Poster Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2017

Incidence of unplanned admissions during chemoradiotherapy for head and neck and lung cancers. (#187)

Siddharth Menon 1 2 , Muhammad Alamgeer
  1. Monash Health, Melbourne, VIC, Australia
  2. Medical Oncology, Monash Health, Melbourne, VIC, Australia


Concurrent chemoradiotherapy (CRT) is a commonly used treatment modality to achieve cure in locally advanced head and neck (HNSCC) and non-small cell lung cancers (NSCLC). Unplanned admissions due to treatment related toxicities are common and have major financial and clinical implications.

The aim of this retrospective study was to estimate the incidence, reasons and predictors of unplanned admissions for patients receiving CRT for HNSCC and NSCLC. 


Patients treated with definitive or adjuvant CRT, from 1 April 2016 to 31 March 2017 were included. A review of the institution's electronic medical record database was performed. Outpatient clinic entries and discharge summaries were reviewed to collect information on hospitalizations during or within 60 days of CRT. Analysis of various patient and treatment related factors was performed. 


A total of 61 patients with HNSCC and 35 with NSCLC were treated with CRT. Of the HNSCC cohort, 39 had oropharyngeal SCC (64%). p16 status was positive in 37 (95%) of those. Of 35 NSCLC patients, 9 (26%) had SCC and 22 (63%) adenocarcinoma. A total of 36 (38%) patients required admissions resulting in 45 inpatient episodes. Of those 33 (73%) were HNSCC while 12 (27%) were NSCLC. in HNSCC, symptoms related to oropharyngeal mucositis was the most frequent reason for admission resulting in 18 admissions (55%), with febrile neutropenia 8 (24%), malnutrition 8 (24%) and dysphagia 5 (15%) also listed as common discharge diagnoses. 

In NSCLC, the common indications for admissions were oesophagitis with 4 admissions (33%) and chest infections accounting for 6 (50%). 


Unplanned hospital admissions during CRT are common and pose a strain on the health system as well as create significant patient morbidity. Additional data is being collected to understand the predictors and hopefully suggest interventions to alleviate this.