Comorbidity in head and neck cancer: A critical appraisal and recommendations for practice

Paleri, Vinidh; Wight, Richard G.; Silver, Carl E.; Haigentz, Missak; Takes, Robert P.; Bradley, Patrick J.; Rinaldo, Alessandra; Sanábria, Álvaro; Bień, Stanisław; Ferlito, Alfio

doi:10.1016/j.oraloncology.2010.07.008

Cited by 196 publications

(199 citation statements)

References 77 publications

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“…2,21 Demographic factors such as age, sex, race, familial history of cancer, socioeconomic status, lifestyles, and habits (tobacco, alcohol, and substance abuse) are only a few of the many factors that impact outcomes of treatment. 13,14,22,23 Clinicians regularly use this information in the decision-making process for treatment of patients with cancer. However, none of the other host characteristics have representation in the current staging system for oral cancer.…”

Section: Discussionmentioning

confidence: 99%

Nomograms for preoperative prediction of prognosis in patients with oral cavity squamous cell carcinoma

Montero

Yu²,

Palmer

et al. 2013

Cancer

111

110

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BACKGROUND: This study sought to develop prognostic tools that will accurately predict overall and cancer-related mortality and risk of recurrence in individual patients with oral cancer based on host and tumor characteristics. These tools would take into account numerous prognosticators beyond those covered by the traditional TNM (tumor-node-metastasis) staging system. METHODS: Demographic, host, and tumor characteristics of 1617 patients with cancer of the oral cavity, who were treated primarily with surgery at a single-institution tertiary care cancer center between 1985 and 2009, were reviewed from a preexisting database. Recurrent disease was recorded in 509 patients (456 locoregional and 116 distant); 328 patients died of cancer-related causes, and 542 died of other causes. The median follow-up was 42 months (range, 1-300 months). The following variables were analyzed as predictors of prognosis: age, sex, race, alcohol and tobacco use, oral cavity subsite, invasion of other structures, comorbidity, tumor size, and clinical nodal status. The stepdown method was used to select the statistically most influential predictors for inclusion in the final nomogram for each outcome of interest. RESULTS: The most influential predictors of both recurrence and cancer-specific mortality probability (CSMP) were tumor size, nodal status, subsite, and bone invasion. Nomograms were generated for prediction of overall survival (OS), CSMP, and locoregional recurrence-free probability (LRRFP). The nomograms were internally validated with an overfit-corrected predictive discrimination metric (concordance index) for OS of 67%, CSMP of 66%, and LRRFP of 60%. CONCLUSIONS: Nomograms have been developed that can reasonably estimate OS, CSMP, and LRRFP based on specific tumor and host characteristics in patients with oral cancer. Cancer 2014;120:214-21.

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Section: Discussionmentioning

confidence: 99%

Nomograms for preoperative prediction of prognosis in patients with oral cavity squamous cell carcinoma

Montero

Yu²,

Palmer

et al. 2013

Cancer

111

110

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“…Particularly in elderly patients, these predominantly consist of reduced organ and cognitive functions, malnutrition, polypharmacy, and socio-economic factors. Most studies show that approximately 60 % of head and neck cancer patients have concurrent illnesses [5]. For better evaluation of comorbidities, weighted assessment systems like Adult Comorbidity Evaluation-27 (ACE-27), and Charlson Comorbidity Index (CCI) include the occurrence of comorbidities as well as their degrees.…”

mentioning

confidence: 99%

On the need for comprehensive assessment of impact of comorbidity in elderly patients with head and neck cancer

Teymoortash

Halmos

Silver

et al. 2014

Eur Arch Otorhinolaryngol

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Although a generally accepted definition of ''elderly'' still does not exist, in a medical context, persons over the age of 65 are often considered to be elderly. As life expectancy rates have increased within the last decades and continuously increase every year by approximately 3 months [1], this segment of the population has increased, particularly in Western countries. Because cancer is a disease of aging, the risk of developing malignant disease including head and neck cancer is highest in this patient population. It also follows that malignancy-related mortality is highest among the elderly.Younger patients with head and neck cancers have a much better overall prognosis. A comparative survival analysis revealed that patients with head and neck cancer who are aged 40 years or younger at the time of diagnosis show significantly improved 5-year survival when compared to older patients [2]. For all age groups the 5-year survival rate of patients with a newly diagnosed head and neck cancer is approximately 60 % at diagnosis. However, prognosis is a dynamic process that improves after the initial critical years of recurrence-free survival. Conditional relative survival shows clinically relevant variations according to time since diagnosis, type of cancer, and age [3]. Conditional survival rates can better analyze and reflect actual life expectancy. After 3 years of survival, the conditional survival rate improves from 60 % up to 80 %. However, long-term survival rates stagnate at 80 %. Patients cured of and neck cancer face an excess mortality of about 20 % in long-term follow-up [4]. The critical reason for this is attributed to the comorbid burden of head and neck cancer patients, connected with unhealthy habits and general lifestyle choices.Comorbidities in cancer patients are defined as one or more unrelated diseases present at the time of cancer diagnosis. Particularly in elderly patients, these predominantly consist of reduced organ and cognitive functions, malnutrition, polypharmacy, and socio-economic factors. Most studies show that approximately 60 % of head and neck cancer patients have concurrent illnesses [5]. For better evaluation of comorbidities, weighted assessment systems like Adult Comorbidity Evaluation-27 (ACE-27), and Charlson Comorbidity Index (CCI) include the occurrence of comorbidities as well as their degrees. Comorbidities exist in 46 % of head and neck cancer

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“…Other than actual tumour staging and treatment, co-morbidity burden, race and performance status are all factors which affect prognosis (Paleri et al, 2010). Some studies suggest factors such as stromal involvement are the most accurate for predicting the outcome of OPSCC lesions (Marsh et al, 2011), whereas others show that patterns of tumour invasion and differentiation, together with cervical node involvement, to be the most important (Rogers et al, 2009).…”

Section: Prognosismentioning

confidence: 99%

Textbook of Plastic and Reconstructive Surgery

Butler¹,

Ghali²,

Kalaskar³

2016

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A CIP catalogue record for this book is available from The British Library.This book is published under a Creative Commons Attribution Non-commercial Non-derivative 4.0 International license (CC BY-NC-ND 4.0). This license allows you to share, copy, distribute and transmit the work for personal and non-commercial use providing author and publisher attribution is clearly stated. Further details about CC BY licenses are available at http://creativecommons.org/ licenses/by/4.0The publishers cannot guarantee the accuracy of any information about dosage and application contained in this book. The user is advised to always check the product information and clinical procedures with the most up-to-date published product information and the most recent codes of conduct and safety regulations. The authors and the publishers do not accept responsibility or legal liability for any errors in the text or misuse or misapplication of material in this work.ISBN: 978-1-910634-37-0 (Hbk.) ISBN: 978-1-910634-38-7 (Pbk.) ISBN: 978-1-910634-39-4 (PDF) ISBN: 978-1-910634-40-0 (epub) ISBN: 978-1-910634-41-7 (mobi)

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Comorbidity in head and neck cancer: A critical appraisal and recommendations for practice

Cited by 196 publications

References 77 publications

Nomograms for preoperative prediction of prognosis in patients with oral cavity squamous cell carcinoma

Nomograms for preoperative prediction of prognosis in patients with oral cavity squamous cell carcinoma

On the need for comprehensive assessment of impact of comorbidity in elderly patients with head and neck cancer

Textbook of Plastic and Reconstructive Surgery

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