1 Teras, L. R. et al. 2016 US lymphoid malignancy statistics by World Health Organization subtypes. CA: A Cancer Journal for Clinicians66, 443-459, doi:10.3322/caac.21357 (2016).
2 Li, S., Young, K. H. & Medeiros, L. J. Diffuse large B-cell lymphoma. Pathology50, 74-87, doi:10.1016/j.pathol.2017.09.006 (2018).
3 Bray, F. et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin68, 394-424, doi:10.3322/caac.21492 (2018).
4 Miranda-Filho, A. et al. Global patterns and trends in the incidence of non-Hodgkin lymphoma. Cancer Causes Control30, 489-499, doi:10.1007/s10552-019-01155-5 (2019).
5 Flowers, C. R., Sinha, R. & Vose, J. M. Improving outcomes for patients with diffuse large B-cell lymphoma. CA Cancer J Clin60, 393-408, doi:10.3322/caac.20087 (2010).
6 National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology: Non-Hodgkin's Lymphoma (version 3.2020), <https://www.nccn.org/professionals/physician_gls/pdf/b-cell.pdf> (
7 Flowers, C. R. et al. Disparities in the early adoption of chemoimmunotherapy for diffuse large B-cell lymphoma in the United States. Cancer Epidemiol Biomarkers Prev21, 1520-1530, doi:10.1158/1055-9965.Epi-12-0466 (2012).
8 Boslooper, K. et al. No outcome disparities in patients with diffuse large B-cell lymphoma and a low socioeconomic status. Cancer Epidemiol48, 110-116, doi:10.1016/j.canep.2017.04.009 (2017).
9 Doyle, Y. & Bull, A. Role of private sector in United Kingdom healthcare system. BMJ321, 563-565, doi:10.1136/bmj.321.7260.563 (2000).
10 Pocock, N. S. & Phua, K. H. Medical tourism and policy implications for health systems: a conceptual framework from a comparative study of Thailand, Singapore and Malaysia. Global Health7, 12, doi:10.1186/1744-8603-7-12 (2011).
11 Higgins, J. P., Thompson, S. G., Deeks, J. J. & Altman, D. G. Measuring inconsistency in meta-analyses. BMJ327, 557-560, doi:10.1136/bmj.327.7414.557 (2003).
12 Wong, O. F., Ho, P. L. & Lam, S. K. Retrospective review of clinical presentations, microbiology, and outcomes of patients with psoas abscess. Hong Kong Med J19, 416-423, doi:10.12809/hkmj133793 (2013).
13 Chan, E. W. et al. Prevention of Dabigatran-Related Gastrointestinal Bleeding With Gastroprotective Agents: A Population-Based Study. Gastroenterology149, 586-595.e583, doi:10.1053/j.gastro.2015.05.002 (2015).
14 Chiu, S. S., Lau, Y. L., Chan, K. H., Wong, W. H. & Peiris, J. S. Influenza-related hospitalizations among children in Hong Kong. N Engl J Med347, 2097-2103, doi:10.1056/NEJMoa020546 (2002).
15 Cheung, K. S., Seto, W. K., Fung, J., Lai, C. L. & Yuen, M. F. Epidemiology and Natural History of Primary Biliary Cholangitis in the Chinese: A Territory-Based Study in Hong Kong between 2000 and 2015. Clinical and translational gastroenterology8, e116, doi:10.1038/ctg.2017.43 (2017).
16 Schulz, K. F., Altman, D. G. & Moher, D. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMJ340, doi:10.1136/bmj.c332 (2010).
17 A predictive model for aggressive non-Hodgkin's lymphoma. N Engl J Med329, 987-994, doi:10.1056/nejm199309303291402 (1993).
18 Social Welfare Department, The Government of the Hong Kong Special Administrative Region. Comprehensive Social Security Assistance (CSSA) Scheme, <https://www.swd.gov.hk/en/index/site_pubsvc/page_socsecu/sub_comprehens/> (2020).
19 Brusselaers, N. & Lagergren, J. The Charlson Comorbidity Index in Registry-based Research. Methods of information in medicine56, 401-406, doi:10.3414/me17-01-0051 (2017).
20 Armitage, J. N. & van der Meulen, J. H. Identifying co-morbidity in surgical patients using administrative data with the Royal College of Surgeons Charlson Score. Br J Surg97, 772-781, doi:10.1002/bjs.6930 (2010).
21 Agresti, A. Foundations of Linear and Generalized Linear Models. (Wiley, 2015).
22 Robins, J. M., Hernan, M. A. & Brumback, B. Marginal structural models and causal inference in epidemiology. Epidemiology11, 550-560 (2000).
23 Williamson, T. & Ravani, P. Marginal structural models in clinical research: when and how to use them? Nephrol Dial Transplant32, ii84-ii90, doi:10.1093/ndt/gfw341 (2017).
24 Kawano, M. et al. Autocrine generation and requirement of BSF-2/IL-6 for human multiple myelomas. Nature332, 83-85, doi:10.1038/332083a0 (1988).
25 Tao, L., Foran, J. M., Clarke, C. A., Gomez, S. L. & Keegan, T. H. Socioeconomic disparities in mortality after diffuse large B-cell lymphoma in the modern treatment era. Blood123, 3553-3562, doi:10.1182/blood-2013-07-517110 (2014).
26 Wang, M., Burau, K. D., Fang, S., Wang, H. & Du, X. L. Ethnic variations in diagnosis, treatment, socioeconomic status, and survival in a large population-based cohort of elderly patients with non-Hodgkin lymphoma. Cancer113, 3231-3241, doi:10.1002/cncr.23914 (2008).
27 Han, X. et al. Insurance status is related to diffuse large B-cell lymphoma survival. Cancer120, 1220-1227, doi:10.1002/cncr.28549 (2014).
28 Smith, A. et al. Impact of age and socioeconomic status on treatment and survival from aggressive lymphoma: a UK population-based study of diffuse large B-cell lymphoma. Cancer Epidemiol39, 1103-1112, doi:10.1016/j.canep.2015.08.015 (2015).
29 Frederiksen, B. L., Brown Pde, N., Dalton, S. O., Steding-Jessen, M. & Osler, M. Socioeconomic inequalities in prognostic markers of non-Hodgkin lymphoma: analysis of a national clinical database. European journal of cancer (Oxford, England : 1990)47, 910-917, doi:10.1016/j.ejca.2010.11.014 (2011).
30 Frederiksen, B. L., Dalton, S. O., Osler, M., Steding-Jessen, M. & de Nully Brown, P. Socioeconomic position, treatment, and survival of non-Hodgkin lymphoma in Denmark--a nationwide study. Br J Cancer106, 988-995, doi:10.1038/bjc.2012.3 (2012).
31 Booth, C. M., Li, G., Zhang-Salomons, J. & Mackillop, W. J. The impact of socioeconomic status on stage of cancer at diagnosis and survival: a population-based study in Ontario, Canada. Cancer116, 4160-4167, doi:10.1002/cncr.25427 (2010).
32 Lee, B. et al. Effect of place of residence and treatment on survival outcomes in patients with diffuse large B-cell lymphoma in British Columbia. The oncologist19, 283-290, doi:10.1634/theoncologist.2013-0343 (2014).
33 Orsini, M., Trétarre, B., Daurès, J.-P. & Bessaoud, F. Individual socioeconomic status and breast cancer diagnostic stages: a French case–control study. European Journal of Public Health26, 445-450, doi:10.1093/eurpub/ckv233 (2016).
34 Pickett, K. E. & Pearl, M. Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J Epidemiol Community Health55, 111-122, doi:10.1136/jech.55.2.111 (2001).
35 Hussein, M., Diez Roux, A. V. & Field, R. I. Neighborhood Socioeconomic Status and Primary Health Care: Usual Points of Access and Temporal Trends in a Major US Urban Area. J Urban Health93, 1027-1045, doi:10.1007/s11524-016-0085-2 (2016).
36 Louwman, W. J. et al. A 50% higher prevalence of life-shortening chronic conditions among cancer patients with low socioeconomic status. Br J Cancer103, 1742-1748, doi:10.1038/sj.bjc.6605949 (2010).
37 Lin, A. W.-C. & Wong, K.-H. Surveillance and response of hepatitis B virus in Hong Kong Special Administrative Region, 1988-2014. Western Pac Surveill Response J7, 24-28, doi:10.5365/WPSAR.2015.6.3.003 (2016).
38 Bo, W., Ghulam, M. & Kosh, A. Reactivation of hepatitis B virus infection in patients with hematologic disorders. Haematologica104, 435-443, doi:10.3324/haematol.2018.210252 (2019).
39 Legislative Council Panel on Health Services Update on Hospital Authority Drug Formulary, <https://www.legco.gov.hk/yr08-09/english/panels/hs/papers/hs0608cb2-1740-4-e.pdf> (
40 Cronin, D. P. et al. Patterns of care in a population-based random sample of patients diagnosed with non-Hodgkin's lymphoma. Hematol Oncol23, 73-81, doi:10.1002/hon.747 (2005).
41 Edwards, B. K. et al. Annual report to the nation on the status of cancer, 1975-2002, featuring population-based trends in cancer treatment. J Natl Cancer Inst97, 1407-1427, doi:10.1093/jnci/dji289 (2005).
42 Shah, B. K., Bista, A. & Shafii, B. Disparities in receipt of radiotherapy and survival by age, sex and ethnicity among patients with stage I diffuse large B-cell lymphoma. Leuk Lymphoma56, 983-986, doi:10.3109/10428194.2014.940583 (2015).
43 Bista, A., Sharma, S. & Shah, B. K. Disparities in Receipt of Radiotherapy and Survival by Age, Sex, and Ethnicity among Patient with Stage I Follicular Lymphoma. Front Oncol6, 101, doi:10.3389/fonc.2016.00101 (2016).
44 Olszewski, A. J., Shrestha, R. & Castillo, J. J. Treatment selection and outcomes in early-stage classical Hodgkin lymphoma: analysis of the National Cancer Data Base. J Clin Oncol33, 625-633, doi:10.1200/jco.2014.58.7543 (2015).
45 Cronin-Fenton, D. P., Sharp, L., Deady, S. & Comber, H. Treatment and survival for non-Hodgkin’s lymphoma: Influence of histological subtype, age, and other factors in a population-based study (1999–2001). European Journal of Cancer42, 2786-2793, doi:https://doi.org/10.1016/j.ejca.2006.04.018 (2006).
46 Pal, S. K. & Hurria, A. Impact of age, sex, and comorbidity on cancer therapy and disease progression. J Clin Oncol28, 4086-4093, doi:10.1200/jco.2009.27.0579 (2010).
47 Yancik, R. et al. Report of the national institute on aging task force on comorbidity. J Gerontol A Biol Sci Med Sci62, 275-280, doi:10.1093/gerona/62.3.275 (2007).
48 Lyman, G. H., Dale, D. C., Friedberg, J., Crawford, J. & Fisher, R. I. Incidence and predictors of low chemotherapy dose-intensity in aggressive non-Hodgkin's lymphoma: a nationwide study. J Clin Oncol22, 4302-4311, doi:10.1200/jco.2004.03.213 (2004).
49 Yellen, S. B., Cella, D. F. & Leslie, W. T. Age and clinical decision making in oncology patients. J Natl Cancer Inst86, 1766-1770, doi:10.1093/jnci/86.23.1766 (1994).
50 Glover, R. et al. Patterns of social support among lymphoma patients considering stem cell transplantation. Soc Work Health Care50, 815-827, doi:10.1080/00981389.2011.595889 (2011).
51 Goldsbury, D. et al. Identifying incident colorectal and lung cancer cases in health service utilisation databases in Australia: a validation study. BMC Med Inform Decis Mak17, 23, doi:10.1186/s12911-017-0417-5 (2017).
52 Polubriaginof, F. C. G. et al. Challenges with quality of race and ethnicity data in observational databases. J Am Med Inform Assoc26, 730-736, doi:10.1093/jamia/ocz113 (2019).
53 Bosch, X. et al. Time to diagnosis and associated costs of an outpatient vs inpatient setting in the diagnosis of lymphoma: a retrospective study of a large cohort of major lymphoma subtypes in Spain. BMC Cancer18, 276, doi:10.1186/s12885-018-4187-y (2018).