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Head and Neck Cancer: What Factors Affect Risk of In-Hospital Mortality?

Along with a variety of other patient- and hospital-related factors, male sex, weekend admissions, and treatment at nonteaching hospitals are associated with increased in-hospital mortality for patients with head and neck cancer, report the authors of a cross-sectional study published today in JAMA Otolaryngology—Head and Neck Surgery.

Using the 2008 to 2013 National Inpatient Sample database, the investigators identified adult hospitalized patients diagnosed with either primary or secondary head and neck cancer. They analyzed the data to calculate patient- and hospital-related risk factors for a primary end point of in-hospital mortality.

Among 85,440 patients, 71.1% of whom were male, with a mean age of 62.2 years, 3,610 patients (4.2%) died during a hospital stay.

The largest patient-related risk factor associated with in-hospital mortality was age, with an adjusted odds ratio of 1.03 per year increase in age; a multilevel analysis showed a 3% increase in risk for every additional year of age. The researchers remark that older patients may present with more advanced disease, and age has a direct association with other health-related outcomes, including hospital complications, length of stay, and intensive care unit admissions.

"The age discrepancy in head and neck cancer in-hospital mortality observed in our study may also be explained by the increasing prevalence of human papillomavirus–positive head and neck cancer," note the investigators, led by first author Eric Adjei Boakye, PhD, Research Assistant Professor in the Department of Population Science and Policy of the Southern Illinois University School of Medicine. "Younger patients are more likely to have human papillomavirus–associated oropharyngeal cancer, which has a very different etiology and pathophysiology and carries a much better prognosis."

Male sex was also a substantial risk factor, with an adjusted odds ratio of 1.23. "Male individuals exhibit more risk factors such as smoking and alcohol use, which are associated with worse treatment outcomes and higher comorbidities," note Dr. Adjei Boakye and colleagues. "Moreover, once diagnosed, male patients are less likely to seek medical care and are less compliant with treatment protocol compared with their female counterparts."

Additional patient-related risk factors included having a higher number of comorbidities (adjusted odds ratio of 1.14), having a metastatic cancer (adjusted odds ratio of 1.49), having a nonelective hospital admission (adjusted odds ratio of 3.26), and being admitted to the hospital on a weekend (adjusted odds ratio of 1.30).

"Reduced number of staff on the weekend may result in delayed diagnosis and management of a patient's condition, placing further emphasis on the importance of robust multidisciplinary team management, including nursing staff, pharmacists, and physicians," state the authors. "Furthermore, patients admitted during the weekend are more likely to be nonelective, emergency admissions."

Of the hospital-related factors, admission to a nonteaching hospital was associated with increased risk of in-hospital mortality, with an adjusted odds ratio of 1.48, as was greater length of stay at the hospital (adjusted odds ratio of 1.02 per one-day increase in hospital stay).

The association with increased mortality risk at nonteaching hospitals confirms previous findings in other studies.

"Teaching hospitals are more likely to be high-volume centers and perform more surgeries… compared with community or nonteaching institutions, which are more likely to treat head and neck cancer with radiation or without chemotherapy," write Dr. Adjei Boakye and colleagues, noting that academic institutions have been found to have better compliance with National Institutes of Health Guidelines. "Moreover, academic centers tend to have more abundant multidisciplinary teams, specialists, and ancillary staff that are better equipped to minimize and manage perioperative and postoperative complications."

In addition to their calculation of odds ratios, the researchers used a multivariable logistic regression analysis to build an in-hospital mortality prediction model, which they represented in a nomogram, a graphic that consists of lines portraying multiple variable quantities, marked off to scale and arranged so that using a straightedge to connect known values on two different lines, it is possible to read an unknown value using the point of intersection with another line.

"Nomograms are currently the most accurate available tools, with the greatest discriminating characteristics for predicting outcomes in patients with different cancers. They provide easily understood outcome probabilities and individualized disease-related risk estimations that facilitate patient management-related decisions," explain the researchers. "Nomogram use may not only facilitate early management decision making but may also minimize unnecessary tests and expenses." According to the authors, this method of understanding risk factors has added benefits compared with traditional odds ratios: "A nomogram is advantageous in that users can tell the association of a risk factor with the outcome by simply adding the points."

How can all of these data and the researchers' nomogram be of use?

"This information can help identify patients at higher risk of in-hospital mortality in the future. Greater levels of care and surveillance may improve their hospital course," state Dr. Adjei Boakye and colleagues. "These multilevel factors are critical indicators of survivorship and should thus be considered when planning programs or interventions aimed to improve survival among this unique population."

For More Information

Adjei Boakye E, Osazuwa-Peters N, Chen B, et al (2020). Multilevel associations between patient- and hospital-level factors and in-hospital mortality among hospitalized patients with head and neck cancer. JAMA Otolaryngol Head Neck Surg. [Epub ahead of print] DOI:10.1001/jamaoto.2020.0132

Image credit: Antti Yrjönen. Courtesy of Vantaa City Museum. Licensed under CC BY 4.0


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