Clinical Oral Investigations

, Volume 23, Issue 9, pp 3581–3588 | Cite as

Association between perioperative oral care and postoperative pneumonia after cancer resection: conventional versus high-dimensional propensity score matching analysis

  • Miho IshimaruEmail author
  • Sachiko Ono
  • Hiroki Matsui
  • Hideo Yasunaga
Original Article



Perioperative oral care was reported to decrease postoperative pneumonia after cancer resections. However, the effect remains controversial because previous studies were limited due to their small sample sizes and lack of strict control for patient backgrounds. The present study evaluated the association between perioperative oral care and postoperative pneumonia using high-dimensional propensity score (hd-PS) matching to adjust for confounding factors.

Materials and methods

Using a Japanese health insurance claims database, we identified patients who underwent surgical treatment of cancer from April 2014 to March 2015. To compare outcomes (postoperative pneumonia and procedure-related complications) between patients with and without perioperative oral care, we performed hd-PS matching and conventional PS matching and chi-square test.


We identified 621 patients with oral care and 4374 patients without oral care. The occurrences of postoperative pneumonia were not significantly different between patients with and without oral care in the unmatched (2.9% vs. 3.2%), conventional PS-matched (2.9% vs. 2.9%), or hd-PS-matched (2.9% vs. 3.3%) groups. The occurrences of procedure-related complication were not significantly different between patients with and without oral care in the unmatched (23.8% vs. 24.5%), conventional PS-matched (23.8% vs. 26.4%), or hd-PS-matched (24.4% vs. 27.7%) groups.


There was no significant difference in postoperative pneumonia or procedure-related complications between patients with and without perioperative oral care.

Clinical relevance

While maintaining optimal oral care in cancer patients is an important goal, the present study revealed no significant difference in postoperative outcomes. Further investigations would be needed to determine the effect of perioperative oral care.


Oral hygiene Perioperative care Postoperative complications Propensity score analysis 



This work was supported by grants from the Ministry of Health, Labour and Welfare, Japan (H29-Policy-Designated-009 and H29-ICT-General-004); Ministry of Education, Culture, Sports, Science, and Technology, Japan (17H04141); and the Japan Agency for Medical Research and Development (AMED).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The Institutional Review Board at The University of Tokyo approved the study protocol.

Informed consent

Informed consent was waived because of the anonymous nature of the data.


  1. 1.
    Spreadborough P, Lort S, Pasquali S et al (2016) A systematic review and meta-analysis of perioperative oral decontamination in patients undergoing major elective surgery. Perioper Med 5:6–12CrossRefGoogle Scholar
  2. 2.
    Zuckerman LM (2016) Oral chlorhexidine use to prevent ventilator-associated pneumonia in adult. Dimens Crit Care Nurs 35(1):25–36CrossRefPubMedGoogle Scholar
  3. 3.
    Silvestri L, Weir I, Gregori D et al (2014) Effectiveness of oral chlorhexidine on nosocomial pneumonia, causative micro-organisms and mortality in critically ill patients: a systematic review and meta-analysis. Minerva Anestesiol 80(7):805–820PubMedGoogle Scholar
  4. 4.
    Vilela MC, Ferreira GZ, Santos PS, Rezende NP (2015) Oral care and nosocomial pneumonia: a systematic review. Einstein 13(2):290–296CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Ono S, Ishimaru M, Yamana H et al (2017) Enhanced oral care and health outcomes among nursing facility residents: analysis using the national long-term care database in Japan. J Am Med Dir Assoc 18(3):e1–e5CrossRefGoogle Scholar
  6. 6.
    Sjögren P, Wårdh I, Zimmerman M, Almståhl A, Wikström M (2016) Oral care and mortality in older adults with pneumonia in hospitals or nursing homes: systematic review and meta-analysis. J Am Geriatr Soc 64(10):2109–2115CrossRefPubMedGoogle Scholar
  7. 7.
    Kaneoka A, Pisegna JM, Miloro KV, Lo M, Saito H, Riquelme LF, LaValley MP, Langmore SE (2015) Prevention of healthcare-associated pneumonia with oral care in individuals without mechanical ventilation: a systematic review and meta-analysis of randomized controlled trials. Infect Control Hosp Epidemiol 36(8):899–906CrossRefPubMedGoogle Scholar
  8. 8.
    Tohara T, Kikutani T, Tamura F, Yoshida M, Kuboki T (2017) Multicentered epidemiological study of factors associated with total bacterial count in the saliva of older people requiring nursing home. Geriatr Gerontol Int 17(2):219–225CrossRefPubMedGoogle Scholar
  9. 9.
    Ishikawa A, Yoneyama T, Hirota K, Miyake Y, Miyatake K (2008) Professional oral health care reduces the number of oropharyngeal bacteria. J Dent Res 87:594–598CrossRefPubMedGoogle Scholar
  10. 10.
    El-Solh AA, Pietrantoni C, Bhat A et al (2004) Colonization of dental plaques: a reservoir of respiratory pathogens for hospital acquired pneumonia in institutionalized elders. Chest 126:1575–1582CrossRefPubMedGoogle Scholar
  11. 11.
    Bágyi K, Haczku A, Márton I, Szabó J, Gáspár A, Andrási M, Varga I, Tóth J, Klekner A (2009) Role of pathogenic oral flora in postoperative pneumonia following brain surgery. BMC Infect Dis 9:104–113CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Wren SM, Martin M, Yoon JK, Bech F (2010) Postoperative pneumonia-prevention program for the inpatient surgical ward. J Am Coll Surg 210:491–495CrossRefPubMedGoogle Scholar
  13. 13.
    Akutu Y, Matsubara H, Okazumi S et al (2008) Impact of preoperative dental plaque culture for predicting postoperative pneumonia in esophageal cancer patients. Dig Surg 25:93–97CrossRefGoogle Scholar
  14. 14.
    Akutsu Y, Matsubara H, Shuto K, Shiratori T, Uesato M, Miyazawa Y, Hoshino I, Murakami K, Usui A, Kano M, Miyauchi H (2010) Pre-operative dental brushing can reduce the risk of postoperative pneumonia in esophageal cancer patients. Surgery 147:497–502CrossRefPubMedGoogle Scholar
  15. 15.
    Yamazaki M, Matsuura K, Kato K et al (2009) Perioperative oral care reduced postoperative complications after head and neck reconstruction surgery. Tokeibu Geka 19:105–110 (Japanese)CrossRefGoogle Scholar
  16. 16.
    Hoshikawa Y, Tanda N, Matsuda Y et al (2016) Current status of preoperative professional oral care by dentists for elderly patients undergoing lung resection and occurrence of postoperative pneumonia. Kyobu Geka 69(1):25–29 (Japanese)PubMedGoogle Scholar
  17. 17.
    Soutome S, Yanamoto S, Funahara M, Hasegawa T, Komori T, Oho T, Umeda M (2016) Preventive effect on post-operative pneumonia of oral health care among patients who undergo esophageal resection: a multi-center retrospective study. Surg Infect 17(4):479–484 (Japanese)CrossRefGoogle Scholar
  18. 18.
    Atkinsm BZ, Shah AS, Hutcheson KA et al (2004) Reducing hospital morbidity and mortality following esophagectomy. Ann Thorac Surg 78:1170–1176CrossRefGoogle Scholar
  19. 19.
    Fang W, Kato H, Tachimori Y, Igaki H, Sato H, Daiko H (2003) Analysis of pulmonary complications after three-field lymph node dissection for esophageal cancer. Ann Thorac Surg 76:903–908CrossRefPubMedGoogle Scholar
  20. 20.
    Trinh VQ, Ravi P, Abd-El-Barr AM et al (2016) Pneumonia after major cancer surgery: temporal trends and patterns of care. Can Respir J 2016:1–7CrossRefGoogle Scholar
  21. 21.
    Sato J, Goto J, Harahashi A, Murata T, Hata H, Yamazaki Y, Satoh A, Notani KI, Kitagawa Y (2011) Oral health care reduced the risk of postoperative surgical site infection in inpatients with oral squamous cell carcinoma. Support Care Cancer 19:409–416CrossRefPubMedGoogle Scholar
  22. 22.
    Ueno T, Ota Y (2012) The importance of perioperative oral care. Jpn J Anesthesiol (Masui) 61(3):276–281 (Japanese)Google Scholar
  23. 23.
    Kimura S, Sato T, Ikeda S, Noda M, Nakayama T (2010) Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage. J Epidemiol 20:413–419CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Ono S, Ono Y, Matsui H, Yasunaga H (2016) Factors associated with hospitalization for seasonal influenza in a Japanese nonelderly cohort. BMC Public Health 16:922–929CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Garbe E, Kloss S, Suling M, Pigeot I, Schneeweiss S (2013) High-dimensional versus conventional propensity scores in a comparative effectiveness study of coxibs and reduced upper gastrointestinal complications. Eur J Clin Pharmacol 69:549–557CrossRefPubMedGoogle Scholar
  26. 26.
    Schneeweiss S, Rassem JA, Glynn RJ et al (2009) High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology 20:512–522CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Toh S, Rodríguez LAG, Hernán MA (2011) Confounding adjustment via a semi-automated high-dimensional propensity score algorithm: an application to electronic medical records. Pharmacoepidemiol Drug Saf 20:849–857CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Franklin JM, Eddings W, Glynn RJ, Schneeweiss S (2015) Regularized regression versus the high-dimensional propensity score for confounding adjustment in secondary database analyses. Am J Epidemiol 182:651–659CrossRefPubMedGoogle Scholar
  29. 29.
    Bross ID (1966) Spurious effects from an extraneous variable. J Chronic Dis 19:637–647CrossRefPubMedGoogle Scholar
  30. 30.
    Soutome S, Yanamoto S, Funahara M, Hasegawa T, Komori T, Yamada SI, Kurita H, Yamauchi C, Shibuya Y, Kojima Y, Nakahara H, Oho T, Umeda M (2017) Effect of perioperative oral care on prevention of postoperative pneumonia associated with esophageal cancer surgery: a multicenter case-control study with propensity score matching analysis. Medicine (Baltimore) 96(33):e7436–e7440CrossRefGoogle Scholar
  31. 31.
    Yang CK, Teng A, Lee DY, Rose K (2015) Pulmonary complications after major abdominal surgery: National Surgical Quality Improvement Program analysis. J Surg Res 198(2):441–449CrossRefPubMedGoogle Scholar
  32. 32.
    Kiuchi J, Komatsu S, Ichikawa D, Kosuga T, Okamoto K, Konishi H, Shiozaki A, Fujiwara H, Yasuda T, Otsuji E (2016) Putative risk factors for postoperative pneumonia which affects poor prognosis in patients with gastric cancer. Int J Clin Oncol 21:920–926CrossRefPubMedGoogle Scholar
  33. 33.
    Pettke E, Ilonzo N, Ayewah M, Tsantes S, Estabrook A, Ma AM (2016) Short-term, postoperative breast cancer outcomes in patients with advanced age. Am J Surg 212(4):677–681CrossRefPubMedGoogle Scholar
  34. 34.
    Hall MK, Taylor RA, Luty S, Allen IE, Moore CL (2016) Impact of point-of-care ultrasonography on ED time to disposition for patients with nontraumatic shock. Am J Emerg Med 34:1022–1030CrossRefPubMedGoogle Scholar
  35. 35.
    Rassen JA, Schneeweiss S (2012) Using high-dimensional propensity scores to automate confounding control in a distributed medical product safety surveillance system. Pharmacoepidemiol Drug Saf 21:41–49CrossRefPubMedGoogle Scholar
  36. 36.
    Guertin JR, Rahme E, LeLorier J (2016) Performance of the high-dimensional propensity score in adjusting for unmeasured confounders. Eur J Clin Pharmacol 72(12):1497–1505CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Guertin JR, Rahme E, Dormuth CR, LeLorier J (2016) Head to head comparison of the propensity score and the high-dimensional propensity score matching methods. BMC Med Res Methodol 16:22–31CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Chien SC, Ou SM, Shih CJ et al (2015) Comparative effectiveness of angiotensin-converting enzyme inhibitor and angiotensin II receptor blockers in terms of major cardiovascular disease outcomes in elderly patients. Medicine 94:1–10CrossRefGoogle Scholar
  39. 39.
    Le HV, Poole C, Brookhart MA et al (2013) Effects of aggregation of drug and diagnostic codes on the performance of the high-dimensional propensity score algorithm: an empirical example. BMC Med Res Methodol 13:142–152CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Hernandez I, Zhang Y (2015) Comparing clinical and economic outcomes of biologic and conventional medications in postmenopausal women with osteoporosis. J Eval Clin Pract 21:840–847CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Yamana H, Moriwaki M, Horiguchi H et al (2017) Validity of diagnoses, procedures, and laboratory data in Japanese administrative data. J Epidemiol 1–7Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Clinical Epidemiology and Health Economics, School of Public HealthThe University of TokyoTokyoJapan
  2. 2.Department of Biostatistics & BioinformaticsThe University of TokyoTokyoJapan

Personalised recommendations