Mistakes to Avoid for Accurate and Transparent Reporting of Survival Analysis in Imaging Research

참고문헌

1. Lee G, Park H, Bak SH, Lee HY. Radiomics in lung cancer from basic to advanced: current status and future directions. Korean J Radiol 2020;21:159-171 
2. Lee SH, Park H, Ko ES. Radiomics in breast imaging from techniques to clinical applications: a review. Korean J Radiol 2020;21:779-792 
3. Park HJ, Park B, Lee SS. Radiomics and deep learning: hepatic applications. Korean J Radiol 2020;21:387-401 
4. Park JE, Kickingereder P, Kim HS. Radiomics and deep learning from research to clinical workflow: neuro-oncologic imaging. Korean J Radiol 2020;21:1126-1137 
5. Zhu X, Zhou X, Zhang Y, Sun X, Liu H, Zhang Y. Reporting and methodological quality of survival analysis in articles published in Chinese oncology journals. Medicine (Baltimore) 2017;96:e9204 
6. Chai-Adisaksopha C, Iorio A, Hillis C, Lim W, Crowther M. A systematic review of using and reporting survival analyses in acute lymphoblastic leukemia literature. BMC Hematol 2016;16:17 
7. Batson S, Greenall G, Hudson P. Review of the reporting of survival analyses within randomised controlled trials and the implications for meta-analysis. PLoS One 2016;11:e0154870 
8. Abraira V, Muriel A, Emparanza JI, Pijoan JI, Royuela A, Plana MN, et al. Reporting quality of survival analyses in medical journals still needs improvement. A minimal requirements proposal. J Clin Epidemiol 2013;66:1340-1346.e5 
9. Altman DG, De Stavola BL, Love SB, Stepniewska KA. Review of survival analyses published in cancer journals. Br J Cancer 1995;72:511-518 
10. Dey T, Mukherjee A, Chakraborty S. A practical overview and reporting strategies for statistical analysis of survival studies. Chest 2020;158:S39-S48 
11. Tolles J, Lewis RJ. Time-to-event analysis. JAMA 2016;315:1046-1047 
12. Therneau T, Crowson C, Atkinson E. Using time dependent covariates and time dependent coefficients in the cox model. Cran.r-project.org Web site. https://cran.r-project.org/web/packages/survival/vignettes/timedep.pdf. Published April 25, 2021. Accessed July 15, 2021 
13. Lee H, Nunan D. Immortal time bias. Catalogofbias.org Web site. https://catalogofbias.org/biases/immortal-time-bias/. Accessed July 15, 2021 
14. Park SY, Park JE, Kim H, Park SH. Review of statistical methods for evaluating the performance of survival or other time-to-event prediction models (from conventional to deep learning approaches). Korean J Radiol 2021;22:1697-1707 
15. CDC. Lesson 3, Section 2: morbidity frequency measures. CDC. gov Web site. https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section2.html. Accessed July 15, 2021 
16. FDA. Clinical trial endpoints for the approval of cancer drugs and biologics: guidance for industry. FDA.gov Web site. https://www.fda.gov/media/71195/download. Published December 2018. Accessed July 15, 2021 
17. Cohen R, Vernerey D, Bellera C, Meurisse A, Henriques J, Paoletti X, et al. Guidelines for time-to-event end-point definitions in adjuvant randomised trials for patients with localised colon cancer: results of the DATECAN initiative. Eur J Cancer 2020;130:63-71 
18. Bellera CA, Penel N, Ouali M, Bonvalot S, Casali PG, Nielsen OS, et al. Guidelines for time-to-event end point definitions in sarcomas and gastrointestinal stromal tumors (GIST) trials: results of the DATECAN initiative (Definition for the Assessment of Time-to-event Endpoints in CANcer trials). Ann Oncol 2015;26:865-872 
19. Gourgou-Bourgade S, Cameron D, Poortmans P, Asselain B, Azria D, Cardoso F, et al. Guidelines for time-to-event end point definitions in breast cancer trials: results of the DATECAN initiative (Definition for the Assessment of Time-to-event Endpoints in CANcer trials). Ann Oncol 2015;26:2505-2506 
20. Kramar A, Negrier S, Sylvester R, Joniau S, Mulders P, Powles T, et al. Guidelines for the definition of time-to-event end points in renal cell cancer clinical trials: results of the DATECAN project^†. Ann Oncol 2015;26:2392-2398 
21. Gourgou-Bourgade S, Cameron D, Poortmans P, Asselain B, Azria D, Cardoso F, et al. Guidelines for time-to-event end point definitions in breast cancer trials: results of the DATECAN initiative (Definition for the Assessment of Time-to-event Endpoints in CANcer trials)^†. Ann Oncol 2015;26:873-879 
22. Bonnetain F, Bonsing B, Conroy T, Dousseau A, Glimelius B, Haustermans K, et al. Guidelines for time-to-event end-point definitions in trials for pancreatic cancer. Results of the DATECAN initiative (Definition for the Assessment of Time-to-event End-points in CANcer trials). Eur J Cancer 2014;50:2983-2993 
23. Park C, Kim JH, Kim PH, Kim SY, Gwon DI, Chu HH, et al. Imaging predictors of survival in patients with single small hepatocellular carcinoma treated with Transarterial chemoembolization. Korean J Radiol 2021;22:213-224 
24. Hong EK, Choi SH, Shin DJ, Jo SW, Yoo RE, Kang KM, et al. Comparison of genetic profiles and prognosis of high-grade gliomas using quantitative and qualitative MRI features: a focus on G3 gliomas. Korean J Radiol 2021;22:233-242 
25. Chung H, Kim BY, Kim HS, Kim HO, Lee JM, Woo JS, et al. Long-term clinical effects of carotid intraplaque neovascularization in patients with coronary artery disease. Korean J Radiol 2020;21:900-907 
26. Park B, Park J, Lim JK, Shin KM, Lee J, Seo H, et al. Prognostic implication of volumetric quantitative ct analysis in patients with COVID-19: a multicenter study in Daegu, Korea. Korean J Radiol 2020;21:1256-1264 
27. Kim JW, Kim JH, Byun SS, Kang JM, Shin JH. Paclitaxel-coated balloon versus plain balloon angioplasty for dysfunctional autogenous radiocephalic arteriovenous fistulas: a prospective randomized controlled trial. Korean J Radiol 2020;21:1239-1247 
28. Seo J, Choi SI, Kim YK. Subclinical coronary atherosclerosis: implication of coronary computed tomography angiography findings among statin candidates according to the 2013 ACC/AHA Cholesterol Management Guidelines. Korean J Radiol 2019;20:1156-1166 
29. Yoon SH, Kim E, Jeon Y, Yi SY, Bae HJ, Jang IK, et al. Prognostic value of coronary CT angiography for predicting poor cardiac outcome in stroke patients without known cardiac disease or chest pain: the assessment of coronary artery disease in stroke patients study. Korean J Radiol 2020;21:1055-1064 
30. Lee SJ, Kim JH, Kim SY, Won HJ, Shin YM, Kim PN. Percutaneous radiofrequency ablation for metachronous hepatic metastases after curative resection of pancreatic adenocarcinoma. Korean J Radiol 2020;21:316-324 
31. Kim S, Kim DY, An C, Han K, Won JY, Kim GM, et al. Evaluation of early response to treatment of hepatocellular carcinoma with yttrium-90 radioembolization using quantitative computed tomography analysis. Korean J Radiol 2019;20:449-458 
32. Kang Y, Hong EK, Rhim JH, Yoo RE, Kang KM, Yun TJ, et al. Prognostic value of dynamic contrast-enhanced MRI-derived pharmacokinetic variables in glioblastoma patients: analysis of contrast-enhancing lesions and non-enhancing T2 high-signal intensity lesions. Korean J Radiol 2020;21:707-716 
33. Ahn Y, Koo HJ, Kang JW, Choi WJ, Kim DH, Song JM, et al. Prognostic implication of right ventricle parameters measured on preoperative cardiac MRI in patients with functional tricuspid regurgitation. Korean J Radiol 2021;22:1253-1265 
34. Kim MY, Park EA, Lee W, Lee SP. Cardiac magnetic resonance feature tracking in aortic stenosis: exploration of strain parameters and prognostic value in asymptomatic patients with preserved ejection fraction. Korean J Radiol 2020;21:268-279 
35. Ahn Y, Koo HJ, Lee S, Kim DH, Song JM, Kang DH, et al. Preoperative cardiac computed tomography characteristics associated with recurrent aortic regurgitation after aortic valve re-implantation. Korean J Radiol 2020;21:181-191 
36. Jo SW, Choi SH, Lee EJ, Yoo RE, Kang KM, Yun TJ, et al. Prognostic prediction based on dynamic contrast-enhanced MRI and dynamic susceptibility contrast-enhanced MRI parameters from non-enhancing, T2-high-signal-intensity lesions in patients with glioblastoma. Korean J Radiol 2021;22:1369-1378 
37. Kim SH, Song BI, Kim HW, Won KS, Son YG, Ryu SW. Prognostic value of restaging F-18 fluorodeoxyglucose positron emission tomography/computed tomography to predict 3-year post-recurrence survival in patients with recurrent gastric cancer after curative resection. Korean J Radiol 2020;21:829-837 
38. Kim EK, Lee GY, Jang SY, Chang SA, Kim SM, Park SJ, et al. The extent of late gadolinium enhancement can predict adverse cardiac outcomes in patients with non-ischemic cardiomyopathy with reduced left ventricular ejection fraction: a prospective observational study. Korean J Radiol 2021;22:324-333 
39. Lee J, Jeong WK, Kim JH, Kim JM, Kim TY, Choi GS, et al. Serial observations of muscle and fat mass as prognostic factors for deceased donor liver transplantation. Korean J Radiol 2021;22:189-197 
40. Shao D, Gao Q, Cheng Y, Du DY, Wang SY, Wang SX. The prognostic value of 18F-fluorodeoxyglucose PET/CT in the initial assessment of primary tracheal malignant tumor: a retrospective study. Korean J Radiol 2021;22:425-434 
41. Cho YH, Do KH, Chae EJ, Choi SH, Jo KW, Lee SO, et al. Association of chest CT-based quantitative measures of muscle and fat with post-lung transplant survival and morbidity: a single institutional retrospective cohort study in Korean population. Korean J Radiol 2019;20:522-530 
42. Yeon EK, Cho YD, Yoo DH, Lee SH, Kang HS, Cho WS, et al. De novo intracranial aneurysms detected on imaging follow-up of coiled aneurysms in a Korean population. Korean J Radiol 2019;20:1390-1398 
43. BMJ. 12. Survival analysis. bmj.com Web site. https://www.bmj.com/about-bmj/resources-readers/publications/statistics-square-one/12-survival-analysis. Accessed July 15, 2021 
44. Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med 2007;356:227-236 
45. Ganna A, Reilly M, de Faire U, Pedersen N, Magnusson P, Ingelsson E. Risk prediction measures for case-cohort and nested case-control designs: an application to cardiovascular disease. Am J Epidemiol 2012;175:715-724 
46. Schaubel DE, Zhang H, Kalbfleisch JD, Shu X. Semiparametric methods for survival analysis of case-control data subject to dependent censoring. Can J Stat 2014;42:365-383 
47. Yoen H, Park HE, Kim SH, Yoon JH, Hur BY, Bae JS, et al. Prognostic value of tumor regression grade on MR in rectal cancer: a large-scale, single-center experience. Korean J Radiol 2020;21:1065-1076 
48. Klein JP, Moeschberger ML. Survival analysis: techniques for censored and truncated data, 2nd ed. New York: Springer, 2003 
49. Choi JW, Lee JM, Lee DH, Yoon JH, Kim YJ, Lee JH, et al. Radiofrequency ablation using a separable clustered electrode for the treatment of hepatocellular carcinomas: a randomized controlled trial of a dual-switching monopolar mode versus a single-switching monopolar mode. Korean J Radiol 2021;22:179-188 
50. Im DJ, Hur J, Han K, Suh YJ, Hong YJ, Lee HJ, et al. Prognostic value of dual-energy CT-based iodine quantification versus conventional CT in acute pulmonary embolism: a propensity-match analysis. Korean J Radiol 2020;21:1095-1103 
51. Jeong DY, Kang TW, Min JH, Song KD, Lee MW, Rhim H, et al. Effect of perfluorobutane microbubbles on radiofrequency ablation for hepatocellular carcinoma: suppression of steam popping and its clinical implication. Korean J Radiol 2020;21:1077-1086 
52. Lee B, Choi YJ, Kim SO, Lee YS, Hong JY, Baek JH, et al. Prognostic value of radiologic extranodal extension in human papillomavirus-related oropharyngeal squamous cell carcinoma. Korean J Radiol 2019;20:1266-1274 
53. Lee DH, Kim SH, Lee SM, Han JK. Prediction of treatment outcome of chemotherapy using perfusion computed tomography in patients with unresectable advanced gastric cancer. Korean J Radiol 2019;20:589-598 
54. Klein JP, Logan B, Harhoff M, Andersen PK. Analyzing survival curves at a fixed point in time. Stat Med 2007;26:4505-4519 
55. Chen Z, Zhang G. Comparing survival curves based on medians. BMC Med Res Methodol 2016;16:33 
56. Kwon JH, Gwon DI, Kim JW, Chu HH, Kim JH, Ko GY, et al. Percutaneous biliary metallic stent insertion in patients with malignant duodenobiliary obstruction: outcomes and factors influencing biliary stent patency. Korean J Radiol 2020;21:695-706 
57. Kim R, Kim CK, Park JJ, Kim JH, Seo SI, Jeon SS, et al. Prognostic significance for long-term outcomes following radical prostatectomy in men with prostate cancer: evaluation with prostate imaging reporting and data system version 2. Korean J Radiol 2019;20:256-264 
58. Hwang HJ, Lee SM, Seo JB, Kim JE, Choi HY, Kim N, et al. Quantitative vertebral bone density seen on chest CT in chronic obstructive pulmonary disease patients: association with mortality in the Korean obstructive lung disease cohort. Korean J Radiol 2020;21:880-890 
59. Nieto FJ, Coresh J. Adjusting survival curves for confounders: a review and a new method. Am J Epidemiol 1996;143:1059-1068 
60. Ghali WA, Quan H, Brant R, van Melle G, Norris CM, Faris PD, et al. Comparison of 2 methods for calculating adjusted survival curves from proportional hazards models. JAMA 2001;286:1494-1497 
61. Liu Z, Jin C, Wu CC, Liang T, Zhao H, Wang Y, et al. Association between initial chest CT or clinical features and clinical course in patients with coronavirus disease 2019 pneumonia. Korean J Radiol 2020;21:736-745 
62. Won SY, Park HS, Kim EK, Kim SI, Moon HJ, Yoon JH, et al. Survival rates of breast cancer patients aged 40 to 49 years according to detection modality in Korea: screening ultrasound versus mammography. Korean J Radiol 2021;22:159-167 
63. Wang T, Yang Y, Liu X, Deng J, Wu J, Hou L, et al. Primary invasive mucinous adenocarcinoma of the lung: prognostic value of CT imaging features combined with clinical factors. Korean J Radiol 2021;22:652-662 
64. Choi WS, Yoon CJ, Lee JH. Percutaneous enteral stent placement using a transhepatic access for palliation of malignant bowel obstruction after surgery. Korean J Radiol 2021;22:742-750 
65. Zheng Y, Xiao A, Yu X, Zhao Y, Lu Y, Li X, et al. Development and validation of a prognostic nomogram based on clinical and CT features for adverse outcome prediction in patients with COVID-19. Korean J Radiol 2020;21:1007-1017 
66. Kim NH, Lee SR, Kim YH, Kim HJ. Diagnostic performance and prognostic relevance of FDG positron emission tomography/computed tomography for patients with extrahepatic cholangiocarcinoma. Korean J Radiol 2020;21:1355-1366 
67. Oh J, Lee JM, Park J, Joo I, Yoon JH, Lee DH, et al. Hepatocellular carcinoma: texture analysis of preoperative computed tomography images can provide markers of tumor grade and disease-free survival. Korean J Radiol 2019;20:569-579