Chemotherapy effectiveness in trial-underrepresented groups with early breast cancer: A retrospective cohort study
Autoři:
Ewan Gray aff001; Joachim Marti aff002; Jeremy C. Wyatt aff003; David H. Brewster aff004; Peter S. Hall aff004;
Působiště autorů:
University of Manchester, Manchester, United Kingdom
aff001; Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
aff002; University of Southampton, Southhampton, United Kingdom
aff003; University of Edinburgh, Edinburgh, United Kingdom
aff004
Vyšlo v časopise:
Chemotherapy effectiveness in trial-underrepresented groups with early breast cancer: A retrospective cohort study. PLoS Med 16(12): e32767. doi:10.1371/journal.pmed.1003006
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pmed.1003006
Souhrn
Background
Adjuvant chemotherapy in early stage breast cancer has been shown to reduce mortality in a large meta-analysis of over 100 randomised trials. However, these trials largely excluded patients aged 70 years and over or with higher levels of comorbidity. There is therefore uncertainty about whether the effectiveness of adjuvant chemotherapy generalises to these groups, hindering patient and clinician decision-making. This study utilises administrative healthcare data—real world data (RWD)—and econometric methods for causal analysis to estimate treatment effectiveness in these trial-underrepresented groups.
Methods and findings
Women with early breast cancer aged 70 years and over and those under 70 years with a high level of comorbidity were identified and their records extracted from Scottish Cancer Registry (2001–2015) data linked to other routine health records. A high level of comorbidity was defined as scoring 1 or more on the Charlson comorbidity index, being in the top decile of inpatient stays, and/or having 5 or more visits to specific outpatient clinics, all within the 5 years preceding breast cancer diagnosis. Propensity score matching (PSM) and instrumental variable (IV) analysis, previously identified as feasible and valid in this setting, were used in conjunction with Cox regression to estimate hazard ratios for death from breast cancer and death from all causes. The analysis adjusts for age, clinical prognostic factors, and socioeconomic deprivation; the IV method may also adjust for unmeasured confounding factors. Cohorts of 9,653 and 7,965 were identified for women aged 70 years and over and those with high comorbidity, respectively. In the ≥70/high comorbidity cohorts, median follow-up was 5.17/6.53 years and there were 1,935/740 deaths from breast cancer. For women aged 70 years and over, the PSM-estimated HR was 0.73 (95% CI 0.64–0.95), while for women with high comorbidity it was 0.67 (95% CI 0.51–0.86). This translates to a mean predicted benefit in terms of overall survival at 10 years of approximately3% (percentage points) and 4%, respectively. A limitation of this analysis is that use of observational data means uncertainty remains both from sampling uncertainty and from potential bias from residual confounding.
Conclusions
The results of this study, as RWD, should be interpreted with caution and in the context of existing and emerging randomised data. The relative effectiveness of adjuvant chemotherapy in reducing mortality in patients with early stage breast cancer appears to be generalisable to the selected trial-underrepresented groups.
Klíčová slova:
Adjuvant chemotherapy – Breast cancer – Cancer detection and diagnosis – Cancer chemotherapy – Death rates – Chemotherapy – Inpatients
Zdroje
1. Early Breast Cancer Trialists’ Collaborative Group. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365(9472):1687–717. doi: 10.1016/S0140-6736(05)66544-0 15894097
2. Early Breast Cancer Trialists’ Collaborative Group. Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100 000 women in 123 randomised trials. Lancet. 2012;379(9814):432–44. doi: 10.1016/S0140-6736(11)61625-5 22152853
3. Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?” Lancet. 2005;365(9453):82–93. doi: 10.1016/S0140-6736(04)17670-8 15639683
4. Zwarenstein M, Treweek S, Gagnier JJ, Altman DG, Tunis S, Haynes B, et al. Improving the reporting of pragmatic trials: an extension of the CONSORT statement. BMJ. 2008;337:a2390. doi: 10.1136/bmj.a2390 19001484
5. Cameron D, Ballinger R, Makris A, Gosney M, Kilburn LS, Mansi J, et al. Adjuvant chemotherapy in older women (ACTION) study—what did we learn from the pilot phase? Br J Cancer. 2011;105(9):1260–6. doi: 10.1038/bjc.2011.377 21989185
6. International Breast Cancer Study Group. Liposomal doxorubicin compared with observation or cyclophosphamide and methotrexate in treating older women who have undergone surgery for breast cancer (CASA). ClinicalTrials.gov NCT00296010. Bethesda (MD): National Library of Medicine; 2015 [cited 2019 Mar 1]. Available from: https://clinicaltrials.gov/ct2/show/NCT00296010.
7. Booth CM, Karim S, Mackillop WJ. Real-world data: towards achieving the achievable in cancer care. Nat Rev Clin Oncol. 2019;16:312–25. doi: 10.1038/s41571-019-0167-7 30700859
8. Gray E, Marti J, Wyatt JC, Brewster DH, Piaget-Rossel R, Hall PS. Real-world evidence was feasible for estimating effectiveness of chemotherapy in breast cancer; a cohort study. J Clin Epidemiol. 2019;109:125–32. doi: 10.1016/j.jclinepi.2019.01.006 30711490
9. Candido Dos Reis FJ, Wishart GC, Dicks EM, Greenberg D, Rashbass J, Schmidt MK, et al. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation. Breast Cancer Res. 2017;19(1):58. doi: 10.1186/s13058-017-0852-3 28532503
10. Gray E, Marti J, Brewster DH, Wyatt JC, Hall PS. Independent validation of the PREDICT breast cancer prognosis prediction tool in 45,789 patients using Scottish Cancer Registry data. Br J Cancer. 2018;119(7):808–14. doi: 10.1038/s41416-018-0256-x 30220705
11. Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47(11):1245–51. doi: 10.1016/0895-4356(94)90129-5 7722560
12. Terza J V, Basu A, Rathouz PJ. Two-stage residual inclusion estimation: addressing endogeneity in health econometric modeling. J Health Econ. 2008;27(3):531–43. doi: 10.1016/j.jhealeco.2007.09.009 18192044
13. Ravdin PM, Siminoff LA, Davis GJ, Mercer MB, Hewlett J, Gerson N, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol. 2001;19(4):980–91. doi: 10.1200/JCO.2001.19.4.980 11181660
14. Down SK, Lucas O, Benson JR, Wishart GC. Effect of PREDICT on chemotherapy/trastuzumab recommendations in HER2-positive patients with early-stage breast cancer. Oncol Lett. 2014;8(6):2757–61. doi: 10.3892/ol.2014.2589 25364461
15. Giordano SH, Duan Z, Kuo YF, Hortobagyi GN, Goodwin JS. Use and outcomes of adjuvant chemotherapy in older women with breast cancer. J Clin Oncol. 2006;24(18):2750–6. doi: 10.1200/JCO.2005.02.3028 16782915
16. Donovan J, Marshall A, Poole C, Rooshenas L, Francis A, Higgins H, et al. OPTIMA: a prospective randomised trial to validate the predictive utility and cost-effectiveness of gene expression test-directed chemotherapy decisions. Eur J Surg Oncol. 2016;42(11):S229.
17. Badve SS, Olson JA, Pritchard KI, Dees EC, Abrams J, Paik S, et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med. 2018;379(2):111–21. doi: 10.1056/NEJMoa1804710 29860917
18. European Organisation for Research and Treatment of Cancer. Adjuvant palbociclib in elderly patients with breast cancer (Appalaches). ClinicalTrials.gov NCT03609047. Bethesda (MD): National Library of Medicine; 2018 [cited 2019 Dec 6]. Available from: https://clinicaltrials.gov/ct2/show/NCT03609047.
19. Helsinki University Central Hospital. Adjuvant trastuzumab, pertuzumab plus docetaxel in the treatment of early HER2-positive breast cancer (BOLD-1). ClinicalTrials.gov NCT02625441. Bethesda (MD): National Library of Medicine; 20182018 [cited 2019 Dec 6]. Available from: https://clinicaltrials.gov/ct2/show/NCT02625441.
20. Agniel D, Kohane IS, Weber GM. Biases in electronic health record data due to processes within the healthcare system: retrospective observational study. BMJ. 2018;361:k1479. doi: 10.1136/bmj.k1479 29712648
21. Kaizar E. Incorporating both randomized and observational data into a single analysis. Annu Rev Stat Appl. 2015;2:49–72.
Štítky
Interní lékařstvíČlánek vyšel v časopise
PLOS Medicine
2019 Číslo 12
- Jak postupovat při výběru betablokátoru − doporučení z kardiologické praxe
- Berberin: přírodní hypolipidemikum se slibnými výsledky
- Příznivý vliv Armolipidu Plus na hladinu cholesterolu a zánětlivé parametry u pacientů s chronickým subklinickým zánětem
- Léčba bolesti u seniorů
- Co lze v terapii hypertenze očekávat od přidání perindoprilu k bisoprololu?
Nejčtenější v tomto čísle
- Ambient particulate matter pollution and adult hospital admissions for pneumonia in urban China: A national time series analysis for 2014 through 2017
- Association between gestational weight gain and severe adverse birth outcomes in Washington State, US: A population-based retrospective cohort study, 2004–2013
- Adherence to the 2017 French dietary guidelines and adult weight gain: A cohort study
- Acute kidney injury and adverse renal events in patients receiving SGLT2-inhibitors: A systematic review and meta-analysis