Nutritional Surveillance from Surgery to Post-Radiotherapy in Oral Cavity Cancer: A Prospective Longitudinal Study

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This prospective longitudinal study aimed to trace the nutritional progression of these patients using a structured surveillance framework and to examine how key nutritional indicators influence clinical outcomes. Methods The study enrolled 100 individuals with histologically confirmed oral cavity cancer, all of whom were scheduled for surgical resection followed by radiotherapy. Nutritional evaluations—including bioelectrical impedance analysis (BIA) for body composition, handgrip strength (HGS), serum albumin, and dietary intake assessments—were conducted at five critical visits: pre-surgery (V0), post-surgery (V1), before radiotherapy (V2), end of radiotherapy (V3), and one-month post-radiotherapy (V4). Outcome measures included length of hospital stay (LOHS), mucositis severity, hospital re-admissions, and mortality. Results Significant declines were noted in body weight, body mass index (BMI), fat mass, and HGS across treatment phases (p < 0.01). A weight loss greater than 5% was associated with a higher prevalence of Grade III/IV mucositis (p < 0.05). Reduced muscle mass correlated with longer hospital stays, while preoperative hypoalbuminemia (< 3.5 g/dL) was significantly linked to increased mortality (p = 0.022) and readmissions (p = 0.007). No significant association was found between albumin and mucositis severity. Conclusion This study demonstrates a clear link between nutritional deterioration and adverse clinical outcomes in oral cancer patients. Regular, multi-dimensional nutritional monitoring is essential, and early individualized interventions may improve treatment tolerance and patient recovery. Oral cavity cancer nutritional status sarcopenia handgrip strength albumin radiotherapy Figures Figure 1 Introduction Oral cavity cancer is one of the most common malignancies of the head and neck, with a rising global burden and particular significance in low- and middle-income countries due to prevalent lifestyle and environmental risk factors [1,2]. Despite improvements in surgical and radiotherapeutic techniques, the overall five-year survival rate remains approximately 50%, and patients often face substantial morbidity throughout the course of treatment [2]. The disease itself and its treatment modalities—primarily surgery followed by radiotherapy (RT)—result in a range of nutrition-impact symptoms, including mucositis, dysgeusia, xerostomia, dysphagia, and pain, all of which impair oral intake and increase the risk of unintentional weight loss [3,4]. Studies have shown that 25–50% of patients with head and neck cancer (HNC) experience reduced dietary intake before initiating treatment, with most losing over 5% of their body weight even before therapy begins, and some losing up to 10% during the treatment course [5,6]. Malnutrition in this group has been linked to poor treatment tolerance, reduced therapy completion rates, diminished quality of life, increased hospitalization costs, and adverse survival outcomes [7,8]. Consequently, early identification of malnutrition and repeated nutritional assessments during treatment are critical to optimizing patient outcomes. While nutritional interventions are known to support dietary intake and recovery in patients undergoing surgery and chemo-radiation [9,10], current literature lacks comprehensive, longitudinal data that evaluates multiple nutritional domains—including anthropometry, body composition, muscle function, and biomarkers—throughout the entire treatment trajectory. The present study aims to address this gap by mapping nutritional trends over time and exploring the association between key nutritional indicators and clinical outcomes, including length of hospital stay, readmissions, radiotherapy compliance, and mortality in oral cavity cancer patients. Methods Study Design and Participants This prospective observational study was conducted at HCG Cancer Hospitals, Bengaluru, between March and December 2024. Adult patients (≥ 18 years) with a histologically confirmed diagnosis of oral cavity cancer who were scheduled for surgical treatment with curative intent were eligible for inclusion. Participants were required to provide written informed consent and be capable of effective communication. Exclusion criteria included concurrent or active malignancies other than oral cancer, evidence of metastasis, and inability to undergo BIA such as patients with pacemakers or those unable to stand unaided. Nutritional Assessment Time Points Participants underwent five standardized assessments throughout their treatment course: V0 : Within three days before surgery (preoperative) V1 : Seven days post-surgery V2 : One day before radiotherapy (RT) initiation V3 : At the completion of RT V4 : One month after RT At each of these time-points, comprehensive nutritional assessments were performed, including body composition analysis using BIA (Bodystat 1500), 24-hour dietary recall, HGS, and serum albumin (V0 only). Anthropometry and Body Composition Anthropometric parameters included body weight (kg), body mass index (BMI, kg/m²), and percentage weight loss from baseline. BMI was categorized based on WHO classifications: underweight (< 18.5), normal weight (18.5–24.9), pre-obese (25.0–29.9), and obese (≥ 30) [11]. Body composition, fat mass (%) and muscle mass (%), was evaluated at each time point using BIA, a validated non-invasive method for estimating body compartments in clinical populations [13]. Nutrition Screening and Laboratory Assessment Nutritional risk was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA), which classifies patients into well-nourished (A), moderately malnourished (B), and severely malnourished (C) [12]. Preoperative serum albumin levels were measured and categorized as normal (≥ 3.5 g/dL) or hypoalbuminemic (< 3.5 g/dL), based on standard clinical cut-offs [14]. Functional Muscle Assessment HGS was measured using an electronic dynamometer (EH101, Camry, China) in a seated position. The protocol involved testing the dominant and non-dominant hands followed by a one-minute rest, with the highest value used for analysis. Dynapenia was defined per EWGSOP guidelines: <30 kg for men and < 20 kg for women [15,16]. Treatment Details All patients underwent surgical resection followed by intensity-modulated radiotherapy (IMRT), with or without chemotherapy. Radiotherapy typically commenced within 3–4 weeks of surgery. Clinical and Outcome Measures Key clinical parameters recorded included date of surgery, discharge date, readmission within 30 days, and RT details (planned vs. actual doses, start/end dates). Mucositis was graded based on Radiation Therapy Oncology Group (RTOG) criteria from Grade 1 (mild) to Grade 4 (severe) [18]. Length of hospital stay (LOHS) was defined as days from postoperative day one to discharge. RT compliance was assessed by comparing actual treatment duration against the ideal duration [17]. Consent to Participate This study was conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration. Ethical approval for this observational trial was obtained from the Institutional Review Board of HCG Cancer Hospitals, Bengaluru. Written informed consent was obtained from all individual participants included in the study. Statistical Analysis Descriptive statistics were used to summarize demographic, nutritional, and clinical variables. Continuous data were expressed as mean ± standard deviation (SD), and categorical data as frequencies and percentages. Relationships between nutritional variables and clinical outcomes were evaluated using linear and logistic regression models. A p-value <0.05 was considered statistically significant. Analyses were conducted using SPSS version 11.0 (SPSS Inc., Chicago, IL, USA). Results Patient Demographics and Clinical Characteristics Table 1 provides a summary of patient demographics and baseline clinical characteristics. The mean age of the study population was 52.1 ± 11.7 years, ranging from 26 to 70 years. The cohort was predominantly male (86%). The tongue and buccal mucosa were the most commonly affected sub-sites, each accounting for 32% of cases. Most patients (72%) presented with advanced-stage disease (Stage III or IV). Comparative Analysis Based on Age and Tumor Stage A comparative evaluation of key nutritional and clinical parameters across age groups (<50 vs. ≥50 years) and disease stage (early vs. advanced) is shown in Table 2. While weight and HGS were significantly lower in the advanced-stage group (p < 0.05), no significant differences were observed in BMI, fat mass, or muscle mass. Younger patients (<50 years) exhibited similar nutritional profiles to older individuals. Longitudinal Changes in Nutritional Parameters Table 3 and figure 1 outlines the progression of nutritional indicators across the five study time points. Statistically significant reductions (p < 0.01) were noted in weight, BMI, fat mass, and HGS from the preoperative phase (V0) through the completion of radiotherapy (V3), with partial recovery by the one-month follow-up (V4). Body weight decreased from 67.10 ± 13.02 kg at V0 to 61.32 ± 11.52 kg at V3, with a modest increase to 62.16 ± 11.42 kg at V4. BMI declined from 24.46 ± 4.28 kg/m² at baseline to 21.90 ± 4.91 kg/m² at V3. Fat mass (%) dropped progressively from 21.43 ± 5.31% to 16.57 ± 5.06% by V4. Muscle mass (%) showed a postoperative increase at V1, followed by a decline during radiotherapy (V3), and a slight rebound at V4. HGS declined steadily, from 20.34 ± 4.64 kg at baseline to 17.27 ± 4.76 kg at V3, with some recovery at V4 (18.48 ± 4.36 kg). A comparative analysis of nutritional decline between the surgical (V0→V1) and RT (V2→V3) phases revealed statistically significant changes across all measured parameters (p < 0.001) (table 4). Post-surgery, a greater reduction was observed in handgrip strength (mean = 2.33 kg) and body weight (mean = 1.95 kg), suggesting acute postoperative catabolism and reduced intake. In contrast, the RT phase was associated with more pronounced declines in BMI (mean = 0.79 kg/m²), fat mass (mean = 1.93%), and muscle mass (mean = 1.62%), indicating sustained nutritional deterioration. Notably, muscle mass showed a increase immediately post-surgery (mean = –1.11%), possibly due to fluid redistribution or early rehabilitation effects, but declined sharply during radiotherapy. Relationship Between Weight Loss and Mucositis As shown in Table 5, patients with more than 5% weight loss were significantly more likely to develop higher grades of mucositis. Specifically, 26% of these individuals experienced Grade III mucositis and 19% developed Grade IV by the end of radiotherapy (p < 0.05), suggesting a strong link between weight loss and RT-induced mucosal toxicity. Muscle Mass and Clinical Outcomes Low muscle mass was significantly associated with increased length of hospital stay (LOHS), with a mean duration of 10.2 ± 1.9 days compared to 9.4 ± 2.1 days in patients with higher muscle mass (p < 0.05). However, no statistically significant association was found between muscle mass and mortality, severe mucositis, or 30-day readmission (table 5). Serum Albumin and Mortality Preoperative hypoalbuminemia (<3.5 g/dL) was significantly correlated with higher mortality (p = 0.022). Among the 12 patients with low albumin, only 58.3% survived, compared to 87.5% survival in the normal albumin group (n = 88). (Table 6) Albumin and Mucositis Severity No significant relationship was observed between serum albumin levels and mucositis severity (p = 0.568; table 6). Although the distribution of Grade III mucositis was similar in both groups, a smaller percentage of hypoalbuminemic patients developed Grade IV mucositis. Albumin and Readmission Rates Unplanned 30-day hospital readmissions were significantly more frequent in patients with hypoalbuminemia (50%) than in those with normal albumin levels (13.6%) (p = 0.007; table 6), suggesting that low preoperative albumin is a reliable predictor of early readmission risk. Discussion This prospective longitudinal study provides a comprehensive evaluation of nutritional status in patients undergoing curative treatment for oral cavity cancer. By assessing parameters such as body composition, muscle strength, serum albumin, and dietary intake at five time points, we offer valuable insight into the progression of malnutrition and its relationship with treatment outcomes. Our findings confirm that significant nutritional deterioration occurs throughout the surgical and radiotherapy phases, with partial recovery noted only in the post-treatment period. A mean weight loss of nearly 5 kg was observed from baseline (V0) to one month after radiotherapy (V4), consistent with patterns reported in earlier studies among head and neck cancer cohorts [19,20]. Early weight loss was primarily attributed to reductions in fat mass, whereas the later stages involved concurrent loss of both fat and muscle mass. These observations align with previous longitudinal studies that highlight the compounded effects of multimodal therapy on body composition [20,21]. Muscle depletion, in particular, appeared to be linked with clinical recovery, as patients with lower muscle mass had significantly longer hospital stays and higher readmission rates, suggesting its prognostic relevance in surgical oncology. The phase-wise comparison of nutritional status highlights distinct patterns of deterioration during treatment. While the immediate postoperative period was marked by significant loss in functional capacity, reflected by reduced handgrip strength and weight, the RT phase contributed more substantially to losses in body composition, especially fat and muscle mass. This trend is consistent with previous literature [22] describing radiotherapy-associated anorexia, mucosal toxicity, and systemic inflammation as key contributors to progressive malnutrition. The sharp decline in muscle mass during radiotherapy, despite relative preservation post-surgery, emphasizes the need for targeted interventions such as high-protein supplementation and resistance-preserving strategies during this phase. These findings reinforce the importance of tailoring nutrition care not just to treatment modality, but to specific treatment windows, to mitigate compounded nutritional risk. Our results also support prior literature showing that sarcopenia negatively impacts clinical outcomes in cancer populations. Filgrad et al. demonstrated that patients with post-radiotherapy sarcopenia had significantly lower survival rates, underscoring the long-term implications of muscle loss [23]. Similarly, studies using BIA have established its utility in quantifying sarcopenia and tracking nutritional trends in head and neck cancer patients [24]. A recent meta-analysis also reinforced that low muscle mass is associated with increased toxicity, prolonged hospital stay, and poor overall survival in this population [25]. Weight loss was significantly associated with higher grades of mucositis. In our cohort, 45% of patients with >5% weight loss developed Grade III or IV mucositis by V3, comparable to data from previous reports linking nutritional decline to worsening mucosal toxicity [26]. The underlying mechanism is likely multifactorial, involving poor oral intake due to dysphagia, mucosal pain, taste changes, and systemic inflammation—all of which can amplify nutritional deficits and compromise treatment compliance [25,27]. Advanced tumor stage was also associated with more pronounced nutritional decline, particularly in terms of weight and functional muscle strength. These findings suggest that tumor burden, in addition to treatment toxicity, contributes to energy imbalance and catabolism, which cumulatively increases the risk of malnutrition and sarcopenia. Serum albumin emerged as a significant predictor of both mortality and 30-day hospital readmissions. Patients with preoperative hypoalbuminemia (<3.5 g/dL) had notably poorer survival and were more likely to require unplanned readmissions following surgery. This finding is supported by studies in gastrointestinal, and head and neck cancers, where low albumin levels have consistently been associated with adverse outcomes [28–29]. Although albumin is not a direct marker of nutritional status, its role as a surrogate for systemic inflammation and metabolic stress makes it a valuable tool in perioperative risk stratification [29,30]. Notably, we found no significant association between albumin levels and mucositis severity, reinforcing the need for multimodal nutritional markers when evaluating treatment toxicity. While albumin alone may not predict local toxicities, it does reflect broader systemic risks such as infection, healing delays, and complications that can influence hospital utilization and recovery trajectories. A major strength of this study lies in its longitudinal design and use of multiple nutritional indicators at defined clinical intervals. This approach allowed for the tracking of dynamic changes in nutritional status and their correlations with clinically meaningful endpoints. Our integration of objective (BIA), functional (HGS), and biochemical (albumin) assessments offers a robust framework for nutritional surveillance in oral oncology. However, certain limitations must be acknowledged. This was a single-center study with a limited sample size, which may affect generalizability. The accuracy of BIA measurements may vary based on hydration status and timing, although standardized protocols were followed. The study also did not include markers of inflammation such as C-reactive protein, which could have provided additional insight into the role of systemic stress. Lastly, the follow-up period was relatively short, limiting our ability to evaluate long-term nutritional recovery and survival outcomes. Conclusion This study highlights the profound and progressive nature of nutritional decline in patients undergoing multimodal treatment for oral cavity cancer. Significant reductions in weight, fat mass, muscle strength, and serum albumin were observed over time, particularly during the radiotherapy phase. These changes were strongly associated with adverse clinical outcomes, including prolonged hospital stay, severe mucositis, increased postoperative readmissions, and mortality. Among the nutritional indicators assessed, low muscle mass and hypoalbuminemia emerged as important predictors of poor treatment tolerance and clinical recovery. The findings reinforce the need for early identification of at-risk individuals and emphasize the value of implementing structured, multimodal nutritional surveillance throughout the treatment continuum. Integrating personalized nutritional interventions into multidisciplinary cancer care protocols may enhance treatment compliance, reduce complications, and improve overall patient outcomes. Declarations Acknowledgments We sincerely thank all the study participants for their cooperation and commitment throughout the study period. We also acknowledge the dedicated efforts of the clinical nutrition and surgical and radiation oncology staff at HCG Cancer Hospitals, Bengaluru, for their invaluable support in data collection and patient follow-up. Competing Interests The authors have no relevant financial or non‑financial interests to disclose. Funding The authors declare that no funds, grants, or other support were received during the preparation or conduct of this study. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Esther Sathiaraj, Kamar Afshan, Shivani Sharma and Sruthi R. 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Cancer Manag Res . 2021;13:2131–40. doi:10.2147/CMAR.S303488 Tables Table 1: Patient Characteristics Characteristic Number of Patients (%) / Mean ± SD Sex Male Female 86 (86%) 14 (14%) Age 50 47 (47%) 53 (53%) Height (cm) 165 ± 7.8 Body Weight (kg) 67.1 ± 13.0 BMI (kg/m²) 24.5 ± 4.3 Fat Mass (%) 21.4 ± 5.3 Muscle Mass (%) 26.5 ± 4.0 HGS (kg) 20.3 ± 4.6 Tumor Stage (T) T1 T2 T3 T4 4 (4%) 36 (36%) 21 (21%) 39 (39%) Nodal Stage (N) N0 N1 N2 N3 51 (51%) 18 (18%) 26 (26%) 5 (5%) % - percentage, SD – standard deviation, cm – centimeter, BMI – body mass index kg – kilogram, m 2 – meter square, HGS – handgrip strength, T – tumor stage, N – Nodal stage Table 2. Comparative Analysis by Age Group and Tumor Stage Variable <50 years (n=47) ≥50 years (n=53) p-value Early Stage (I–II) Advanced Stage (III–IV) p-value Body weight (kg), mean ± SD 66.2 ± 12.5 68.0 ± 13.4 0.42 70.4 ± 11.1 65.2 ± 13.8 0.03* BMI (kg/m²), mean ± SD 24.7 ± 4.2 24.3 ± 4.4 0.65 25.1 ± 3.7 23.9 ± 4.6 0.18 Fat mass (%), mean ± SD 21.8 ± 5.2 21.1 ± 5.4 0.48 22.4 ± 4.9 20.7 ± 5.3 0.12 Muscle mass (%), mean ± SD 26.2 ± 4.3 26.7 ± 3.8 0.45 27.4 ± 3.7 25.9 ± 4.1 0.06 HGS (kg), mean ± SD 20.6 ± 4.7 20.0 ± 4.5 0.49 21.8 ± 4.2 19.4 ± 4.5 0.01* Kg- kilogram, SD – standard deviation, BMI – body mass index, %- percentage, n – number of participants, *Statistically significant at p<0.05 Table 3: Nutrition Status over time Parameter V0 V1 V2 V3 V4 p-value Weight (kg) 67.10 ± 13.02 65.15 ± 12.65 62.26 ± 12.14 61.32 ± 11.52 62.16 ± 11.42 <0.01* BMI (kg/m²) 24.46 ± 4.28 23.77 ± 4.25 22.69 ± 3.99 21.90 ± 4.91 22.21 ± 4.92 <0.01* Fat Mass (%) 21.43 ± 5.31 19.67 ± 5.32 19.57 ± 5.19 17.64 ± 5.38 16.57 ± 5.06 <0.01* Muscle Mass (%) 26.54 ± 4.01 27.65 ± 3.02 27.13 ± 3.32 25.51 ± 4.05 27.08 ± 3.59 <0.01* HGS (kg) 20.34 ± 4.64 18.01 ± 4.04 17.94 ± 4.72 17.27 ± 4.76 18.48 ± 4.36 <0.01* Kg – kilogram, % - percentage, BMI - Body Mass Index, FM - Fat Mass, MM - Muscle Mass, HGS – Handgrip strength, * Statistically significant at p<0.05 Table 4 . Nutritional Decline: Surgery Phase (V0 → V1) vs. Radiotherapy Phase (V2 → V3) Parameter Decline After Surgery Decline After RT Greater Decline p-value Weight (kg) 1.95 kg 0.94 kg Surgery 0.000* BMI (kg/m²) 0.69 0.79 Radiotherapy 0.000* Fat Mass (%) 1.76% 1.93% Radiotherapy 0.000* Muscle Mass (%) Increase (–1.11%) 1.62% loss Radiotherapy 0.000 Handgrip Strength (kg) 2.33 0.67 Surgery 0.000 Kg – kilogram, % - percentage, BMI - Body Mass Index, FM - Fat Mass, MM - Muscle Mass, HGS – Handgrip strength, * Statistically significant at p5% Weight Loss p-value Low Muscle Mass p-value Grade III Mucositis (%) 26% <0.05* 24% 0.83 Grade IV Mucositis (%) 19% <0.05* 18% 0.8 30-day Unplanned Readmission (%) 14% 0.047* 12% 0.841 Mortality (%) 10% 0.081 9% 0.612 Mean LOHS (days) 9.4 ± 2.1 0.032* 10.2 ± 1.9 - greater than, LOHS – length of hospital stay, *Statistically significant at p<0.05 Table 6: Association Between Preoperative Albumin Levels and Clinical Outcomes Albumin Level (V0) Total Patients Mortality (n, %) Grade III Mucositis (n, %) Grade IV Mucositis (n, %) 30-day Unplanned Readmissions (n, %) < 3.5 g/dL 12 5 (41.7%) 5 (41.7%) 1 (8.3%) 6 (50.0%) ≥ 3.5 g/dL 88 11 (12.5%) 37 (42.0%) 18 (20.5%) 12 (13.6%) p-value — 0.022* 0.568 0.568 0.007* g/dl – gram per deciliter, n – number, % - percentage, *Statistically significant at p<0.05 Additional Declarations No competing interests reported. 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Sathiaraj","email":"data:image/png;base64,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","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":true,"prefix":"","firstName":"Esther","middleName":"","lastName":"Sathiaraj","suffix":""},{"id":495333409,"identity":"f3af58ab-862f-43a5-966a-d404c29f2cb7","order_by":1,"name":"Kamar Afshan","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Kamar","middleName":"","lastName":"Afshan","suffix":""},{"id":495333411,"identity":"5ad51ea8-57bd-4cdc-9a3c-fa1ec9b0d716","order_by":2,"name":"Shivani Sharma","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Shivani","middleName":"","lastName":"Sharma","suffix":""},{"id":495333412,"identity":"32712eee-da60-4164-8b1c-c4776e94af0c","order_by":3,"name":"R Sruthi","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"R","middleName":"","lastName":"Sruthi","suffix":""},{"id":495333413,"identity":"b4a981c1-9bde-424b-ac6e-5b508c4b6068","order_by":4,"name":"Prasanna Suresh Hegde","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Prasanna","middleName":"Suresh","lastName":"Hegde","suffix":""},{"id":495333414,"identity":"1331b961-8b6d-4710-81f0-ba212ff8694a","order_by":5,"name":"Shalini Thakur","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Shalini","middleName":"","lastName":"Thakur","suffix":""},{"id":495333415,"identity":"b4bc1073-4093-41ea-ab01-21f8e3fd4234","order_by":6,"name":"Anand Subhash","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Anand","middleName":"","lastName":"Subhash","suffix":""},{"id":495333416,"identity":"300a1b0d-7400-4eb5-bbc9-24b7899956ea","order_by":7,"name":"Vishal Rao","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Vishal","middleName":"","lastName":"Rao","suffix":""},{"id":495333417,"identity":"1391845b-13c2-4dad-a71e-04b464817ecd","order_by":8,"name":"Radheshyam Naik","email":"","orcid":"","institution":"HCG Cancer Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Radheshyam","middleName":"","lastName":"Naik","suffix":""}],"badges":[],"createdAt":"2025-06-24 07:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6963010/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6963010/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00520-025-10217-1","type":"published","date":"2025-11-25T15:57:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88413716,"identity":"d615613a-4ff8-448c-9ba7-8d21a15946fe","added_by":"auto","created_at":"2025-08-06 08:42:00","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":299677,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLongitudinal changes in weight, BMI, fat mass, muscle mass, and handgrip strength across treatment visits (V0 to V4).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6963010/v1/886825fa416b214218d7a4be.jpeg"},{"id":97180013,"identity":"7e54f217-07ce-435b-9a48-a76bc2651882","added_by":"auto","created_at":"2025-12-01 16:17:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1550029,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6963010/v1/97cd86b5-d1be-4e59-a529-776a5ca6e13a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Nutritional Surveillance from Surgery to Post-Radiotherapy in Oral Cavity Cancer: A Prospective Longitudinal Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOral cavity cancer is one of the most common malignancies of the head and neck, with a rising global burden and particular significance in low- and middle-income countries due to prevalent lifestyle and environmental risk factors [1,2]. Despite improvements in surgical and radiotherapeutic techniques, the overall five-year survival rate remains approximately 50%, and patients often face substantial morbidity throughout the course of treatment [2].\u003c/p\u003e\u003cp\u003eThe disease itself and its treatment modalities\u0026mdash;primarily surgery followed by radiotherapy (RT)\u0026mdash;result in a range of nutrition-impact symptoms, including mucositis, dysgeusia, xerostomia, dysphagia, and pain, all of which impair oral intake and increase the risk of unintentional weight loss [3,4]. Studies have shown that 25\u0026ndash;50% of patients with head and neck cancer (HNC) experience reduced dietary intake before initiating treatment, with most losing over 5% of their body weight even before therapy begins, and some losing up to 10% during the treatment course [5,6].\u003c/p\u003e\u003cp\u003eMalnutrition in this group has been linked to poor treatment tolerance, reduced therapy completion rates, diminished quality of life, increased hospitalization costs, and adverse survival outcomes [7,8]. Consequently, early identification of malnutrition and repeated nutritional assessments during treatment are critical to optimizing patient outcomes.\u003c/p\u003e\u003cp\u003eWhile nutritional interventions are known to support dietary intake and recovery in patients undergoing surgery and chemo-radiation [9,10], current literature lacks comprehensive, longitudinal data that evaluates multiple nutritional domains\u0026mdash;including anthropometry, body composition, muscle function, and biomarkers\u0026mdash;throughout the entire treatment trajectory. The present study aims to address this gap by mapping nutritional trends over time and exploring the association between key nutritional indicators and clinical outcomes, including length of hospital stay, readmissions, radiotherapy compliance, and mortality in oral cavity cancer patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Participants\u003c/h2\u003e\u003cp\u003eThis prospective observational study was conducted at HCG Cancer Hospitals, Bengaluru, between March and December 2024. Adult patients (\u0026ge;\u0026thinsp;18 years) with a histologically confirmed diagnosis of oral cavity cancer who were scheduled for surgical treatment with curative intent were eligible for inclusion. Participants were required to provide written informed consent and be capable of effective communication. Exclusion criteria included concurrent or active malignancies other than oral cancer, evidence of metastasis, and inability to undergo BIA such as patients with pacemakers or those unable to stand unaided.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eNutritional Assessment Time Points\u003c/h3\u003e\n\u003cp\u003eParticipants underwent five standardized assessments throughout their treatment course:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eV0\u003c/b\u003e: Within three days before surgery (preoperative)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eV1\u003c/b\u003e: Seven days post-surgery\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eV2\u003c/b\u003e: One day before radiotherapy (RT) initiation\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eV3\u003c/b\u003e: At the completion of RT\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eV4\u003c/b\u003e: One month after RT\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eAt each of these time-points, comprehensive nutritional assessments were performed, including body composition analysis using BIA (Bodystat 1500), 24-hour dietary recall, HGS, and serum albumin (V0 only).\u003c/p\u003e\n\u003ch3\u003eAnthropometry and Body Composition\u003c/h3\u003e\n\u003cp\u003eAnthropometric parameters included body weight (kg), body mass index (BMI, kg/m\u0026sup2;), and percentage weight loss from baseline. BMI was categorized based on WHO classifications: underweight (\u0026lt;\u0026thinsp;18.5), normal weight (18.5\u0026ndash;24.9), pre-obese (25.0\u0026ndash;29.9), and obese (\u0026ge;\u0026thinsp;30) [11].\u003c/p\u003e\u003cp\u003eBody composition, fat mass (%) and muscle mass (%), was evaluated at each time point using BIA, a validated non-invasive method for estimating body compartments in clinical populations [13].\u003c/p\u003e\n\u003ch3\u003eNutrition Screening and Laboratory Assessment\u003c/h3\u003e\n\u003cp\u003eNutritional risk was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA), which classifies patients into well-nourished (A), moderately malnourished (B), and severely malnourished (C) [12]. Preoperative serum albumin levels were measured and categorized as normal (\u0026ge;\u0026thinsp;3.5 g/dL) or hypoalbuminemic (\u0026lt;\u0026thinsp;3.5 g/dL), based on standard clinical cut-offs [14].\u003c/p\u003e\n\u003ch3\u003eFunctional Muscle Assessment\u003c/h3\u003e\n\u003cp\u003eHGS was measured using an electronic dynamometer (EH101, Camry, China) in a seated position. The protocol involved testing the dominant and non-dominant hands followed by a one-minute rest, with the highest value used for analysis. Dynapenia was defined per EWGSOP guidelines: \u0026lt;30 kg for men and \u0026lt;\u0026thinsp;20 kg for women [15,16].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eTreatment Details\u003c/h2\u003e\u003cp\u003eAll patients underwent surgical resection followed by intensity-modulated radiotherapy (IMRT), with or without chemotherapy. Radiotherapy typically commenced within 3\u0026ndash;4 weeks of surgery.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eClinical and Outcome Measures\u003c/h3\u003e\n\u003cp\u003eKey clinical parameters recorded included date of surgery, discharge date, readmission within 30 days, and RT details (planned vs. actual doses, start/end dates). Mucositis was graded based on Radiation Therapy Oncology Group (RTOG) criteria from Grade 1 (mild) to Grade 4 (severe) [18]. Length of hospital stay (LOHS) was defined as days from postoperative day one to discharge. RT compliance was assessed by comparing actual treatment duration against the ideal duration [17].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration. Ethical approval for this observational trial was obtained from the Institutional Review Board of HCG Cancer Hospitals, Bengaluru. Written informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were used to summarize demographic, nutritional, and clinical variables. Continuous data were expressed as mean \u0026plusmn; standard deviation (SD), and categorical data as frequencies and percentages. Relationships between nutritional variables and clinical outcomes were evaluated using linear and logistic regression models. A p-value \u0026lt;0.05 was considered statistically significant. Analyses were conducted using SPSS version 11.0 (SPSS Inc., Chicago, IL, USA).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient Demographics and Clinical Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 provides a summary of patient demographics and baseline clinical characteristics. The mean age of the study population was 52.1 \u0026plusmn; 11.7 years, ranging from 26 to 70 years. The cohort was predominantly male (86%). The tongue and buccal mucosa were the most commonly affected sub-sites, each accounting for 32% of cases. Most patients (72%) presented with advanced-stage disease (Stage III or IV).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparative Analysis Based on Age and Tumor Stage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA comparative evaluation of key nutritional and clinical parameters across age groups (\u0026lt;50 vs. \u0026ge;50 years) and disease stage (early vs. advanced) is shown in Table 2. While weight and HGS were significantly lower in the advanced-stage group (p \u0026lt; 0.05), no significant differences were observed in BMI, fat mass, or muscle mass. Younger patients (\u0026lt;50 years) exhibited similar nutritional profiles to older individuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLongitudinal Changes in Nutritional Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 and figure 1 outlines the progression of nutritional indicators across the five study time points. Statistically significant reductions (p \u0026lt; 0.01) were noted in weight, BMI, fat mass, and HGS from the preoperative phase (V0) through the completion of radiotherapy (V3), with partial recovery by the one-month follow-up (V4).\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eBody weight\u003c/strong\u003e decreased from 67.10 \u0026plusmn; 13.02 kg at V0 to 61.32 \u0026plusmn; 11.52 kg at V3, with a modest increase to 62.16 \u0026plusmn; 11.42 kg at V4.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eBMI\u003c/strong\u003e declined from 24.46 \u0026plusmn; 4.28 kg/m\u0026sup2; at baseline to 21.90 \u0026plusmn; 4.91 kg/m\u0026sup2; at V3.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFat mass (%)\u003c/strong\u003e dropped progressively from 21.43 \u0026plusmn; 5.31% to 16.57 \u0026plusmn; 5.06% by V4.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMuscle mass (%)\u003c/strong\u003e showed a postoperative increase at V1, followed by a decline during radiotherapy (V3), and a slight rebound at V4.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHGS\u003c/strong\u003e declined steadily, from 20.34 \u0026plusmn; 4.64 kg at baseline to 17.27 \u0026plusmn; 4.76 kg at V3, with some recovery at V4 (18.48 \u0026plusmn; 4.36 kg).\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eA comparative analysis of nutritional decline between the surgical (V0\u0026rarr;V1) and RT (V2\u0026rarr;V3) phases revealed statistically significant changes across all measured parameters (p \u0026lt; 0.001) (table 4). Post-surgery, a greater reduction was observed in handgrip strength (mean = 2.33 kg) and body weight (mean = 1.95 kg), suggesting acute postoperative catabolism and reduced intake. In contrast, the RT phase was associated with more pronounced declines in BMI (mean = 0.79 kg/m\u0026sup2;), fat mass (mean = 1.93%), and muscle mass (mean = 1.62%), indicating sustained nutritional deterioration. Notably, muscle mass showed a increase immediately post-surgery (mean = \u0026ndash;1.11%), possibly due to fluid redistribution or early rehabilitation effects, but declined sharply during radiotherapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship Between Weight Loss and Mucositis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 5, patients with more than 5% weight loss were significantly more likely to develop higher grades of mucositis. Specifically, 26% of these individuals experienced Grade III mucositis and 19% developed Grade IV by the end of radiotherapy (p \u0026lt; 0.05), suggesting a strong link between weight loss and RT-induced mucosal toxicity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMuscle Mass and Clinical Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLow muscle mass was significantly associated with increased length of hospital stay (LOHS), with a mean duration of 10.2 \u0026plusmn; 1.9 days compared to 9.4 \u0026plusmn; 2.1 days in patients with higher muscle mass (p \u0026lt; 0.05). However, no statistically significant association was found between muscle mass and mortality, severe mucositis, or 30-day readmission (table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerum Albumin and Mortality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreoperative hypoalbuminemia (\u0026lt;3.5 g/dL) was significantly correlated with higher mortality (p = 0.022). Among the 12 patients with low albumin, only 58.3% survived, compared to 87.5% survival in the normal albumin group (n = 88). (Table 6)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlbumin and Mucositis Severity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo significant relationship was observed between serum albumin levels and mucositis severity (p = 0.568; table 6). Although the distribution of Grade III mucositis was similar in both groups, a smaller percentage of hypoalbuminemic patients developed Grade IV mucositis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlbumin and Readmission Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnplanned 30-day hospital readmissions were significantly more frequent in patients with hypoalbuminemia (50%) than in those with normal albumin levels (13.6%) (p = 0.007; table 6), suggesting that low preoperative albumin is a reliable predictor of early readmission risk.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis prospective longitudinal study provides a comprehensive evaluation of nutritional status in patients undergoing curative treatment for oral cavity cancer. By assessing parameters such as body composition, muscle strength, serum albumin, and dietary intake at five time points, we offer valuable insight into the progression of malnutrition and its relationship with treatment outcomes. Our findings confirm that significant nutritional deterioration occurs throughout the surgical and radiotherapy phases, with partial recovery noted only in the post-treatment period.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA mean weight loss of nearly 5 kg was observed from baseline (V0) to one month after radiotherapy (V4), consistent with patterns reported in earlier studies among head and neck cancer cohorts [19,20]. Early weight loss was primarily attributed to reductions in fat mass, whereas the later stages involved concurrent loss of both fat and muscle mass. These observations align with previous longitudinal studies that highlight the compounded effects of multimodal therapy on body composition [20,21]. Muscle depletion, in particular, appeared to be linked with clinical recovery, as patients with lower muscle mass had significantly longer hospital stays and higher readmission rates, suggesting its prognostic relevance in surgical oncology.\u003c/p\u003e\n\u003cp\u003eThe phase-wise comparison of nutritional status highlights distinct patterns of deterioration during treatment. While the immediate postoperative period was marked by significant loss in functional capacity, reflected by reduced handgrip strength and weight, the RT phase contributed more substantially to losses in body composition, especially fat and muscle mass. This trend is consistent with previous literature [22] describing radiotherapy-associated anorexia, mucosal toxicity, and systemic inflammation as key contributors to progressive malnutrition. The sharp decline in muscle mass during radiotherapy, despite relative preservation post-surgery, emphasizes the need for targeted interventions such as high-protein supplementation and resistance-preserving strategies during this phase. These findings reinforce the importance of tailoring nutrition care not just to treatment modality, but to specific treatment windows, to mitigate compounded nutritional risk.\u003c/p\u003e\n\u003cp\u003eOur results also support prior literature showing that sarcopenia negatively impacts clinical outcomes in cancer populations. Filgrad et al. demonstrated that patients with post-radiotherapy sarcopenia had significantly lower survival rates, underscoring the long-term implications of muscle loss [23]. Similarly, studies using BIA have established its utility in quantifying sarcopenia and tracking nutritional trends in head and neck cancer patients [24]. A recent meta-analysis also reinforced that low muscle mass is associated with increased toxicity, prolonged hospital stay, and poor overall survival in this population [25].\u003c/p\u003e\n\u003cp\u003eWeight loss was significantly associated with higher grades of mucositis. In our cohort, 45% of patients with \u0026gt;5% weight loss developed Grade III or IV mucositis by V3, comparable to data from previous reports linking nutritional decline to worsening mucosal toxicity [26]. The underlying mechanism is likely multifactorial, involving poor oral intake due to dysphagia, mucosal pain, taste changes, and systemic inflammation\u0026mdash;all of which can amplify nutritional deficits and compromise treatment compliance [25,27].\u003c/p\u003e\n\u003cp\u003eAdvanced tumor stage was also associated with more pronounced nutritional decline, particularly in terms of weight and functional muscle strength. These findings suggest that tumor burden, in addition to treatment toxicity, contributes to energy imbalance and catabolism, which cumulatively increases the risk of malnutrition and sarcopenia.\u003c/p\u003e\n\u003cp\u003eSerum albumin emerged as a significant predictor of both mortality and 30-day hospital readmissions. Patients with preoperative hypoalbuminemia (\u0026lt;3.5 g/dL) had notably poorer survival and were more likely to require unplanned readmissions following surgery. This finding is supported by studies in gastrointestinal, and head and neck cancers, where low albumin levels have consistently been associated with adverse outcomes [28\u0026ndash;29]. Although albumin is not a direct marker of nutritional status, its role as a surrogate for systemic inflammation and metabolic stress makes it a valuable tool in perioperative risk stratification [29,30].\u003c/p\u003e\n\u003cp\u003eNotably, we found no significant association between albumin levels and mucositis severity, reinforcing the need for multimodal nutritional markers when evaluating treatment toxicity. While albumin alone may not predict local toxicities, it does reflect broader systemic risks such as infection, healing delays, and complications that can influence hospital utilization and recovery trajectories.\u003c/p\u003e\n\u003cp\u003eA major strength of this study lies in its longitudinal design and use of multiple nutritional indicators at defined clinical intervals. This approach allowed for the tracking of dynamic changes in nutritional status and their correlations with clinically meaningful endpoints. Our integration of objective (BIA), functional (HGS), and biochemical (albumin) assessments offers a robust framework for nutritional surveillance in oral oncology.\u003c/p\u003e\n\u003cp\u003eHowever, certain limitations must be acknowledged. This was a single-center study with a limited sample size, which may affect generalizability. The accuracy of BIA measurements may vary based on hydration status and timing, although standardized protocols were followed. The study also did not include markers of inflammation such as C-reactive protein, which could have provided additional insight into the role of systemic stress. Lastly, the follow-up period was relatively short, limiting our ability to evaluate long-term nutritional recovery and survival outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the profound and progressive nature of nutritional decline in patients undergoing multimodal treatment for oral cavity cancer. Significant reductions in weight, fat mass, muscle strength, and serum albumin were observed over time, particularly during the radiotherapy phase. These changes were strongly associated with adverse clinical outcomes, including prolonged hospital stay, severe mucositis, increased postoperative readmissions, and mortality. Among the nutritional indicators assessed, low muscle mass and hypoalbuminemia emerged as important predictors of poor treatment tolerance and clinical recovery. The findings reinforce the need for early identification of at-risk individuals and emphasize the value of implementing structured, multimodal nutritional surveillance throughout the treatment continuum. Integrating personalized nutritional interventions into multidisciplinary cancer care protocols may enhance treatment compliance, reduce complications, and improve overall patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank all the study participants for their cooperation and commitment throughout the study period. We also acknowledge the dedicated efforts of the clinical nutrition and surgical and radiation oncology staff at HCG Cancer Hospitals, Bengaluru, for their invaluable support in data collection and patient follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non‑financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation or conduct of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Esther Sathiaraj, Kamar Afshan, Shivani Sharma and Sruthi R. The first draft of the manuscript was written by Shivani Sharma and Esther Sathiaraj and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhuang B, Zhang L, Wang Y, Cao Y, Shih Y, Jin S, Li H, Gong L, Wang Y, Lu Q. Body composition and dietary intake in patients with head and neck cancer during radiotherapy: a longitudinal study. BMJ Supportive \u0026amp; Palliative Care. 2020;13(4):445-52. doi:10.1136/bmjspcare-2019-001803\u003c/li\u003e\n\u003cli\u003eSun Z, Zhang Y, Liu Y, Zhang Y, Li J, Wang H, et al. Global, regional, and national burden of oral cancer and its attributable risk factors from 1990 to 2019. Cancer Med. 2023;12(3):1234\u0026ndash;1245. doi:10.1002/cam4.6025\u003c/li\u003e\n\u003cli\u003eSankaranarayanan R, Ramadas K, Thomas G, Muwonge R, Thara S, Mathew B, et al. 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Nutritional assessment and prognosis of oral cancer patients: a large-scale prospective study. \u003cem\u003eBMC Cancer\u003c/em\u003e. 2020;20(1):146. doi:10.1186/s12885-020-06740-9\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Obesity: preventing and managing the global epidemic. Report on a WHO consultation. Geneva: World Health Organization; 2000. (WHO Technical Report Series, No. 894).\u003c/li\u003e\n\u003cli\u003eOttery FD. Definition of standardized nutritional assessment and interventional pathways in oncology. Nutrition. 1996;12(1 Suppl):S15\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eKyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, G\u0026oacute;mez JM, et al. Bioelectrical impedance analysis\u0026mdash;part I: review of principles and methods. Clin Nutr. 2004;23(5):1226\u0026ndash;43. doi:10.1016/j.clnu.2004.06.004\u003c/li\u003e\n\u003cli\u003eDon BR, Kaysen G. Serum albumin: relationship to inflammation and nutrition. 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Bioelectrical impedance analysis as a quantitative measure of sarcopenia in head and neck cancer patients treated with radiotherapy. \u003cem\u003eRadiother Oncol\u003c/em\u003e. 2021;159:21\u0026ndash;27. doi:10.1016/j.radonc.2021.04.021\u003c/li\u003e\n\u003cli\u003eDeng Y, Wang L, Liu T, et al. Impact of sarcopenia on survival and clinical outcomes in patients with head and neck cancer undergoing radiotherapy: a meta-analysis. \u003cem\u003eFront Oncol\u003c/em\u003e. 2022;12:843111. doi:10.3389/fonc.2022.843111.\u003c/li\u003e\n\u003cli\u003eElting LS, Keefe DM, Sonis ST, et al. Patient‑reported measurements of oral mucositis in head and neck cancer patients treated with radiotherapy with or without chemotherapy. \u003cem\u003eCancer\u003c/em\u003e. 2008;113(10):2704\u0026ndash;13. doi:10.1002/cncr.23927\u003c/li\u003e\n\u003cli\u003eDatema FR, Ferrier MB, Baatenburg de Jong RJ. Impact of severe malnutrition on short‑term mortality and overall survival in head and neck cancer. \u003cem\u003eOral Oncol\u003c/em\u003e. 2011;47(9):910\u0026ndash;4. doi:10.1016/j.oraloncology.2011.05.012\u003c/li\u003e\n\u003cli\u003eLiang JT, Lai HS, Chen CC. Hypoalbuminemia and colorectal cancer; a systematic review and meta-analysis. \u003cem\u003eColorectal Dis\u003c/em\u003e. 2023;25(4):520\u0026ndash;9. doi:10.1111/codi.16261\u003c/li\u003e\n\u003cli\u003eLiang JJ, Zhang J, Liu YJ, Li HY, Tian YL, Li HZ. Preoperative hypoalbuminemia in colon cancer patients increases risks of mortality and morbidity. Colorectal Dis. 2016;18(10):970\u0026ndash;8. doi:10.1111/codi.13304\u003c/li\u003e\n\u003cli\u003eLiu Y, Zhang Y, Zhang H, Wang H. Preoperative serum albumin as a predictor of postoperative complications and survival in patients with oral squamous cell carcinoma: A retrospective study. \u003cem\u003eCancer Manag Res\u003c/em\u003e. 2021;13:2131\u0026ndash;40. doi:10.2147/CMAR.S303488\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Patient Characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Patients (%) / Mean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e86 (86%)\u003c/p\u003e\n \u003cp\u003e14 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003e\u0026lt;50\u003c/p\u003e\n \u003cp\u003e\u0026gt;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47 (47%)\u003c/p\u003e\n \u003cp\u003e53 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e165 \u0026plusmn; 7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eBody Weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e67.1 \u0026plusmn; 13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e24.5 \u0026plusmn; 4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eFat Mass (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e21.4 \u0026plusmn; 5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eMuscle Mass (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e26.5 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003eHGS (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 312px;\"\u003e\n \u003cp\u003e20.3 \u0026plusmn; 4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eTumor Stage (T)\u003c/p\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (4%)\u003c/p\u003e\n \u003cp\u003e36 (36%)\u003c/p\u003e\n \u003cp\u003e21 (21%)\u003c/p\u003e\n \u003cp\u003e39 (39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eNodal Stage (N)\u003c/p\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003cp\u003eN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e51 (51%)\u003c/p\u003e\n \u003cp\u003e18 (18%)\u003c/p\u003e\n \u003cp\u003e26 (26%)\u003c/p\u003e\n \u003cp\u003e5 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e% - percentage, SD \u0026ndash; standard deviation, cm \u0026ndash; centimeter, BMI \u0026ndash; body mass index kg \u0026ndash; kilogram, m\u003csup\u003e2\u003c/sup\u003e \u0026ndash; meter square, HGS \u0026ndash; handgrip strength, T \u0026ndash; tumor stage, N \u0026ndash; Nodal stage\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Comparative Analysis by Age Group and Tumor Stage\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;50 years (n=47)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;50 years (n=53)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEarly Stage (I\u0026ndash;II)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAdvanced Stage (III\u0026ndash;IV)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBody weight (kg), mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.2 \u0026plusmn; 12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68.0 \u0026plusmn; 13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e70.4 \u0026plusmn; 11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65.2 \u0026plusmn; 13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u0026sup2;), mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.7 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.3 \u0026plusmn; 4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.1 \u0026plusmn; 3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.9 \u0026plusmn; 4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFat mass (%), mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.8 \u0026plusmn; 5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.1 \u0026plusmn; 5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.4 \u0026plusmn; 4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.7 \u0026plusmn; 5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMuscle mass (%), mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.2 \u0026plusmn; 4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.7 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.4 \u0026plusmn; 3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.9 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHGS (kg), mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.6 \u0026plusmn; 4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.0 \u0026plusmn; 4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.8 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.4 \u0026plusmn; 4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eKg- kilogram, SD \u0026ndash; standard deviation, BMI \u0026ndash; body mass index, %- percentage, n \u0026ndash; number of participants, *Statistically significant at p\u0026lt;0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Nutrition Status over time\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eV0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eV1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eV2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eV3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eV4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e67.10 \u0026plusmn; 13.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65.15 \u0026plusmn; 12.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.26 \u0026plusmn; 12.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61.32 \u0026plusmn; 11.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.16 \u0026plusmn; 11.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u0026sup2;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.46 \u0026plusmn; 4.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.77 \u0026plusmn; 4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.69 \u0026plusmn; 3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.90 \u0026plusmn; 4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.21 \u0026plusmn; 4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFat Mass (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.43 \u0026plusmn; 5.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.67 \u0026plusmn; 5.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.57 \u0026plusmn; 5.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.64 \u0026plusmn; 5.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.57 \u0026plusmn; 5.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMuscle Mass (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.54 \u0026plusmn; 4.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.65 \u0026plusmn; 3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.13 \u0026plusmn; 3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.51 \u0026plusmn; 4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.08 \u0026plusmn; 3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHGS (kg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.34 \u0026plusmn; 4.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.01 \u0026plusmn; 4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.94 \u0026plusmn; 4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.27 \u0026plusmn; 4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.48 \u0026plusmn; 4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eKg \u0026ndash; kilogram, % - percentage, BMI - Body Mass Index, FM - Fat Mass, MM - Muscle Mass, HGS \u0026ndash; Handgrip strength, \u003cstrong\u003e*\u003c/strong\u003eStatistically significant at p\u0026lt;0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e. \u003cstrong\u003eNutritional Decline: Surgery Phase (V0 \u0026rarr; V1) vs. Radiotherapy Phase (V2 \u0026rarr; V3)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDecline After Surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDecline After RT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGreater Decline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.95 kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.94 kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRadiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFat Mass (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.76%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRadiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMuscle Mass (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIncrease\u003c/strong\u003e (\u0026ndash;1.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.62% loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRadiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHandgrip Strength (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eKg \u0026ndash; kilogram, % - percentage, BMI - Body Mass Index, FM - Fat Mass, MM - Muscle Mass, HGS \u0026ndash; Handgrip strength, \u003cstrong\u003e*\u003c/strong\u003eStatistically significant at p\u0026lt;0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Association of Nutritional Parameters with Clinical Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;5% Weight Loss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLow Muscle Mass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGrade III Mucositis (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.05*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGrade IV Mucositis (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.05*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e30-day Unplanned Readmission (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.047*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMortality (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean LOHS (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.4 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.032*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.2 \u0026plusmn; 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.05*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e% - percentage, \u0026gt; - greater than, LOHS \u0026ndash; length of hospital stay, *Statistically significant at p\u0026lt;0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6: Association Between Preoperative Albumin Levels and Clinical Outcomes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAlbumin Level (V0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMortality (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGrade III Mucositis (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGrade IV Mucositis (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e30-day Unplanned Readmissions (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt; 3.5 g/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge; 3.5 g/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 (42.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.022*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.007*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eg/dl \u0026ndash; gram per deciliter, n \u0026ndash; number, % - percentage, *Statistically significant at p\u0026lt;0.05\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Oral cavity cancer, nutritional status, sarcopenia, handgrip strength, albumin, radiotherapy","lastPublishedDoi":"10.21203/rs.3.rs-6963010/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6963010/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003ePatients diagnosed with oral cavity cancer are highly vulnerable to nutritional deterioration due to both tumor-related factors and treatment-induced side effects. This prospective longitudinal study aimed to trace the nutritional progression of these patients using a structured surveillance framework and to examine how key nutritional indicators influence clinical outcomes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThe study enrolled 100 individuals with histologically confirmed oral cavity cancer, all of whom were scheduled for surgical resection followed by radiotherapy. Nutritional evaluations\u0026mdash;including bioelectrical impedance analysis (BIA) for body composition, handgrip strength (HGS), serum albumin, and dietary intake assessments\u0026mdash;were conducted at five critical visits: pre-surgery (V0), post-surgery (V1), before radiotherapy (V2), end of radiotherapy (V3), and one-month post-radiotherapy (V4). Outcome measures included length of hospital stay (LOHS), mucositis severity, hospital re-admissions, and mortality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eSignificant declines were noted in body weight, body mass index (BMI), fat mass, and HGS across treatment phases (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). A weight loss greater than 5% was associated with a higher prevalence of Grade III/IV mucositis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Reduced muscle mass correlated with longer hospital stays, while preoperative hypoalbuminemia (\u0026lt;\u0026thinsp;3.5 g/dL) was significantly linked to increased mortality (p\u0026thinsp;=\u0026thinsp;0.022) and readmissions (p\u0026thinsp;=\u0026thinsp;0.007). No significant association was found between albumin and mucositis severity.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study demonstrates a clear link between nutritional deterioration and adverse clinical outcomes in oral cancer patients. Regular, multi-dimensional nutritional monitoring is essential, and early individualized interventions may improve treatment tolerance and patient recovery.\u003c/p\u003e","manuscriptTitle":"Nutritional Surveillance from Surgery to Post-Radiotherapy in Oral Cavity Cancer: A Prospective Longitudinal Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-06 08:41:55","doi":"10.21203/rs.3.rs-6963010/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-18T16:18:56+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"120950806887601501085550763137870087094","date":"2025-09-09T07:00:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T16:58:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54389090384611189760032281520619076289","date":"2025-08-22T09:24:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-04T10:46:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-31T15:24:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-28T09:26:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2025-06-24T07:49:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"af4d1a73-af48-4726-88a0-8235c0f25ef1","owner":[],"postedDate":"August 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:17:11+00:00","versionOfRecord":{"articleIdentity":"rs-6963010","link":"https://doi.org/10.1007/s00520-025-10217-1","journal":{"identity":"supportive-care-in-cancer","isVorOnly":false,"title":"Supportive Care in Cancer"},"publishedOn":"2025-11-25 15:57:01","publishedOnDateReadable":"November 25th, 2025"},"versionCreatedAt":"2025-08-06 08:41:55","video":"","vorDoi":"10.1007/s00520-025-10217-1","vorDoiUrl":"https://doi.org/10.1007/s00520-025-10217-1","workflowStages":[]},"version":"v1","identity":"rs-6963010","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6963010","identity":"rs-6963010","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}