Effectiveness of a Screening Tool for Early Identification of Malnutrition in Patients with Head and Neck Cancer
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The purpose of this study was to evaluate the impact of the Malnutritional Universal Screening Tool (MUST) assessment on effects of postoperative surgical site infection (SSI) and length of hospitalization stay (LOS) for patients undergoing oncologic resection for head and neck cancers. A pre-posttest design was used to evaluate the effects of preoperative nutritional screening on postoperative SSI and LOS rates in patients undergoing oncologic resection. A purposive sampling was used to recruit participants for the study. Pre- and post-implementation data were collected over a period of 8 weeks. All patients in the post-implementation group were assessed using the MUST and pre-surgery nutritional optimization was instituted. All participants were monitored for incidences of SSI until discharge. Of the 36 patients in the post-implementation group, 23(63.9%) had a MUST score of moderate to high and 13 (36.1%) had a score of low risk. There was a statistical significance observed between the pre-and post-implementation groups, with both postoperative surgical site infection (SSI) reduced from 50% to 22% and length of hospitalization stay from 28 to 17 days (p = 0.014) between the groups. Patients who were non-smokers (p = 0.010) and without reconstruction after surgery (p = 0.007) were less likely to develop postoperative SSI. Use of the MUST for preoperative nutritional screening has demonstrated that it is a feasible and easy to implement tool for assessment of malnutrition and it has demonstrated positive outcomes in reduction of both postoperative SSI and length of hospitalization stay.
KeywordsHNSCC Nutritional screening MUST LOS SSI
Head and neck cancer are malignancies occurring in the upper aerodigestive track including the oral cavity, oropharynx, hypopharynx, and larynx . It is the sixth most common malignancy in the world  with squamous cell cancer as the predominant histology type. The incidences are frequently associated with heavy use of alcohol and smoking. With an incidence of 6.5 cases per 10,000, South East Asia has the highest incidence worldwide . The main treatment modality with curative intention in early stage is surgical intervention and postoperative adjuvant chemotherapy and radiotherapy . Postoperative complications are often challenging to manage due to preexisting poor nutritional state prior to surgery . Significant malnutrition exists in 35–50% of patients with cancer of the head and neck region, which are often multifactorial in nature . Anatomical location of the tumors can result in dysphagia, odynophagia, dysgeusia, chewing difficulties, and pain  which contributes to malnutrition.
Unintentional weight loss leading to nutritional deficiencies is a life-threatening and complicated clinical concern for patients undergoing curative cancer treatment. Surgical-related complications can be attributed to nutrition deficiency state combined with the immune suppressive effects of surgery, general anesthesia, and tumors effects suppressing immune functions, which contribute to poor healing [21, 27]. Complications such as increased rate of infections, decreased immunity, delayed wound healing, disruption of treatment can result in increased morbidity and mortality post-surgery. Nutritional interventions perioperatively have demonstrated beneficial outcomes which include significant reductions in postoperative complications and length of hospitalization stay [8, 9, 10, 26]. However, most patients are not adequately assessed due to the absence of a quick, simple, and effective screening tool. A validated screening tool can detect malnutrition, reduce misdiagnosis, and ensure timely and appropriate assessment and treatment for malnutrition [4, 6]. Hence, early preoperative screening and identification of malnutrition are paramount as it provides practitioners with a systematic assessment of the nutritional status of the individual.
Postoperative complications are often challenging to manage due to preexisting poor nutritional state , which is a contributing factor in the spiral effects of postoperative complications and mortality particularly in patients with head and neck cancer [1, 5, 32]. Increased postoperative infection rates ranging from 20 to 40%, were observed in both surgical and non-surgical-related infections and were significantly correlated with patients who were malnourished at diagnosis [9, 10, 13, 17, 26, 33]. Therefore, preoperative assessment of nutritional status using a validated screening tool that has high specificity and sensitivity is vital in the initial screening of patients so that accurate assessment of their nutritional status can be established. Early nutritional interventions to correct malnutrition can positively influence postoperative outcomes such as reduced postoperative complications and length of hospitalization [9, 10, 13, 26, 33].
The use of a validated screening tool such as the Malnutritional Universal Screening Tool (MUST) can significantly increase the detection rate of malnutrition thus enhancing early identification and treatment for malnutrition [4, 6]. It is used for identifying malnourished and at risk of malnutrition status with specific recommendations based on the score. There is also a correlation between MUST and its ability to predict postoperative outcomes for both surgical and non-surgical complications [1, 2, 23, 28, 30, 31] in terms of length of hospitalization stay, mortality, hospitalization cost and improved quality of life [1, 9, 13, 30, 33]. MUST is an effective measurement of nutritional status with high indexes for sensitivity, specificity and concordance agreement in comparison with the standard Patient-Generated Subjective Global Assessment (PG-SGA) for oncology patients [1, 3, 4, 5, 30, 31]. Thus, these essential factors were considered (practicability, predictively, reliability, validity, and ease of implementation) before tool implementation for the intended group and purpose.
The study used a pre-posttest intervention design approach to evaluate the effectiveness of the Malnutrition Universal Screening Tool (MUST) , a nutritional screening tool for early detection of malnutrition. A purposive sampling strategy was used to recruit participants. The inclusion criteria included newly diagnosed head and cancer patients planned for oncologic resection with or without reconstruction, who were 21 years old and willing to comply with the nutritional interventions. Participants with history of malabsorption syndrome, uncontrolled diabetics mellites were excluded. The study was conducted after approval from the Duke University Institutional Review Board (DIRB) and the Quality Department Management (QDM) of the tertiary cancer center. Participants enrolled were briefed on the purpose of the project. Participants included in the study were screened using the MUST tool before surgery. Participants with a MUST score of medium risk and above were referred to the dietitian for consultation prior to their scheduled surgery. Dietitians from the dietetic department performed a comprehensive nutritional assessment using the subjective global assessment (SGA) tool which is validated for its accuracy in nutritional assessment on oncology population. Nutritional interventions were started after the assessment between 3 to 5 days before surgery. Patients were reviewed postoperatively and nutritional supplements initiated as required after surgery.
Screened with MUST n = 36
Referred to dietician
Low risk (0)
Medium risk (1)
High risk (2 and above)
Variables measured consisted of demographic data, BMI, clinical characteristics, postoperative complication rates (surgical and non-surgical related), length of hospitalization stay, and MUST scoring. Comparison of the MUST score with the subjective global assessment (SGA) score, a comprehensive assessment tool used in oncology population was used to compare the concordance between the tools. All participants were monitored for postoperative complication and length of hospitalization stay until their discharge.
Descriptive statistics was used to detail the sociodemographic and clinical characteristics for the total sample (N = 74) and by groups (pre- and post-implementation). Chi-square test was used for categorical variables and independent t-test for continuous measures to evaluate for between-group differences. Non-parametric Fisher’s exact test was used when assumption of test was violated. Sample comparison was used to identify potential covariates included in the outcome analysis. Smoking status and type of surgical closure were included as covariate for analysis. The sample size estimated to be required for this study was 74 patients .
Demographics and clinical outcomes
Pre-implementation n = 38
Post-implementation n = 36
Male = 23 (60.5%)
Female = 15 (39.5%)
Male = 17 (47.2%)
Female = 19 (52.8%)
Mean: 63.86 (SD = 9.94)
Mean: 60.85 (SD = 12.11)
Yes: 19 (50%)
No: 19 (50%)
Yes: 24 (66.7%)
No: 12 (15.1%)
Oral cavity: 25 (65.8%)
Hypopharynx: 3 (7.9%)
Oropharynx: 1 (2.6%)
Larynx: 3 (7.9%)
Others: 6 (15.8%)
Oral cavity: 32 (88.9%)
Larynx: 1 (1.9%)
Others: 3 (8.3%)
Yes: 15 (39.5%)
No: 23 (60.5%)
Yes: 8 (11.2%)
No: 28 (77.8%)
Type of closure
No reconstruction: 16 (42.1%)
With reconstruction: 22 (57.9%)
No reconstruction: 16 (44.45)
With reconstruction: 20 (55.6%)
Surgical SSI (surgical site infection)
Yes: 19 (50%)
No: 19 (50%)
Yes: 8 (22.2%)
No: 28 (77.8%)
LOS (length of hospitalization stay)
Mean: 28.74 (SD = 23.14)
Mean: 17.83 (SD = 12.30)
BMI (body mass index)
Mean: 22.16 (SD = 3.56)
Mean: 22.01 (SD = 4.45)
Surgical Site infections (SSI) were monitored for both pre and post-implementation groups. In the pre-implementation groups, patients had a 50% chance of developing an SSI (n = 19) (Table 2). Conversely, in the post-implementation group, only 22.2% (n = 8) developed SSI, p = 0.017. We assessed the relationship between smoking, type of surgical closure, and diabetes mellitus (DM) and the development of SSI. The following developed SSI, 54.8% (n = 17) of smokers and 45.2% (n = 14) of non-smokers . Based on type of closure, 18.8% (n = 6) of patients with primary closure developed SSI compared to the group with reconstruction, where 50% (n = 42) developed SSI, p = 0.007. For DM, twelve (52.2%) patients who had preexisting DM developed post-op SSI compared to 29.4% (n = 15) of non-diabetics. The logistic regression analysis for post-op SSI indicated that, after controlling for DM, smoking status and type of surgical closure were statistically significant, X2(1, N = 74) = 19.037, p < 0.001. Patients without reconstruction after surgery were 80% less likely to develop SSI (B = −1.632, SE: 0.609, p = 0.007) and non-smokers are 75% less likely to develop post-op SSI (B = −1.442, SE: 0.561 p = 0.010).
At baseline, there was a significant difference between the mean LOS (days) of the pre-28.74 (SD = ± 23.14) and post-implementation groups 17.83 (SD = ± 12.31), t (72) = 2.51, p = 0.014. There was also a positive weak linear relationship between LOS and the age of patients (r (74) = 0.239, p = 0.04). As age increases, LOS tends to increase. Approximately 5.7% of the variability in LOS was explained by age. Smoking status did not significantly predict LOS, t (72) = 1.300, p = 0.198, after controlling for type of surgical closure. Type of closure significantly predicted LOS, t (72) = 3.721, p = 0.000, after controlling for smoking. Smoking status and type of surgical closure explained 18.8% of the variance of LOS.
MUST and SGA
Both MUST and SGA nutritional tools were used to assess for nutritional status of patients in the post-implementation group (n = 36). A total of 63.9% of patients in both the MUST and SGA (n = 23) groups have moderate (33.3%, n = 12) to high risk for malnutrition (30.6%, n = 11). Both nutritional tools demonstrated no statistical difference in terms of concordance in its ability to detect malnutrition (p = 0.999).
Significant malnutrition, which is multifactorial in nature and may be precipitated by symptoms of pain, compression, and obstruction due to tumors growth, exists in 35 to 50% of patients with head and neck cancers . Traditionally, BMI was used as a surrogate marker for nutritional status. However, in this study, the use of BMI status did not demonstrate similar findings. Instead, there was a significant correlation between malnutrition and using the MUST nutritional screening tool in detecting medium and high-risk groups (63.9% of patients). Among the participants only 14.9% (n = 11) were underweight and 67.6% (n = 50) were within the normal BMI ranges. Thus, assessment of their nutritional status was inaccurate when BMI was used. Similar findings were reported in several studies [1, 4, 5, 18, 24], where the use of conventional method of utilizing BMI was shown to be ineffective in the screening of individuals with malnutrition as detection rates were relatively low. In addition, the cut-off points for BMI are often arbitrary and based on young, healthy adults which is a misrepresentative for patients with a life-threatening condition such as cancer . Our analysis demonstrated that both MUST and SGA nutritional tools, reported similar findings where 63.9% (n = 23) of patients showed malnutrition before surgery. Thus, there was no difference in detection rates of malnutrition (p = 0.999). This was in concordance with other studies [1, 4]. In addition, MUST was identified as an effective measuring tool with high indexes for sensitivity, specificity and in concordance agreement with the standard Patient-Generated Subjective Global Assessment (PG-SGA) as the benchmark assessment tool [1, 3, 4, 5, 30, 31].
Malnutrition is a known contributing factor in the spiral effects of postoperative complications and mortality, particularly in patients with head and neck cancers [1, 5, 32]. Preoperative nutritional screening can detect malnutrition and facilitate early nutritional intervention which has demonstrated beneficial outcomes, i.e., significant reductions in postoperative complications and length of hospitalization stay [8, 9, 10, 26]. This study demonstrated similar results where nutritional screening and early nutritional interventions, significantly reduced postoperative SSI rates from 50% (n = 19) to 22.2% (n = 8) after the implementation of MUST. Diabetic mellitus has been associated with increased postoperative complications including mortality . However, this was not demonstrated in our cohort of participants as diabetic mellitus rates (44.4%) were only marginally significant (p = 0.053). Tobacco use is the primary risk factors for head and neck cancer . The study reported that tobacco use is associated with postoperative complications and may distinguish at risk patients. This was in agreement with our findings where more than half of our participants (63%), who are smokers developed postoperative SSI, p = 0.006. In terms of type of surgical closure, our study showed that patients with reconstruction were more likely to develop postoperative SSI. Similarly, this was reported in another study where reconstruction surgery was associated with increased risk of postoperative SSI, length of hospitalization stay (LOS), occurs in older patients who were likely to have neoadjuvant radiotherapy and methicillin-resistance staphylococcus aureus (MRSA) positive results [6, 11]. We did not review the MRSA status of the patients in this study. Most of our patients were radiation naïve, older and have longer LOS.
Significant reduction was noted on length of hospitalization stay between the pre-and post-implementation group, p = 0.0140. Thus, enhancing preoperative nutritional statues by early identification of nutritional status using the MUST have demonstrated good outcomes which is evidenced in our study. This is supported by several studies [1, 9, 13, 30, 33], where positive outcomes prediction associated with the use of MUST were demonstrated in terms of length of hospitalization stay, mortality, hospitalization cost and improved quality of life. In addition, it was observed that participants who were non-smokers and underwent primary surgical closure were related to decreased length of hospitalization stay. This can be attributed to shorter surgery time, extend of surgery and better wound healing in non-smokers . This study has demonstrated the effectiveness of preoperative nutritional screening and effects of early nutritional interventions in preventing postoperative SSI and decreasing the length of hospitalization stay.
Due to the availability of operating theaters and short timeframe to surgery date, some participants (n = 6) were not recruited as they were not unable to fulfil the criteria of at least 3 to 5 days of preoperative nutritional interventions. In addition, compliance to the prescribed nutritional supplements and additional alternative treatments/ supplements were based on patients’ reports after their agreement to comply. Direct observed compliance and close monitoring on supplement compliance can lessen the discrepancies for future projects. Although all patients were screened by our allied health professionals (AHP) before surgery, interventions (e.g., insertion of nasogastric tubes for dysphagia due to complications of cancer) might be untimely due to time constraints to surgery, thus the consumption of prescribed nutritional interventions, for the required period of 3 to 5 days, might be suboptimal.
Conclusion and Clinical Implications
This study found substantial support on implementation of MUST as a preoperative nutritional screening tool to assess the nutritional status of patients undergoing oncology resection for head and neck cancers. It has shown promising outcomes that prevalence of malnutrition can be influenced with the implementation of nutritional interventions when introduced at a timely phase. Closing the gap in nutrition screening and interventions for malnutrition can reduce long-term cost to both the patients and the healthcare system. This is applicable to other disciplines in oncology especially for patients who are undergoing concurrent chemoradiation, an adjuvant therapy, commonly required after surgery. Thus, it is paramount to continue monitoring for postoperative nutritional deficiency by the dieticians. System-wide screening for malnutrition is critical in the care of patients with cancer and translation of this knowledge will induce a culture of change in our nutritional care for patients. Our next step is to begin the process of introducing this screening tool to the various departments within the oncology setting for all newly diagnosed patients to be screened using the MUST nutritional screening tool. The study has given us some insights to risk identifiers such as smoking status and diabetics mellitus control, which may have an impact on postoperative complications besides malnutrition. Smoking cessation program and appropriate control of diabetes mellitus before surgery are options to explore for patient management. Future research focusing on other contribution factors, e.g., quality of life, cultural aspect on use of nutritional supplements and effects of comorbidities can be explored and a randomized clinical trial methodology can be used to further explored the effectiveness of the tool.
The authors would like to thank Dr. Julia Thompson for her guidance in this study.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
This study was conducted after approval from both the Duke University Institutional Review Board (DIRB) and the Quality Department Management (QDM) of the tertiary cancer center.
Verbal consent was obtained from all participants.
- 3.Bapen. (2003). The Malnutrition Universal Screening Tool. Retrieved from http://www.bapen.org.uk/pdfs/must/must_full.pdf
- 5.Borges NP, Silva DA, Cohen C, Filho PF, Medeiros FJ. Comparison of the nutritional diagnosis, obtained through different methods and indicators in patients with cancer. Nutr Hosp. 2009;24(1):51–5.Google Scholar
- 6.Davidson W, Isenring E, Brown T, Riddle B. Nutritional management of patients with head and neck cancers: integrating research into practice. Cancer Forum. 2006;30(3):183–7.Google Scholar
- 9.Falwee MN, Schilf A, Boufflers E, Cartier C, Bachmann P, Pressoir M, et al. Reduced infections with perioperative immunonutrition in head and neck cancer: exploratory results of a multicenter, prospective, randomized, double – blind study. Clin Nutr. 2014;33:776–84. https://doi.org/10.1016/j.clnu.2013.10.006.CrossRefGoogle Scholar
- 10.Felekis D, Eleftheriadou A, Papadakos G, Bosinakou I, Ferekidou E, Kandiloros D, et al. Effect of perioperative immuno-enhanced enteral nutrition on inflammatory response, nutritional status and outcomes in head and neck cancer patients undergoing major surgery. Nutr Cancer. 2010;62(8):1105–12. https://doi.org/10.1080/01635581.2010.494336.CrossRefPubMedGoogle Scholar
- 17.Leistra E, Eerenstein S, van Aken L, Jansen F, de van der Schueren M, Twisk J, et al. Effect of early individualized dietary counselling on weight loss, complications, and length of hospital stay in patients with head and neck cancer: A comparative study. Nutr Cancer. 2015;67(7):1093–103. https://doi.org/10.1016/s0261-5614(14)50405-0.CrossRefPubMedGoogle Scholar
- 20.Machiels JP, Lambrecht M, Hanin FX, Duprez T, Gregoire V, Schmitz S, et al. Advanced in the management of squamous cell carcinoma of the head and neck. F1000Prime Rep. 2014;6(44):1–10.Google Scholar
- 24.Rahman A, Wu T, Bricknell R, Muqtadir Z, Armstrong D. Malnutrition matters in Canadian hospitalized patients: Malnutrition risk in hospitalized patients in a tertiary care center using the malnutritional universal screening tool. Nutr Clin Pract. 2015;30(5):709–13. https://doi.org/10.1177/0884533615598954.CrossRefPubMedGoogle Scholar
- 26.Rowan N, Johnson J, Fratangelo C, Smith B, Kemerer P, Ferris R. Utility of a perioperative nutritional intervention on postoperative outcomes in high-risk head & neck cancer patients. Oral Oncol. 2016;54:42–6. https://doi.org/10.1016/j.oraloncology.2016.01.006.CrossRefPubMedGoogle Scholar
- 27.Senkal M, Zumtobel V, Bauer KH, Marpe B, Wolfram G, Frei A, et al. Outcome and cost-effectiveness of perioperative enteral immunonutrition in patients undergoing elective upper gastrointestinal tract surgery: a prospective randomized study. Arch Surg. 1999;134:1309–16. https://doi.org/10.1001/archsurg.134.12.1309.CrossRefPubMedGoogle Scholar
- 28.Stratton RJ, Hackston A, Longmore D, Dixon R, Price S, Stroud M, et al. Malnutrition in hospital outpatients and inpatients prevalence, concurrent validity and ease of use of the ‘malnutritional universal screening tool’ (MUST) for adults. Br J Nutr. 2004;92:799–808. https://doi.org/10.1079/bjn20041258.CrossRefPubMedGoogle Scholar
- 29.Tabachinick BG, Fidell LS. Using multivariate statistics. 5th ed. New York: Allyn and Bacon; 2007.Google Scholar
- 32.Watterson C, Fraser A, Banks M, Isenring E, Miller M, Silvester C, et al. Evidence based practice guidelines for the nutritional management of malnutrition in adult patients across the continuum of care. Nutr Diet. 2009;66:S1–S34. https://doi.org/10.1111/j.1747-0080.2009.01383.x.CrossRefGoogle Scholar
- 33.Zhong JX, Kang K, Shu XL. Effect of nutritional support on clinical outcomes in perioperative malnourished patients: a meta-analysis. Asia Pac J Clin Nurs. 2015;24(3):367–78.Google Scholar