.20) | 1.03 (0.97 – 1.09) | 1.19 (1.12 – 1.27) | 1.24 (1.12 – 1.37) |
| Group 2 | 1.11 (1.08 – 1.15) | 1.17 (1.09 – 1.25) | 1.03 (0.96 – 1.10) | 1.16 (1.09 – 1.24) | 1.29 (1.17 – 1.43) |
| Group 1 | 1.17 (1.13 – 1.22) | 1.23 (1.15 – 1.32) | 1.07 (1.00 – 1.14) | 1.29 (1.21 – 1.39) | 1.38 (1.24 – 1.53) |
| Unknown | 1.12 (1.07 – 1.17) | 1.06 (0.97 – 1.17) | 1.13 (1.03 – 1.23) | 1.10 (1.00 – 1.21) | 1.31 (1.14 – 1.50) |
| Marital status | |||||
| 1Married | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) | 1.00 (reference) |
| 2Single | 1.12 (1.08 – 1.16) | 1.06 (1.00 – 1.13) | 1.10 (1.03 – 1.17) | 1.22 (1.14 – 1.31) | 1.19 (1.07 – 1.31) |
| 3Separated/Divorced | 1.15 (1.11 – 1.20) | 1.07 (0.99 – 1.14) | 1.11 (1.03 – 1.18) | 1.28 (1.19 – 1.38) | 1.27 (1.14 – 1.42) |
| 4Widowed | 1.13 (1.09 – 1.16) | 1.15 (1.08 – 1.23) | 1.07 (1.02 – 1.14) | 1.20 (1.13 – 1.28) | 1.11 (1.01 – 1.22) |
| 5Unknown/unmarried | 0.97 (0.92 – 1.03) | 1.01 (0.91 – 1.13) | 0.98 (0.89 – 1.08) | 0.94 (0.84 – 1.05) | 1.04 (0.88 – 1.22) |
HR and 95% CI were derived from the Cox proportional models, with adjustment for other demographic factors listed in the table.
Discussion
In this study using SEER data, we have shown that the overall survival of all types of BTCs persistently improved over time. As the strongest prognostic factor for overall and cancer-specific survival, the BTC stages at diagnosis showed a temporal change, with distant stage increasing and regional stage decreasing between 2006 and 2018. Demographic factors, including age at diagnosis, sex, race, SES, and marital status, were significantly associated with the overall survival of all BTCs in a similar manner, except for the opposite association of sex with EBD cancer, in which male patients had better overall survival. The significant associations found for overall survival became weaker for cancer-specific survival.
We observed that the overall and cancer-specific survival of BTC patients significantly improved over time, across all types and all stages (Table 3), after adjustment for demographic factors. A recent study reported similar findings for cholangiocarcinoma4. The improved BTC survival could be attributed to improved surgery, better adjuvant chemotherapy and radiotherapy treatment after surgery, and advanced immunotherapy 12–16 during recent years. Recent advances in imaging technologies continue to improve the sensitivity to detect early BTCs17,18, thus, helping early diagnosis and treatment and improving BTC survival. As shown in Table 3, the improvement of BTC survival across all types and all stages provided evidence to verify this hypothesis. It is worth noting that higher surgical accessibility for ampullary and gallbladder cancer patients could be a contributing factor to their higher survival rates than IBD and EBD cancer patients (as shown in Table 1). In addition, we observed that the improved cancer-specific survival was most significant during the 2015–2018 period, which may reflect, in part, improved coverage and access to health care due to the Medicaid expansions facilitated by the Patient Protection and Affordable Care Act established in 2014. A study19 using the SEER data found that the 2014 Medicaid expansions were associated with an increase in cancer diagnosis, particularly at the early stage, thus contributing to improving cancer detection and survival.
As expected, BTC patients with more advanced stages have lower overall and cancer-specific survival. However, it is surprising to observe the increase of distant BTCs over time, which have the worst overall survival, since BTC patients’ survival has generally improved. Although the reasons for increased distant BTCs and decreased regional BTCs over time are not elucidated, more regional BTCs could be diagnosed as distant BTC due to improved imaging technologies. A stage migration towards more advanced and more aggressive stages over time was also observed in prostate cancer, which may be related to active surveillance and improved imaging technologies for diagnosis 20,21
We observed that being old, male, or having the lowest SES are more likely to be diagnosed at localized stages, which was unexpected. Diagnosis of cancer at older ages is often complicated by comorbidities and frailty, and screening is more cautious among older people. As a result, cancers in old age groups are often more advanced in other cancers22,23. Men and people with low SES are usually less likely to seek health care 24,25. Thus, they should be more likely to be diagnosed at later stages. Future studies are warranted to investigate the BTC stage-related factors.
It’s not surprising that older BTC patients have poorer overall and cancer-specific survival. Previous studies showed that old BTC patients are more subject to comorbidities and less likely to receive survival benefit surgery and adjuvant therapy (chemotherapy / chemoradiotherapy) compared to the younger patients 26,27. It’s worth pointing out that poorer survival in older BTC patients can’t be explained by the later stage of the disease since older BTC patients were less likely to be at distant or regional stage than localized stage, as shown in Table 2.
In general, the survival of female cancer patients is better than male patients due to behavioral and environmental factors as well as biological differences28. Recent studies4,5 using the SEER data also showed that female cholangiocarcinoma patients had better survival than male cholangiocarcinoma patients. However, these studies failed to analyze the survival by BTC types. In this study, we showed that female patients of IBD, gallbladder, and ampullary cancer had better overall and cancer-specific survival, but the opposite was true for EBD, with which the male patients had better survival. The biological mechanism for the sex difference of survival of different BTCs remains to be identified.
Racial/ethnic disparities in cancer survival in the United States and The association of cancer survival with SES are well documented24,29–31. Previous studies consistently reported that NHB and people with low SES had higher cancer mortality, and NHB and low SES cancer patients had poorer survival than NHW and those with high SES. In this study, we also observed that NHB and low SES patients had poorer survival. Socioeconomic inequalities in medical examinations and access to medical care may contribute to these differences in cancer mortality and survival.
Marital status has been established as an important social factor associated with mortality and has been found to be associated with better survival in some common cancers 32,33 A recent systematic review of the literature showed that being married is associated with improved overall and cancer-specific survival 34. Our findings are consistent with previous studies that married patients consistently had better survival across all BTC types. The survival benefit of being married could be attributed to social and financial support provided by a partner.
Compared with the slight improvement of cancer-specific survival of BTC patients, the improvement of overall survival was more evident, which could be explained by the steady improvement in survival of other leading causes of death, such as heart disease35, chronic lower respiratory disease36, and stroke37.
Our study shares the limitations of all similar studies based on the SEER database and relying on retrospective data. Although we analyzed the association of demographic factors with BTC stages and observed a temporal change with distant stage increasing and regional stage decreasing between 2006 and 2018, future studies are warranted to investigate specific reasons for these temporal trends. In addition, our study did not include treatment, lifestyle factors, and comorbidities, which have a big impact on BTC survival. However, those factors should be considered as mediators instead of confounders of the demographic factors analyzed in the study according to the temporal ordering of causal structure, thus, not affecting the total effects of the demographic factors on the BTC survival.
In conclusion, this study found that demographic factors, including age, sex, race, SES, and marital status, were significantly associated with overall survival and less evidently with cancer-specific survival of BTC patients. The survival of BTC patients significantly improved over time, across all types and all stages, after adjustment for demographic factors. In addition, this study found that distant and regional BTC significantly increased and decreased respectively over time. The reasons for the temporal changes of BTC stages warrant future investigations.
Acknowledgements
This work was supported in part by a research grant (U01 CA262678) from the National Institutes of Health, United States. W. Zheng (Principal Investigator) received this grant.
Footnotes
Conflicts of interest: The authors disclose no conflicts.
References
- 1.Tariq NUA, McNamara MG, Valle JW. Biliary tract cancers: current knowledge, clinical candidates and future challenges. Cancer Manag Res. 2019;11:2623–2642. doi: 10.2147/CMAR.S157092 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Randi G, Malvezzi M, Levi F, Ferlay J, Negri E, Franceschi S, et al. Epidemiology of biliary tract cancers: an update. Ann Oncol Off J Eur Soc Med Oncol. 2009;20(1):146–159. doi: 10.1093/annonc/mdn533 [DOI] [PubMed] [Google Scholar]
- 3.Dwivedi AND, Jain S, Dixit R. Gall bladder carcinoma: Aggressive malignancy with protean loco-regional and distant spread. World J Clin Cases. 2015;3(3):231–244. doi: 10.12998/wjcc.v3.i3.231 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Mukkamalla SKR, Naseri HM, Kim BM, Katz SC, Armenio VA. Trends in Incidence and Factors Affecting Survival of Patients With Cholangiocarcinoma in the United States. J Natl Compr Cancer Netw JNCCN. 2018;16(4):370–376. doi: 10.6004/jnccn.2017.7056 [DOI] [PubMed] [Google Scholar]
- 5.Javle M, Lee S, Azad NS, Borad MJ, Kate Kelley R, Sivaraman S, et al. Temporal Changes in Cholangiocarcinoma Incidence and Mortality in the United States from 2001 to 2017. The oncologist. 2022;27(10):874–883. doi: 10.1093/oncolo/oyac150 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Raza SA, da Costa WL, Thrift AP. Increasing Incidence of Gallbladder Cancer among Non-Hispanic Blacks in the United States: A Birth Cohort Phenomenon. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2022;31(7):1410–1417. doi: 10.1158/1055-9965.EPI-21-1452 [DOI] [PubMed] [Google Scholar]
- 7.Low SK, Giannis D, Thuong ND, Nam NH, Alshareef A, Koulas I, et al. Trends in Primary Gallbladder Cancer Incidence and Incidence-based Mortality in the United States, 1973 to 2015. Am J Clin Oncol. 2022;45(7):306–315. doi: 10.1097/COC.0000000000000918 [DOI] [PubMed] [Google Scholar]
- 8.Yost K, Perkins C, Cohen R, Morris C, Wright W. Socioeconomic status and breast cancer incidence in California for different race/ethnic groups. Cancer Causes Control CCC. 2001;12(8):703–711. doi: 10.1023/a:1011240019516 [DOI] [PubMed] [Google Scholar]
- 9.Howlader N, Ries LAG, Mariotto AB, Reichman ME, Ruhl J, Cronin KA. Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst. 2010;102(20):1584–1598. doi: 10.1093/jnci/djq366 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK. Estimating average annual per cent change in trend analysis. Stat Med. 2009;28(29):3670–3682. doi: 10.1002/sim.3733 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kleinbaum DG, Klein M. Survival Analysis, A Self-Learning Text, (pp 201–227). Third edition. Springer; 2012. [Google Scholar]
- 12.Oneda E, Abu Hilal M, Zaniboni A. Biliary Tract Cancer: Current Medical Treatment Strategies. Cancers. 2020;12(5). doi: 10.3390/cancers12051237 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Vogel A, Saborowski A. Current and Future Systemic Therapies in Biliary Tract Cancer. Visc Med. 2021;37(1):32–38. doi: 10.1159/000513969 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Rizzo A, Ricci AD, Brandi G. Recent advances of immunotherapy for biliary tract cancer. Expert Rev Gastroenterol Hepatol. 2021;15(5):527–536. doi: 10.1080/17474124.2021.1853527 [DOI] [PubMed] [Google Scholar]
- 15.Valle JW, Kelley RK, Nervi B, Oh DY, Zhu AX. Biliary tract cancer. Lancet Lond Engl. 2021;397(10272):428–444. doi: 10.1016/S0140-6736(21)00153-7 [DOI] [PubMed] [Google Scholar]
- 16.Matsukuma S, Tokumitsu Y, Shindo Y, Matsui H, Nagano H. Essential updates to the surgical treatment of biliary tract cancer. Ann Gastroenterol Surg. 2019;3(4):378–389. doi: 10.1002/ags3.12266 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Hennedige TP, Neo WT, Venkatesh SK. Imaging of malignancies of the biliary tract- an update. Cancer Imaging Off Publ Int Cancer Imaging Soc. 2014;14(1):14. doi: 10.1186/1470-7330-14-14 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bridgewater JA, Goodman KA, Kalyan A, Mulcahy MF. Biliary Tract Cancer: Epidemiology, Radiotherapy, and Molecular Profiling. Am Soc Clin Oncol Educ Book Am Soc Clin Oncol Annu Meet. 2016;35:e194–203. doi: 10.1200/EDBK_160831 [DOI] [PubMed] [Google Scholar]
- 19.Soni A, Simon K, Cawley J, Sabik L. Effect of Medicaid Expansions of 2014 on Overall and Early-Stage Cancer Diagnoses. Am J Public Health. 2018;108(2):216–218. doi: 10.2105/AJPH.2017.304166 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Desai MM, Cacciamani GE, Gill K, Zhang J, Liu L, Abreu A, et al. Trends in Incidence of Metastatic Prostate Cancer in the US. JAMA Netw Open. 2022;5(3):e222246. doi: 10.1001/jamanetworkopen.2022.2246 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Herlemann A, Washington SL 3rd, Cooperberg MR. Health Care Delivery for Metastatic Hormone-sensitive Prostate Cancer Across the Globe. Eur Urol Focus. 2019;5(2):155–158. doi: 10.1016/j.euf.2018.12.003 [DOI] [PubMed] [Google Scholar]
- 22.Van Herck Y, Feyaerts A, Alibhai S, Papamichael D, Decoster L, Lambrechts Y, et al. Is cancer biology different in older patients? Lancet Healthy Longev. 2021;2(10):e663–e677. doi: 10.1016/S2666-7568(21)00179-3 [DOI] [PubMed] [Google Scholar]
- 23.Williams GR, Mackenzie A, Magnuson A, Olin R, Chapman A, Mohile S, et al. Comorbidity in older adults with cancer. J Geriatr Oncol. 2016;7(4):249–257. doi: 10.1016/j.jgo.2015.12.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Ellis L, Canchola AJ, Spiegel D, Ladabaum U, Haile R, Gomez SL. Racial and Ethnic Disparities in Cancer Survival: The Contribution of Tumor, Sociodemographic, Institutional, and Neighborhood Characteristics. J Clin Oncol Off J Am Soc Clin Oncol. 2018;36(1):25–33. doi: 10.1200/JCO.2017.74.2049 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Bertakis KD, Azari R, Helms LJ, Callahan EJ, Robbins JA. Gender differences in the utilization of health care services. J Fam Pract. 2000;49(2):147–152. [PubMed] [Google Scholar]
- 26.Lee BS, Hwang JH, Lee SH, Jang SE, Ahn DW, Hwang DW, et al. Older adults with biliary tract cancer: treatment and prognosis. J Am Geriatr Soc. 2012;60(10):1862–1871. doi: 10.1111/j.1532-5415.2012.04163.x [DOI] [PubMed] [Google Scholar]
- 27.Horgan A, Knox J, Aneja P, Le L, McKeever E, McNamara M. Patterns of care and treatment outcomes in older patients with biliary tract cancer. Oncotarget. 2015;6(42):44995–45004. doi: 10.18632/oncotarget.5707 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Dong M, Cioffi G, Wang J, Waite KA, Ostrom QT, Kruchko C, et al. Sex Differences in Cancer Incidence and Survival: A Pan-Cancer Analysis. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2020;29(7):1389–1397. doi: 10.1158/1055-9965.EPI-20-0036 [DOI] [PubMed] [Google Scholar]
- 29.Singh GK, Jemal A. Socioeconomic and Racial/Ethnic Disparities in Cancer Mortality, Incidence, and Survival in the United States, 1950–2014: Over Six Decades of Changing Patterns and Widening Inequalities. J Environ Public Health. 2017;2017:2819372. doi: 10.1155/2017/2819372 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Kogevinas M, Porta M. Socioeconomic differences in cancer survival: a review of the evidence. IARC Sci Publ. 1997;(138):177–206. [PubMed] [Google Scholar]
- 31.Kish JK, Yu M, Percy-Laurry A, Altekruse SF. Racial and ethnic disparities in cancer survival by neighborhood socioeconomic status in Surveillance, Epidemiology, and End Results (SEER) Registries. J Natl Cancer Inst Monogr. 2014;2014(49):236–243. doi: 10.1093/jncimonographs/lgu020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Huang TB, Zhou GC, Dong CP, Wang LP, Luan Y, Ye JT, et al. Marital status independently predicts prostate cancer survival in men who underwent radical prostatectomy: An analysis of 95,846 individuals. Oncol Lett. 2018;15(4):4737–4744. doi: 10.3892/ol.2018.7964 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Martínez ME, Unkart JT, Tao L, Kroenke CH, Schwab R, Komenaka I, et al. Prognostic significance of marital status in breast cancer survival: A population-based study. PloS One. 2017;12(5):e0175515. doi: 10.1371/journal.pone.0175515 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Krajc K, Miroševič Š, Sajovic J, Klemenc Ketiš Z, Spiegel D, Drevenšek G, et al. Marital status and survival in cancer patients: A systematic review and meta-analysis. Cancer Med. 2023;12(2):1685–1708. doi: 10.1002/cam4.5003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Jones NR, Roalfe AK, Adoki I, Hobbs FDR, Taylor CJ. Survival of patients with chronic heart failure in the community: a systematic review and meta-analysis. Eur J Heart Fail. 2019;21(11):1306–1325. doi: 10.1002/ejhf.1594 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Zarrabian B, Mirsaeidi M. A Trend Analysis of Chronic Obstructive Pulmonary Disease Mortality in the United States by Race and Sex. Ann Am Thorac Soc. 2021;18(7):1138–1146. doi: 10.1513/AnnalsATS.202007-822OC [DOI] [PubMed] [Google Scholar]
- 37.Ananth CV, Brandt JS, Keyes KM, Graham HL, Kostis JB, Kostis WJ. Epidemiology and trends in stroke mortality in the USA, 1975–2019. Int J Epidemiol. 2023;52(3):858–866. doi: 10.1093/ije/dyac210 [DOI] [PMC free article] [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 in this study are publicly available which can be accessed at https://www.cdc.gov/cancer/uscs/public-use/obtain-data.htm.