Competing Risk Analysis in Lung Cancer Patients Over 80 Years Old Undergoing Surgery

  • Haruaki Hino
  • Takahiro Karasaki
  • Yukihiro Yoshida
  • Takeshi Fukami
  • Atsushi Sano
  • Makoto Tanaka
  • Yoshiaki Furuhata
  • Kosuke Kashiwabara
  • Junji Ichinose
  • Mitsuaki Kawashima
  • Jun NakajimaEmail author
Original Scientific Report



This study aimed to analyze cause-specific mortality in lung cancer patients over 80 years old undergoing surgery.


This retrospective, multi-institutional analysis included patients aged ≥ 80 years who underwent radical surgery for primary lung cancer from January 1998 to December 2015. Preoperative clinical data, surgical results, survival, and cause of death were evaluated. Competing risk analysis for cause-specific mortality was performed.


Of the 337 patients (median age 82 years) enrolled and analyzed, 68.1% were male. There were 52 and 44 cancer-specific and non-cancer-specific deaths, respectively. On competing risk regression analysis, non-cancer-specific deaths were significantly associated with male sex (hazard ratio [HR]: 3.06, 95% confidence interval [CI]: 1.02–9.12, p = 0.046), coronary artery disease (HR: 2.49, 95% CI: 2.49 [1.14–5.47], p = 0.02), interstitial pneumonia (HR: 3.58, 95% CI: 1.73–7.40, p < 0.001), and pathological stage III (HR: 3.83, 95% CI: 1.44–10.13, p = 0.007). In contrast, cancer-specific deaths were significantly associated with limited resection (HR: 1.99, 95% CI: 1.02–3.89, p = 0.04) and pathological stage III (HR: 3.13, 95% CI: 1.44–6.80, p = 0.004). The 5-year cumulative incidences of lung cancer-specific and non-cancer-specific deaths were 18.0% and 15.9%, respectively.


Prognostic factors for non-cancer-specific death were different from those of cancer-specific death, except for pathological stage. Each prognostic factor should be considered when deciding surgical indication and procedure and monitoring for pulmonary events during outpatient follow-up.



We are deeply grateful to Editage for English proofreading.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

268_2019_4982_MOESM1_ESM.pdf (33 kb)
Cumulative incidence of death curve stratified by lung cancer-specific and non-cancer-specific deaths within 30 months after surgery (PDF 33 kb)


  1. 1.
    Ministry of Health, Labour and Welfare. Vital Statistics Japan (2018). Published 28 March 2018, Accessed 22 May 2018
  2. 2.
    Masuda M, Okumura M, Doki Y (2016) Committee for Scientific Affairs, The Japanese Association for Thoracic Surgery. Gen Thorac Cardiovasc Surg 64:665–697CrossRefGoogle Scholar
  3. 3.
    Dominguez-Ventura A, Allen MS, Cassivi SD et al (2006) Lung cancer in octogenarians: factors affecting morbidity and mortality after pulmonary resection. Ann Thorac Surg 82:1175–1179CrossRefGoogle Scholar
  4. 4.
    Dominguez-Ventura A, Cassivi SD, Allen MS et al (2007) Lung cancer in octogenarians: factors affecting long-term survival following resection. Eur J Cardiothorac Surg 32:370–374CrossRefGoogle Scholar
  5. 5.
    Okami J, Higashiyama M, Asamura H et al (2009) Pulmonary resection in patients aged 80 years or over with clinical stage I non-small cell lung cancer: prognostic factors for overall survival and risk factors for postoperative complications. J Thorac Oncol 4:1247–1253CrossRefGoogle Scholar
  6. 6.
    Blanchard EM, Arnaoutakis K, Hesketh PJ (2010) Lung cancer in octogenarians. J Thorac Oncol 5:909–916CrossRefGoogle Scholar
  7. 7.
    Fanucchi O, Ambrogi MC, Dini P et al (2011) Surgical treatment of non-small cell lung cancer in octogenarians. Interact CardioVasc Thorac Surg 12:749–753CrossRefGoogle Scholar
  8. 8.
    Hino H, Murakawa T, Ichinose J et al (2015) Results of lung cancer surgery for octogenarians. Ann Thorac Cardiovasc Surg 21:209–216CrossRefGoogle Scholar
  9. 9.
    Saji H, Ueno T, Nakamura H et al (2018) A proposal for a comprehensive risk scoring system for predicting postoperative complications in octogenarian patients with medically operable lung cancer: JACS1303. Eur J Cardiothorac Surg 53:835–841CrossRefGoogle Scholar
  10. 10.
    Hino H, Karasaki T, Yoshida Y, Fukami T, Sano A, Tanaka M, Furuhata Y, Ichinose J, Kawashima M, Nakajima J (2018) Risk factors for postoperative complications and long-term survival in lung cancer patients older than 80 years. Eur J Cardiothorac Surg 53:980–986CrossRefGoogle Scholar
  11. 11.
    Eguchi T, Bains S, Lee MC et al (2017) Impact of increasing age on cause-specific mortality and morbidity in patients with I non-small-cell lung cancer: a competing risks analysis. J Clin Oncol 35:281–290CrossRefGoogle Scholar
  12. 12.
    Fine JP, Gray RJ (1999) A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 94:496–509CrossRefGoogle Scholar
  13. 13.
    Sobin LH, Gospodarowicz MK, Wittekind C (2009) lung and pleural tumours. In: Sobin LH, Gospodarowicz MK, Wittekind C (eds) UICC International Union Against Cancer TNM Classification of malignant tumours, 7th edn. Wiley-Blackwell, Oxford, pp 138–146Google Scholar
  14. 14.
    Travis WD, Brambilla E, Müller-Hermelink HK, Harris CC (2004) Pathology and genetics of tumours of the lung, pleura, thymus and heart. In: Travis WD, Brambilla E, Müller-Hermelink HK, Harris CC (eds) World Health Organization classification of tumours. IARC Press, Lyon, pp 9–124Google Scholar
  15. 15.
    Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383CrossRefGoogle Scholar
  16. 16.
    McMillan DC, Elahi MM, Sattar N, Angerson WJ, Johnstone J, McArdle CS (2001) Measurement of the systemic inflammatory response predicts cancer-specific and non-cancer survival in patients with cancer. Nutr Cancer 41:64–69CrossRefGoogle Scholar
  17. 17.
    Kanda Y (2013) Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transpl 48:452–458CrossRefGoogle Scholar
  18. 18.
    Scrucca L, Santucci A, Aversa F (2007) Competing risk analysis using R: an easy guide for clinicians. Bone Marrow Transpl 40:381–387CrossRefGoogle Scholar
  19. 19.
    Albertsen PC, Hanley JA, Gleason DF, Barry MJ (1998) Competing risk analysis of men aged 55 to 74 years at diagnosis managed conservatively for clinically localized prostate cancer. JAMA 280:975–980CrossRefGoogle Scholar
  20. 20.
    Cai M, Wei J, Zhang Z et al (2012) Impact of age on the cancer-specific survival of patients with localized renal cell carcinoma: martingale residual and competing risks analysis. PLoS ONE 7:e48489CrossRefGoogle Scholar
  21. 21.
    Yang L, Shen W, Sakamoto N (2013) Population-based study evaluating and predicting the probability of death resulting from thyroid cancer and other causes among patients with thyroid cancer. J Clin Oncol 31:468–474CrossRefGoogle Scholar
  22. 22.
    Shen W, Sakamoto N, Yang L (2015) Cancer-specific mortality and competing mortality in patients with head and neck squamous cell carcinoma: a competing risk analysis. Ann Surg Oncol 22:264–271CrossRefGoogle Scholar
  23. 23.
    Ferraz RO, Moreira-Filho DC (2017) Survival analysis of women with breast cancer: competing risk models. Cien Saude Colet 22:3743–3754CrossRefGoogle Scholar
  24. 24.
    Bayliss EA, Reifler LM, Zeng C et al (2014) Competing risks of cancer mortality and cardiovascular events in individuals with multimorbidity. J Comorb 4:29–36CrossRefGoogle Scholar
  25. 25.
    Austin Peter C, Lee Douglas S, Fine Jason P (2016) Introduction to the analysis of survival data in the presence of competing risks. Circulation 133:601–609CrossRefGoogle Scholar
  26. 26.
    Baade PD, Royle JA, Joske DJ, Fritschi L (2011) Non-cancer mortality among people diagnosed with lymphohaematopoietic neoplasm in Australia. Cancer Causes Control 22:715–723CrossRefGoogle Scholar
  27. 27.
    Tan KS, Eguchi T, Adusumilli PS (2017) Competing risks and cancer-specific mortality: why it matters. Oncotarget 9:7272–7273Google Scholar
  28. 28.
    Gillings D, Koch G (1991) The application of the principle of intention–to–treat to the analysis of clinical trials. Drug Inf J 25:411–424CrossRefGoogle Scholar
  29. 29.
    Kiss Nicole (2016) Nutrition support and dietary interventions for patients with lung cancer: current insights. Lung Cancer (Auckl) 7:1–9Google Scholar
  30. 30.
    Bugge AS, Lund MB, Valberg M et al (2018) Cause-specific death after surgical resection for early-stage non-small-cell lung cancer. Eur J Cardiothorac Surg 53:221–227CrossRefGoogle Scholar

Copyright information

© Société Internationale de Chirurgie 2019

Authors and Affiliations

  • Haruaki Hino
    • 1
  • Takahiro Karasaki
    • 2
  • Yukihiro Yoshida
    • 3
  • Takeshi Fukami
    • 4
  • Atsushi Sano
    • 5
  • Makoto Tanaka
    • 6
  • Yoshiaki Furuhata
    • 7
  • Kosuke Kashiwabara
    • 8
  • Junji Ichinose
    • 2
  • Mitsuaki Kawashima
    • 2
  • Jun Nakajima
    • 2
    Email author
  1. 1.Department of Thoracic SurgeryTokyo Metropolitan Geriatric Hospital and Institute of GerontologyTokyoJapan
  2. 2.Department of Thoracic SurgeryThe University of Tokyo Graduate School of MedicineTokyoJapan
  3. 3.Department of Thoracic SurgeryAsahi General HospitalChibaJapan
  4. 4.Department of Thoracic SurgeryNational Hospital Organization Tokyo National HospitalTokyoJapan
  5. 5.Department of Thoracic SurgeryChigasaki Municipal HospitalKanagawaJapan
  6. 6.Department of Thoracic SurgeryJR Tokyo General HospitalTokyoJapan
  7. 7.Department of Thoracic SurgeryJapanese Red Cross Medical CenterTokyoJapan
  8. 8.Department of Biostatistics, School of Public HealthThe University of TokyoTokyoJapan

Personalised recommendations