Comparison of Nutrition Screening Tools and Calf Circumference in Estimating the Preoperative Prevalence of Malnutrition Among Patients with Aerodigestive Tract Cancers- A Prospective Observational Cohort Study

doi:10.21203/rs.3.rs-1316502/v1

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Research Article

Comparison of Nutrition Screening Tools and Calf Circumference in Estimating the Preoperative Prevalence of Malnutrition Among Patients with Aerodigestive Tract Cancers- A Prospective Observational Cohort Study

https://doi.org/10.21203/rs.3.rs-1316502/v1

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Purpose

There is paucity of data on the prevalence of malnutrition among cancer patients in India and a brief tool to identify the same would be an asset. Our aim was to evaluate two nutrition screening tools and calf circumference (CC) with the European Society for Clinical Nutrition and Metabolism (ESPEN) consensus guidelines for malnutrition among patients with head and neck(H&N) and gastrointestinal(GI) cancers.

Methods

Nutritional evaluation was performed preoperatively using Malnutrition Universal Screening Tool (MUST), Short Form of Mini Nutritional Assessment (MNA-SF) and Calf circumference (CC) in 206 patients. The diagnostic accuracy of these tools was compared with the ESPEN criteria for malnutrition. Patients evaluated were grouped as normal or malnourished. The incidence of infection, antibiotic days, antibiotic escalation and length of stay were compared among the groups. Clavien-Dindo score at discharge, 30-day readmission and mortality were also examined.

Results

28.6% were malnourished as per ESPEN criteria and 25.2% had CC less than the cut-off. With respect to ESPEN criteria, MUST and MNA-SF had 100% sensitivity and negative predictive value. CC had the highest specificity and positive predictive value for the total population (91.16%,75% respectively). The agreement between the tools was acceptable except in MNA-SF(MNA-SF-ESPEN κ = 0.228, MUST-ESPEN κ = 0.565, CC-ESPEN κ = 0.594). There was no difference in postoperative outcomes between the malnourished and normal.

Conclusion

Thus, more than a quarter of patients with H&N and GI cancers are malnourished preoperatively. As the best agreement between the screening tools was for MUST-ESPEN and CC-ESPEN, either of them can be used to identify malnutrition at admission

Malnutrition

Calf Circumference

Gastrointestinal Cancer

Sensitivity and Specificity

Malnutrition is prevalent among 20-80% of cancer patients and its origin is multi-factorial.[1, 2] Malnutrition encompasses both under-nourished patients with low BMI and/or weight loss, as well as, obese (BMI ≥ 25 kg/m²) where the loss of lean body mass is masked by adiposity and/or fluid retention.[3] Patients with upper aero-digestive tract and colorectal cancers are susceptible to malnutrition. Further, malnutrition is associated with postoperative morbidity[4] and length of hospital stay (LOS).[5, 6]

Several nutritional screening tools have been validated in oncology such as the Malnutrition Universal Screening Tool (MUST)[7] and the Short Form of Mini Nutritional Assessment (MNA-SF).[8] Calf-circumference (CC) is a pertinent marker in identifying under-nutrition among the elderly.[9–11] The rationale of our study was to evaluate the consistency of the three screening tools namely MNA-SF, MUST and CC in diagnosing malnutrition in cancer patients.

The primary objective of the study was to evaluate the diagnostic accuracy of the three nutritional tools against the European Society for Clinical Nutrition and Metabolism (ESPEN) consensus guidelines,[12] among patients with head and neck (H&N) and gastrointestinal (GI) cancers. We also observed the association of malnutrition with postoperative morbidity and LOS.

A prospective observational cohort study was conducted between September 2019 and November 2020 at Cancer Institute(WIA), Adyar, India after obtaining the approval from the institute ethics committee (IEC) (IEC 2019/Sept/01) for preoperative screening of cancer patients. The study was conducted in accordance to the Declaration of Helsinki of 1975, revised in 2000. A written informed consent was obtained from all the patients before the nutrition screening. The study was registered at Clinical Trial Registry-India (CTRI/2020/04/024733). All consecutive adult patients above the age of 18 years, with H & N or GI cancer scheduled for definitive surgeries were included. The exclusion criteria were 1. Patients having Poliomyelitis or lower limb edema 2. Patients for short procedures lasting less than three hours such as thyroidectomy or excision biopsies in the tongue or neck dissection.3. Patients for palliative or emergency procedures. Screening for malnutrition was performed using the nutrition tools (ESPEN, MNA-SF and MUST) and CC was measured in the immediate preoperative period (Fig. 1).

According to the ESPEN consensus, malnutrition was diagnosed when the patients met one of the following two options. Option 1 requires Body mass index (BMI) <18.5 kg/m² while the second option requires unintentional weight loss and reduced BMI or reduced fat free mass index.[12]

MNA-SF was designed especially for the elderly. It contains six questions as shown in Fig. 1. Each question is rated from 0 to 2 or 3 and the total score of MNA-SF is 14.[8]

MUST include the following parameters: BMI, unintentional weight loss and any acute disease which compromises nutritional intake for more than 5 days. The three parameters rated as 0, 1 or 2 are as follows: BMI >20 kg/m²=0, 18.5–20 kg/m²=1, <18.5 kg/m²=2; unintentional weight loss in the past 3–6 months <5%=0, 5–10%=1; any acute disease present would mean 2 points. Overall risk of malnutrition is assessed by adding all the points together.[7]

Calf Circumference (CC) is measured along the widest circumference of calf on either limb. Patients with CC< 26cm for women and CC<28cm for men were considered malnourished.[11] CC could be wider due to pedal edema or smaller due to atrophied lower limb in poliomyelitis.

All patients were observed daily until discharge. Information on any patient who was readmitted within 30 days was retrieved from their medical records. Socio-demographic (age, gender, comorbidities, prior treatment history, habits), anthropometric (height, weight and CC) and clinical details (pedal edema, hemoglobin, albumin, total white blood cell count, diagnosis, planned surgery, and date of surgery) were collected. Weight (in kg) was measured using a digital weighing machine and the height (in cm) using a stadiometer. The postoperative outcome parameters are defined in Supplementary Table 1.

With an expected prevalence of malnutrition ranging from 20-52% [13], the estimated sample size with 90% power and 5% precision considering prevalence of malnutrition to be 20% in our population and the estimated proportion being 0.25, was calculated as 203.[14]

The study sample was divided into three subsets namely H&N, Upper GI cancers and Lower GI cancers. Continuous variables were reported as mean (SD) while categorical variables were reported as frequency (percentage). MUST, MNA-SF were first classified into three categories namely malnourished, at risk and normal, which was further reorganised as normal and malnourished. Patients who were malnourished and at risk of it were included in the malnourished group for ease of understanding. CC was also classified into two groups. MNA-SF, MUST and CC versus ESPEN guidelines of malnutrition(reference standard) was evaluated by the estimation of sensitivity, specificity and their positive predictive (PPV) and negative predictive values (NPV).The concordance between the reference standard and each of the three tools was analysed using Cohen’s κ (Kappa) statistic and the Shrout classification was used to interpret the κ value as follows: 0–0.1, virtually nil ; 0.11–0.4, slight; 0.41–0.6, fair; 0.61–0.8, moderate; and 0.81–1, substantial agreement.[15, 16] Student t-test was used for comparison of means and Pearson’s Chi-square test for evaluation of frequency distribution. P value≤ 0.05 was considered significant. Clavien Dindo scores of patients were further classified into two groups as scores less than 3 (minor complications) and greater than or equal to 3 (major complications) to analyse postoperative complications using the different tools. The tools were evaluated using the MedCalc software, diagnostic test evaluation calculator (https://www.medcalc.org/calc/diagnostic_test.php) and Statistical Package for Social Sciences, SPSS Version 26.0(IBM, Armonk, NY, USA).

Patient Characteristics: Of the 251 patients screened, 8 cases were inoperable, 37 patients had incomplete data, and thus 45 patients were excluded. Seventy-seven (37.4%) women were included in the analysis. According to the reference standard, 29.5% of men and 27% of women were malnourished. The prevalence of malnutrition in the total population was 28.6%, and was highest in patients with upper GI cancer. Fifty-two (25.2%) had CC less than the cut-off (<26cm for women and <28cm for men), while with MUST and MNA-SF the patients at moderate/high risk for malnutrition were 59(28.6%) and 56(27.1%) respectively. The preoperative and postoperative characteristics of all 206 patients have been described in Tables 1 and 2 There were differences in the consistencies between the three tools with respect to the reference tool. All tools exhibited statistically significant association with malnutrition (P=0.000). MUST and MNA-SF had 100% sensitivity and NPV for the overall population and for the three subsets of populations namely H&N, upper and lower GI cancers. Specificity and PPV of MNA-SF for H&N:34.38%,27.5%;Upper GI 28.5,50.8;lower GI 39%,32.4% while that of MUST for H&N were 72%,47%;for upper GI 69.6%;70.4% and lower GI 65.8%,46% respectively.CC had the lowest sensitivity and NPV respectively for all patients and for the three subgroups (H&N: 81.25%, 95.08%, upper GI:61.2%,76.4%, and lower GI:58.3%,88.1% respectively). On the contrary, CC had the highest specificity and PPV for the total population and for the three subgroups (specificity for H&N:90.6%, upper GI:92.8%, lower GI 90.2%) (PPV for H&N: 68.4%, upper GI: 83.3%, lower GI: 63.6%). CC had the highest consistency in the total population (κ = 0.594), in H&N (κ = 0.672) and lower GI population (κ = 0.501). MUST had the highest consistency in the upper GI population (κ = 0.655). The sensitivity, specificity and the predictive values of the screening tools are in Table 3.

There was no difference in mean LOS and mean antibiotic days between the malnourished and normally nourished groups. There were no differences in antibiotic escalation or occurrence of infection between the normal and malnourished patients using the screening tools (Fig. 2a, 2b, 3a, 3b). Number of malnourished patients, with major complications, were 50 (71.4%) as defined by MNA-SF, 34 (48.5%) using MUST and 21 (30%) using CC. There was no difference in the postoperative complications between the malnourished and the normal patients using the ESPEN guidelines (P = 0.337), MNA-SF (P = 0.302), MUST (P = 0.693) and CC (P = 0.259).

This prospective, observational cohort study on preoperative nutritional assessment of patients with aerodigestive cancers identified that MUST and MNA-SF had the highest sensitivity and the CC had the best specificity with respect to the ESPEN criteria. CC had the best consistency in the H&N and lower GI group while MUST was better in the upper GI patients. The strength of agreement with ESPEN was fair for both MUST and CC.A study comparing MNA-SF, MUST and Nutritional Risk Screening-2002 (NRS) against the ESPEN criteria in geriatric (age≥70 years) found MUST to have the highest sensitivity (94.1%) and specificity (76.5%) among all GI cancers.[13] The magnitude of agreement was comparable to our study (κ = 0.565 versus κ = 0.530). All tools had a similar consistency (κ = 0.414-0.469) in gastric cancers, however in the colorectal group, MUST had the highest agreement (κ = 0.576). In a recent study comparing six nutritional tools among 140 patients undergoing surgery for gastric cancer, the MNA-SF emerged as the most diagnostic of malnutrition with a specificity of 86% and sensitivity of 84%.[17] Between the tools MNA-SF exhibited the strongest association, accuracy and moderate agreement (κ = 0.59). The authors attributed the result to using the free fatty mass index (FFMI), an optional component of the ESPEN criteria, in their analysis. In a large study of 1146 hospitalised patients, MUST was found to have high sensitivity (96%) and specificity (96%) with moderate to substantial agreement (κ = 0.777-0.843), using the ESPEN criteria as the reference standard.[18] Conversely, a study among institutionalized elderly, found MUST to have a poor predictive value for nutritional risk and mortality compared to MNA and MNA-SF.[19]

CC has been explored as surrogate marker for sarcopenia and malnutrition in many studies.[10, 11, 20] An increased catabolic state causes sarcopenia which in turn leads to poorer outcomes.[21, 22] The cut-off values for CC vary depending on the study sample. Among elderly subjects in rural India, CC at cut-off of 26.5 cm, was used to detect malnutrition and correlated well with BMI (r = 0.70).[10] In a Japanese study among 1,164 hospitalized, elderly, adults CC cut-off values ≤ 26 cm for women and ≤ 28 cm for men were used in diagnosing malnutrition using the ESPEN criteria with very similar sensitivity and specificity.[11] Further these values correlated with the finding in these patients of a decreased muscle mass using dual energy absorptiometry. This justifies our choice of the same gender specific cut-off values. The number of false positive cases as per the definition of CC was only 13(6.3%) as compared to 97(47%) for MNA-SF and 45(21.8%) for MUST and hence the higher PPV for CC. This reinforces the fact that predictive values have more relevance in a clinical scenario.[23] 52(25%) of our patients had low CC of which 22(42%) patients suffered from upper GI cancer,19 (36%) had H&N cancer and 11(5.3%) had lower GI cancers. Major brunt of malnutrition was identified in the upper GI cancers with loss of muscle mass and cachexia. CC being very specific with a high PPV, can be an effective tool to rule out malnutrition.

The prevalence of malnutrition was 25-28% in our study population. An Indian study, involving H&N cancers, reported a prevalence of 76.9%.[24] Their sample size however was very small. Ye et al estimated the prevalence to be 20% in elderly patients with GI cancers.[13] This is similar to a study in gastric cancer patients wherein, prevalence of malnutrition was 20.71% according to ESPEN criteria.[17] The prevalence of malnutrition was greater in our study and can be attributed to the inclusion of upper aero- digestive cancers in our sample. Also many patients in our study had prior oncological treatment which resulted in weight loss due to several nutrition impact symptoms.[25, 26] Despite this, only 46(22.3%) of our patients reported weight loss which is lower than that of the Chinese study [13],74 (29%). This could be because 34(16.5%) of our patients were unaware of their weight loss and 71(34.5%) denied any weight loss.

The prevalence of malnutrition calculated in the overall population using three different screening tools varied because each tool is unique. ESPEN consensus guidelines have been used as a reference standard for assessment of screening tools.[13, 17] We chose ESPEN as the reference standard because it is simple, clear, and applicable to both undernourished and the obese.[12] There’s a tilt in our population towards the low BMI, (50(24.2%)), than the obese (5(2.4%). Majority of our patients (151(73.3%)) had a BMI between 18.5-29.9 Kg/m² and some of them also experienced weight loss, which was higher in the upper GI group 24(15.8%) than the H&N 22(14.5%) or lower GI 17(11.2%). Four patients (2%) suffering from upper GI cancer had been acutely ill amounting to no volitional intake for more than five days. Any patient with an acute disease resulting in almost no food intake for > five days will lose 5-10% of their weight and hence is given a score of two in MUST.[7] Since percentage weight loss was highest in the upper GI group, it may have reflected on the higher consistency of the MUST in that population.

Mean LOS and mean antibiotic days showed no difference between the malnourished and normal group in our study. A recent study in patients with GI cancer undergoing surgery found that malnutrition increases LOS by 2-11.1 days.[27] Another study, among 47 elderly patients undergoing cancer surgery, identified significant differences in the LOS (17.10(10.2) versus 29.1(10.1)) and mean antibiotic days (9.30(4.1) versus 14.22(3.6)) between the normal and the malnourished respectively.[6] LOS is influenced by multiple preoperative, intraoperative and postoperative factors.[28] The mean antibiotic days or its escalation were no different between the two groups because the rates of infection and postoperative complications were similar in both. All our patients were advised a protein enriched diet and simple exercises in the preoperative period, which might have influenced the results.

There is paucity of data on the systematic nutritional screening of cancer patients in India. The time constraints of a busy outpatient department cannot be overemphasized and, a brief tool which can accurately identify a patient at risk is the need of the hour. To the best of our knowledge, this is the first study comparing CC with standard nutritional screening tools in identifying malnutrition among cancer patients in the preoperative period. The generalizability of our study is limited to oncological patients in the Indian subcontinent. All the tools are non-invasive, take less than five minutes and have both subjective and objective components thus avoiding errors. CC can be performed even in the supine posture by non-medical staff. However, this study has certain limitations. The data was from a single center and specific to aerodigestive tract cancers. The nutritional evaluation was performed just prior to surgery and may have underestimated the true prevalence of malnutrition. Patients had ample opportunity to improve their nutritional status before surgery. Further the study lacked the power to detect a significant difference in the secondary objectives between the normal and malnourished groups. Though low CC has been found to be an independent risk factor in predicting mortality, [29] we could not analyse it because of the few numbers. Further research in defining CC values specific to our population is needed. A recent study emphasizes the use of BMI adjusted CC values to remove the confounding effect of adiposity.[30]

More than a quarter of the patients with H&N and GI cancers are malnourished preoperatively. As the best agreement between the screening tools was for MUST-ESPEN and CC-ESPEN, either of them can be used to identify malnutrition in the out-patient department to facilitate early nutritional intervention.

Acknowledgement: We sincerely thank Dr. Swaminathan Rajaram, Professor, Department of Tumor Registry and Biostatistics for helping us with the statistics and calculation of the sample size

Funding: The authors declare that no funds, grants, or other supports were received during the preparation of this manuscript.

Disclosure statement/ Competing interests: The authors have no relevant financial or non-financial interests to disclose.

Author Contributions: All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Dr. Nivedhyaa, Dr. Meenakshi ,Dr. Thendral ,Dr. Aishwarya and Dr. Ajit. The first draft of the manuscript was written by Dr. Nivedhyaa ,Dr. Meenakshi and Dr. Kalpana . All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript

Ethics Approval: The ethics approval was obtained from the institute ethics committee (IEC) (IEC 2019/Sept/01).The study was performed in accordance to the Declaration of Helsinki of 1975, revised in 2000.

Availability of data and material: We have full control of data and we agree to the fact that the journal or reviewers can request to view the data.Data can be made available upon request to the corresponding author

Code Availability: Not applicable.

Consent to Participate: Informed consent was obtained from all individual participants included in the study.

Consent for publication: Not applicable. Manuscript does not contain any individual s images or videos.

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Table No 1: Patient preoperative characteristics

				^aH&N 80(38.9%)		^bUGI 73(35.4%)		^cLGI 53(25.7%)
	Total N=206(100)	Not malnourished 147(71.4%)	^dMalnourished 59(28.6%)	^aH&N 64(80%)	^a,dH&N 16(20%)	^bUGI 42(57.5%)	^b,dUGI 31(42.5%)	^cLGI 41(77%)	^c,dLGI 12(23%)
Age (years)	54.7(11)	55.6(11.5)	52.4(10.6)	52.6(11.6)	52.6(12.3)	58.4(9.5)	52.1(7.6)	57.2(12.2)	53.5(15.1)
^eBMI (kg/m²⁾	22.1(5)	24.2(4.35)	16.9(1.6)	24.6(5.26)	16.6(1.2)	24.03(2.8)	16.9(1.62)	24(4.1)	17.28(2.05)
Albumin(g%)	3.51(0.56)	3.5(0.5)	3.3(0.6)	3.7(0.54)	3.5(0.5)	3.4(0.5)	3.2(0.57)	3.5(0.5)	3.01(0.74)
Haemoglobin(g%)	11.2(2.2)	11.4(2.3)	10.7(1.9)	13(1.8)	11.7(1.6)	10.5(1.9)	10.8(1.5)	9.9(1.9)	9.2(2.3)
Calf Circumference(cm)	30.6(4.3)	32(4.06)	27(2.5)	32.8(4.5)	27.2(2.6)	31.4(3.2)	27.3(2.1)	31.3(3.9)	26.6(3.49)
Radiotherapy^f	42(20.4%)	29(19.7)	13(22)	12(18.8)	3(18.8)	3(7)	4(12.9)	14(34.1)	4(33.3)
Chemotherapy^f	73(35)	48(32.7)	25(42.4)	10(15.6)	5(31)	25(59.5)	18(58)	13(31.7)	4(33.3)
MNA-SF^g	9.1(2.6)	10.2(2.05)	6.4(1.71)	10.5(1.77)	6.8(1.9)	9.8(2.2)	6.1(1.79)	10.2(2.18)	6.75(1.05)
MUST^h	0.96(1.13)	0.35(0.5)	2.47(0.7)	0.31(0.53)	2.38(0.6)	0.38(0.6)	2.58(0.76)	0.3(0.5)	2.3(0.65)

^aHead and Neck, ^bUpper Gastrointestinal, ^clower gastrointestinal,^dMalnourished according to European Society of Enteral and Parenteral Nutrition consensus ^eBody Mass Index, ^fvariables are presented as n (%) and while others as Mean(Standard Deviation). ^gMini Nutrition Assessment Short Form, ^hMalnutrition Universal Screening tool

Table No 2: Enumeration of the postoperative outcomes in 206 patients

	N=206	^aMalnourished 59(28.6%)	Not malnourished 147(71.4%)	Head and Neck 80(38.9%)	Upper GI^b 73(35.4%)	Lower GI^b 53(25.7%)
Clavien Dindo^c 0	64(31)	20(34)	44(30)	24(30)	23(31.5)	17(32.1)
1	31(15)	5(8)	26(18)	16(20)	10(14)	5(9)
2	41(20)	11(19)	30(20.4)	24(30)	14(19)	3(6)
3a/3b	47(23)/18(9)	11(19)/10(17)	36(24.5)/8(5)	9(11)/7(9)	17(23)/5(7)	21(40)/6(11)
4	2(1)	0	2(1.4)	0	2(2.8)	0
5	3(1.5)	2(3)	1(0.7)	0	2(2.7)	1(1.9)
SSI ^c,d	62(30)	17(29)	45(31)	35(44)	15(20.5)	12(23)
Wound dehiscence^c	49(23.8)	15(25)	34(23)	11(14)	15(20.5)	23(43)
Pneumonia^c	33(16)	5(8.5)	28(19)	10(12.5)	18(25)	5(9.4)
UTI ^c,e	4(1.9)	1(1.7)	3(2)	0	2(2.7)	2(3.8)
Deep Seated Infection^c	16(7.8)	5(8.5)	11(7.5)	6(7.5)	9(12.3)	1(1.9)
Bacteremia^c	4(1.9)	2(3.4)	2(1.4)	0	3(4.1)	1(1.9)
Antibiotic Escalation^c	75(36)	22(37)	53(36)	32(40)	28(39)	15(28)
Antibiotic days	7.09(5.7)	7.08(5.92)	7.1(5.67)	8.9(6.7)	6.75(4.9)	4.7(4.06)
LOS^f(days)	15.6(10.1)	16.7(11.3)	15.22(9.6)	16.8(10.8)	15.05(9.02)	14.5(10.4)
30-day Readmission^c	4(1.9)	3(5.1)	1(0.7)	3(3.8)	1(1.4)	0
30-day mortality^c	5(2.4)	3(5.1)	2(1.4)	0	4(5.5)	1(1.9)

^aMalnourished according to European Society of Enteral and Parenteral Nutrition consensus,^bGastrointestinal, ^cvariables are presented as n(%) while LOS and antibiotic days as Mean(Standard Deviation),^dSurgical Site Infection, ^eUrinary Tract Infection, ^flength of hospital stay.

Table No 3: Statistical evaluation of the malnutrition screening tools compared with the reference standard of the European Society for Clinical Nutrition and Metabolism (ESPEN) for malnutrition

	N=206
	^aMNA-SF	^bMUST	^cCC
Sensitivity	100%	100%	66.10%
Specificity	34.01%	69.39%	91.16%
Positive Predictive Value	37.82%	56.7%	75%
Negative predictive value	100%	100%	87.01%
Accuracy	52.91%	78.16%	83.98%
^dκ value(consistency)	0.228	0.565	0.594
Percentage Agreement	52%	78%	83%

^aMini Nutrition Assessment Short Form, ^bMalnutrition Universal Screening tool , ^cCalf Circumference, ^dCohen’s Kappa

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Editorial decision: Major Revisions Needed
29 Mar, 2022
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Reviewers invited by journal
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Editor assigned by journal
07 Feb, 2022
First submitted to journal
31 Jan, 2022

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Comparison of Nutrition Screening Tools and Calf Circumference in Estimating the Preoperative Prevalence of Malnutrition Among Patients with Aerodigestive Tract Cancers- A Prospective Observational Cohort Study

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