Head and neck cancer patients recollection of their clinical characteristics

SIMON ROGERS, Helen Al-Nakisbandi, Anna Dahill, Derek Lowe

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Patient reported outcomes (PRO) are an important component of treatment evaluation. Typically, PROs are completed by patients on paper, however through advances in technology, such as mobile phone apps and websites, there is great opportunity for electronic completion. It can be challenging particularly at a regional or national level to maintain accurate core clinical head and neck cancer (HNC) records; baseline, recurrence, second primary, and further treatments. These will influence PRO and outcomes reporting. In addition, with data security and confidentiality, there is merit in undertaking anonymous surveys but in this approach, there is a reliance on patient recall. The aim of this study was to compare updated hospital records with details completed by patients. In January 2019, 395 HNC patients treated in 2015 and 2016 were sent a survey. They were asked to recall clinical variables of gender, age at diagnosis, tumour site, tumour stage and primary treatment and these were analysed for agreement with hospital records. The Kappa statistic (KP) was used to measure strength of agreement for categorical variables. There were 146 responders with one patient correctly stating they did not have cancer. Five patients indicated further disease rather than primary cancer within the selection cohort of 2015-16. Agreement between hospital record and patient recall was excellent for gender (KP=0.97) and age-group (KP=0.92), very good for treatment (KP=0.79), good for site of cancer (KP=0.61) but poor for stage of cancer (KP=0.18). Conclusion: In general patients give accurate accounts of these
HNC details apart from tumour staging.
Original languageEnglish
Pages (from-to)86-90
Number of pages5
JournalBritish Journal of Oral and Maxillofacial Surgery
Issue number1
Early online date20 Aug 2020
Publication statusPublished - 1 Jan 2021


  • Patients recollection
  • head and neck cancer
  • datasets of clinical characteristics
  • health literacy


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