Study of Nutritional Status and Clinical Outcomes in Patients With Common Malignancies
Conditions: Cancer, Chemoradiotherapy, Nutrition, Healthy, Oncology, Clinical Outcomes
Sponsor: Xiaoqin Luo

 
 
1
A cohort study protocol of nutritional status and clinical outcomes 
1 
in patients with common malignancies (NCOM study)  
2 
HeXiang Yang 1#, Yaxin Yu 1#, Haige Cao1，Jinglin Li1，Feng Liu1，Xiaoqin Luo 
3 
1ID 
4 
Malnutrition is common in cancer patients, impairing treatment tolerance, quality of life, and 
5 
survival. However, its longitudinal association with clinical outcomes remains unclear. The 
6 
Nutritional Status and Clinical Outcomes in Patients with Common Malignancies (NCOM) 
7 
study investigates the long-term impact of nutritional status on cancer outcomes and identifies 
8 
modifiable risk factors to support personalised nutritional care. This prospective, multicentre 
9 
cohort includes cancer patients from 11 hospitals in China. Nutritional status is assessed 
10 
within 48 hours of admission, with follow-ups at 1, 2, 3, 6, and 12 months, then annually for 4 
11 
years. Data include nutritional assessments, biomarkers, quality of life, psychosocial factors, 
12 
physical activity, sleep, dietary knowledge, attitudes and practices, and survival outcomes. 
13 
Multivariable models, survival analysis, and longitudinal methods will be used. Early findings 
14 
reveal a high burden of nutritional risk, underscoring the importance of timely identification 
15 
and intervention. The study will generate critical evidence to optimise nutrition-focused 
16 
strategies and improve clinical outcomes in oncology. 
17 
Keywords  Cancer, Nutritional status, Malnutrition, Clinical outcomes, Cohort study 
18 
 
 
19 

 
 
2
Introduction 
20 
Cancer remains a leading cause of mortality worldwide, with nearly 20 million new cases and 9.7 
21 
million deaths reported in 2022. Approximately 20% of individuals will develop cancer in their 
22 
lifetime, and 11% of men and 8% of women are expected to succumb to the disease(Bray et al). In 
23 
China, rapid population growth, increasing demographics, and unhealthy lifestyles are driving an 
24 
increasing cancer burden(Cao et al, 2021; Qiu et al, 2021). 
25 
Malnutrition is common among cancer patients, with prevalence rates ranging from 16–40% at 
26 
diagnosis and increasing to 40–80% during treatment, depending on factors such as age, cancer type, 
27 
and treatment modality(Bossi et al, 2021; Kaegi-Braun et al, 2021). Tumor location plays a crucial 
28 
role, with the highest malnutrition rates observed in pancreatic (66.7%), esophageal/gastric (60.2%), 
29 
head and neck (48.9%), and lung (45.3%) cancers(Hébuterne et al, 2014; Bossi et al, 2021). 
30 
Nutritional status in cancer patients is intricately linked to clinical outcomes. Tumor and 
31 
therapeutic interventions notably impact nutritional health(Webb et al, 2020; Kipouros et al, 2023). 
32 
Malnutrition significantly affects treatment tolerance, morbidity, survival, and quality of 
33 
life(Hébuterne et al, 2014; Liu et al, 2021; Garutti et al, 2023). It can lead to reduced nutrient intake, 
34 
cachexia, and impaired treatment efficacy(Muscaritoli et al, 2019; Holdoway et al, 2023). Early 
35 
nutritional interventions have been shown to mitigate adverse clinical outcomes and reduce 30-day 
36 
mortality in at-risk patients(Muscaritoli et al, 2019; Schuetz et al, 2019; Kipouros et al, 2023). 
37 
Although the association between malnutrition and adverse clinical outcomes has been well 
38 
established (Muscaritoli et al, 2019; Liu et al, 2021; Kipouros et al, 2023), the benefits of nutritional 
39 
improvement reported in different studies remain inconsistent (Schuetz et al, 2019; Kaegi-Braun et 
40 
al, 2021). On the one hand, nutritional status might vary considerably over the course of 
41 
treatment(Webb et al, 2020); on the other hand, psychological factors, sleep quality, and physical 
42 
activity may further influence these outcomes (Nissim et al, 2024; Ye et al, 2024). High-quality and 
43 
large-scale cohort studies that can capture dynamic changes in nutrition are needed to carry out more 
44 
precise nutritional interventions or treatments to improve clinical outcomes. Hence, we established 
45 
a cohort study to evaluate nutritional status and clinical outcomes in patients with common 
46 
malignancies (NCOM study), aiming to provide evidence for personalized and precise nutritional 
47 
treatment in oncology care. 
48 

 
 
3
Methods 
49 
Study design 
50 
The NCOM study is a multicenter, prospective cohort study designed to assess longitudinal 
51 
changes in nutritional status and their impact on clinical outcomes in cancer patients. We aim 
52 
primarily to identify modifiable risk factors associated with malnutrition-related morbidity and 
53 
mortality and assess the effectiveness of targeted nutritional interventions. The secondary objectives 
54 
include examining variations in nutritional status across cancer types and treatment modalities and 
55 
exploring how nutritional health interacts with psychological well-being, sleep quality, and physical 
56 
activity. Participants diagnosed with common malignancies across multiple hospitals undergo 
57 
baseline nutritional assessments within 48 hours of admission, followed by structured follow-ups at 
58 
1, 2, 3, 6, and 12 months and then annually for an additional four years to track nutritional changes 
59 
and key clinical endpoints (Riboli, 2001). Nutritional status, the primary exposure factor, is 
60 
classified via validated screening tools and dietary intake assessments. Patients are stratified on the 
61 
basis of malnutrition severity, dietary intake, and nutritional support status, with classifications 
62 
updated at each follow-up, to evaluate their associations with short- and long-term outcomes (Fig. 
63 
1). 
64 

 
 
4
 
65 
Fig. 1. The workflow of the NCOM study. 
66 
 
67 
Study Setting & Population 
68 
Study sites 
69 
The NCOM study was conducted across 11 tertiary hospitals in Xi’an, Shaanxi Province, China. 
70 
The participating institutions included Shaanxi Provincial Cancer Hospital; the First Affiliated 
71 

 
 
5
Hospital of Xi’an Jiaotong University; the Second Affiliated Hospital of Xi’an Jiaotong University; 
72 
Shaanxi Provincial People’s Hospital; the First Affiliated Hospital of the Fourth Military Medical 
73 
University; the Second Affiliated Hospital of the Fourth Military Medical University; Shaanxi 
74 
Provincial Chest Hospital; and the Affiliated Hospital of Northwest University Xi’an No.3 Hospital; 
75 
Xi’an International Medical Center Hospital; The First Affiliated Hospital of Xi 'an Medical 
76 
University; The Second Affiliated Hospital of Xi’an Medical University. 
77 
Recruitment strategy 
78 
Eligible patients will be recruited by clinical medical staff. Recruitment will primarily occur 
79 
through direct physician referrals during oncology consultations, supplemented by promotional 
80 
materials in hospitals, such as posters, brochures, and electronic notices. Patients and their families 
81 
who learn about the study through these materials can also self-refer by contacting the research team. 
82 
The screening process consists of two steps. The first screening visit (SV1) is conducted remotely 
83 
via online consultation or phone call to assess basic eligibility, including willingness to participate 
84 
and key exclusion factors such as pregnancy or concurrent trial participation. Informed consent is 
85 
obtained at this stage. Patients who pass SV1 will proceed to the second screening visit (SV2), 
86 
which will be conducted onsite at each hospital. During SV2, medical records will be reviewed, and 
87 
clinical assessments will be performed to confirm whether patients meet the inclusion and exclusion 
88 
criteria. Only patients who meet all the criteria will be formally enrolled. 
89 
Inclusion criteria 
90 
a. Age ≥ 18 years. 
91 
b. Histologically confirmed diagnosis of malignancy. 
92 
c. Patients are scheduled to receive oncologic treatment, including surgery, chemotherapy, 
93 
radiotherapy, or a combination. 
94 
d. Mentally competent and able to provide informed consent. 
95 
e. Willingness to participate in follow-up assessments 
96 
f. Patients with multiple hospital admissions may be included in repeat assessments, with each 
97 
admission counted as an independent case. 
98 

 
 
6
Exclusion criteria 
99 
Patients were excluded if they met any of the following criteria: 
100 
a. Severe comorbidities that may interfere with participation (e.g., end-stage liver/kidney disease 
101 
or severe cardiac failure). 
102 
b. Patients with HIV/AIDS. 
103 
c. Prior organ transplantation recipients. 
104 
d. Expected survival of less than 6 months. 
105 
e. Pregnant patients. 
106 
f. Patients currently participating in another interventional clinical trial. 
107 
Sample size 
108 
The sample size for the NCOM study was determined on the basis of the impact of nutritional 
109 
status on clinical outcomes in cancer patients, with a two-sided significance level (α) of 0.05 and 
110 
80% power (1 − β = 0.80) (von Elm et al, 2007; Arends et al, 2017). On the basis of previous studies 
111 
on nutritional status and cancer outcomes, we assumed a baseline event rate of 20% (P₁ = 0.50) in 
112 
the unexposed group and an expected rate of 24% (P₂ = 0.40) in the exposed group(Rasschaert et al, 
113 
2024). Given that longitudinal oncology cohort studies report attrition rates ranging from 30% to 
114 
50% over a multiyear follow-up period (Reeves et al, 2007; Schwedhelm et al, 2016), the final 
115 
target sample size for this study was estimated to be approximately 1,538 participants. 
116 
Data collection 
117 
Data collection followed a standardized protocol across all participating hospitals to ensure 
118 
consistency and accuracy. The baseline assessments will be conducted within 48 hours of hospital 
119 
admission, and well-trained researchers will collect information on demographic and clinical data, 
120 
nutritional status, laboratory biomarkers, quality of life, psychosocial factors, physical activity, sleep 
121 
status, and knowledge, attitudes, and practices (KAPs). Follow-up assessments will be conducted at 
122 
predefined intervals to track longitudinal changes in nutritional status and clinical outcomes. 
123 
To ensure data reliability, each hospital will designate 1 to 2 trained personnel to be responsible 
124 
for questionnaires and clinical data recording. At the same time, a supervisor will be appointed to 
125 
review the integrity of the data and coordinate follow-up work if necessary. All researcher personnel 
126 

 
 
7
must complete standardized training and pass competency assessments to ensure consistency in data 
127 
collection and minimize variations. 
128 
Data management will be centralized through the Research Electronic Data Capture (REDCap) 
129 
system, which ensures data security, accuracy, and accessibility(Harris et al, 2009). Standardized, 
130 
validated measurement tools will be used at each site. Data entry will include built-in validation 
131 
checks to identify missing values or inconsistencies, with routine audits and cross-site comparisons 
132 
performed to maintain high data quality and study validity. 
133 
Data Content & Assessment Tools 
134 
Demographics & Clinical Data 
135 
Upon enrollment, trained personnel will obtain informed consent and record demographic details, 
136 
including sex, age, marital status, occupation, education, and socioeconomic status. Lifestyle factors 
137 
such as smoking, alcohol, and tea consumption are documented, given their potential influence on 
138 
nutritional status and cancer progression(Yuan et al, 2023). Medical history, including chronic 
139 
conditions, previous diagnoses, medication use, and family history of malignancies, will also be 
140 
recorded to assess genetic predispositions. 
141 
Cancer-specific data will be collected at baseline and updated at follow-ups to monitor disease 
142 
progression and treatment response. This includes pathology-confirmed diagnosis, TNM staging at 
143 
first diagnosis, and available molecular markers. The tumor burden will be reassessed at each visit, 
144 
alongside major treatments (surgery, chemotherapy, radiotherapy, targeted therapy, and 
145 
immunotherapy), with details on the type, duration, and response. Nutritional support, including 
146 
enteral or parenteral nutrition in the preceding week, will be tracked to evaluate its impact on 
147 
treatment outcomes. 
148 
Karnofsky Performance Status (KPS): The KPS evaluates a patient's ability to perform daily 
149 
activities, the presence of physical discomfort, and overall performance status, providing a 
150 
standardized measure of functional impairment(McNair et al, 2023). 
151 
Nutritional assessments 
152 
Nutritional assessments will be conducted via validated screening tools to evaluate nutritional 
153 
status, risk factors, and dietary intake patterns. Two primary tools and standardized anthropometric 
154 

 
 
8
measurements will be employed to assess malnutrition risk and severity: 
155 
Subjective Global Assessment (mPG-SGA): The mPG-SGA scoring system consists of five 
156 
sections: weight loss history, dietary intake changes, symptoms, activity and function levels, and 
157 
age. Patients' nutritional status will be categorized on the basis of scores as normal (0–2 points), 
158 
mild malnutrition (3–6 points), and moderate malnutrition (≥7 points)(Huo et al, 2023a). The 
159 
version used in this study, mPG-SGAL11, is an adapted and validated version developed for Chinese 
160 
cancer patients who  that incorporates modifications on the basis of nationwide clinical feedback 
161 
and statistical validation(Fu et al, 2022; Huo et al, 2023b). 
162 
Nutritional risk screening (NRS-2002): The NRS-2002 screening tool evaluates nutritional risk 
163 
on the basis of three components: disease severity, nutritional status, and age. A total score of ≥ 3 
164 
indicates nutritional risk, warranting nutritional intervention, whereas a score of <3 requires weekly 
165 
reassessment to monitor changes in nutritional status(Zhang et al, 2021). 
166 
Standardized anthropometric measurements: These measurements will include body mass index 
167 
(BMI), percentage of weight loss, mid-arm circumference (MAC), triceps skinfold thickness (TSF), 
168 
and handgrip strength. All measurements will be made under controlled conditions and repeated to 
169 
ensure accuracy and reliability. To ensure methodological consistency, all measurements will be 
170 
taken under fasting conditions, with patients wearing minimal clothing and no shoes. 
171 
Simple Diet Self-Assessment Tool (SDSAT): A validated self-reported dietary intake tool will be 
172 
used to estimate the dietary intake of cancer patients. Compared with 24-hour dietary recall, the 
173 
SDSAT has good reliability and validity(Jin et al, 2020). 
174 
Nutrition support in and out of the hospital: To evaluate the nutritional support of patients in and 
175 
out of the hospital, patients need to provide information on the type of nutritional support (enteral 
176 
or parenteral), formula, and supplemental dose. 
177 
Laboratory biomarkers 
178 
Biochemical markers will be analyzed to assess nutritional status, systemic inflammation, and 
179 
metabolic function. Blood samples will be collected, processed, and stored following standardized 
180 
protocols to ensure consistency among sites. 
181 
Serum ALB, prealbumin, and transferrin can be measured as indicators of protein-energy 
182 
malnutrition, providing insights into nutritional depletion and muscle wasting risk. These factors 
183 

 
 
9
will be analyzed alongside C-reactive protein (CRP) to account for inflammation-related reductions 
184 
in protein levels[30]. Inflammatory cytokines, including interleukin-6 (IL-6), interleukin-1 (IL-1), 
185 
and tumor necrosis factor-alpha (TNF-α), serve as markers of systemic inflammation and metabolic 
186 
dysregulation in patients with cancer-related malnutrition and cachexia(Keller, 2019). 
187 
Additional biochemical parameters, including hematological markers such as blood glucose, 
188 
hemoglobin, white blood cell count, neutrophil count, lymphocyte count, red blood cell count, 
189 
monocyte count, and platelet count, will be recorded where available. The liver and kidney function 
190 
markers used were AST, ALT, creatinine, blood urea nitrogen, total bilirubin, and direct bilirubin. 
191 
Lipid profile: Total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), and 
192 
low-density lipoprotein cholesterol (LDL-C)(Yang et al, 2019). 
193 
All values are based on the most recent test results closest to the evaluation. If certain parameters 
194 
are not routinely available, they will be documented as unavailable. To ensure data reliability, 
195 
assessments will follow strict quality assurance protocols, including routine calibration of analyzers, 
196 
standardized sample handling procedures, and interlaboratory validation. When feasible, blood 
197 
samples will be collected in a fasting state to minimize variability in metabolic markers. 
198 
Quality of Life & Psychosocial Factors 
199 
A comprehensive assessment of quality of life and emotional well-being will be conducted to 
200 
evaluate the psychosocial impact of cancer and its treatment on patients. Standardized and validated 
201 
measurement tools will be used across study sites to ensure the comparability and reliability of the 
202 
data. 
203 
European Organization for Research and Treatment of Cancer Quality of Life Questionnaire 
204 
(EORTC QLQ-C30): This questionnaire is used to evaluate the overall quality of life of cancer 
205 
patients. This validated instrument consists of five functional scales (physical, role, cognitive, 
206 
emotional, and social functions), three symptom scales (fatigue, pain, nausea/vomiting), six single-
207 
item symptom measures (dyspnea, appetite loss, sleep disturbance, constipation, diarrhea, and 
208 
financial difficulties), and a global quality of life scale. Each scale and single-item measure is scored 
209 
from 0 to 100, with higher scores indicating better quality of life. This tool has been widely applied 
210 
in oncology research and provides valuable insights into patients’ well-being, treatment-related side 
211 
effects, and overall functionality(Aaronson et al, 1993). 
212 

 
 
1
Hospital Anxiety and Depression Scale (HADS): This questionnaire will be used to assess anxiety 
213 
and depression levels in cancer patients. This scale consists of two subscales, measuring anxiety 
214 
(HADS-A) and depression (HADS-D), each with seven items. The total score for each subscale 
215 
ranges from 0 to 21, with the following interpretations: 0–7: normal; 8–10: mild anxiety/depression; 
216 
11–14: moderate anxiety/depression; and 15–21: severe anxiety/depression. The HADS is designed 
217 
specifically for use in hospitalized patients, as it eliminates items related to somatic symptoms that 
218 
may overlap with cancer-related physical effects, ensuring a more accurate psychological 
219 
assessment in this population(Snaith, 2003). 
220 
Physical Activity & Sleep Status 
221 
Pittsburgh Sleep Quality Index (PSQI): This scale consists of seven components (subjective sleep 
222 
quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping 
223 
medications, and daytime dysfunction), with total scores ranging from 0--21. A score of >5 indicates 
224 
poor sleep quality, which is commonly observed in cancer patients because of disease-related 
225 
symptoms, psychological stress, and treatment side effects(Divani et al, 2022). 
226 
Leisure-time physical activity levels: This questionnaire categorizes activity levels into mild, 
227 
moderate, and vigorous-intensity exercise. This assessment provides insights into physical activity 
228 
patterns and their role in cancer-related fatigue management, functional status, and long-term patient 
229 
outcomes. The questionnaire captures the frequency, duration, and intensity of activity to allow for 
230 
a detailed analysis of the impact of physical activity on patient well-being(Moore et al, 2016). 
231 
Dietary Nutrition Knowledge, Attitude, and Practice (KAP) 
232 
The KAP questionnaire is designed to assess cancer patients' nutrition-related knowledge, 
233 
attitudes, and practices. It comprises three components, namely, nutritional knowledge, dietary 
234 
attitudes, and dietary practices, with a total score ranging from 0--104, where higher scores indicate 
235 
greater nutritional awareness, more positive dietary attitudes, and healthier dietary behaviors(Tang 
236 
et al, 2023). 
237 
The nutritional knowledge section evaluates patients’ understanding of nutrient composition, 
238 
dietary recommendations, and the relationship between nutrition and cancer treatment outcomes. 
239 
The attitude section measures patients’ perceptions and beliefs regarding the importance of nutrition 
240 
in managing cancer-related symptoms and treatment side effects. The practice section assesses 
241 

 
 
1
actual dietary behaviors, including food choices, meal frequency, and adherence to nutritional 
242 
recommendations. 
243 
Short-Term & Long-Term Clinical Outcomes 
244 
Short-term clinical outcomes will focus on early posthospitalization events within 30 days of 
245 
admission, providing insights into the immediate impact of nutritional status on patient recovery 
246 
and complications. These outcomes will include 30-day survival status, intensive care unit (ICU) 
247 
admissions, length of stay, and total hospitalization costs, with a specific breakdown of nutrition-
248 
related expenses, such as enteral and parenteral nutrition. Additionally, changes in body weight 
249 
within 30 days of hospitalization will be monitored as a key indicator of early nutritional 
250 
deterioration. The incidence of complications, including infections, malnutrition, and drug-related 
251 
adverse effects, will be systematically recorded to assess treatment-related risks. These measures 
252 
provide critical data on the role of nutritional status in influencing short-term recovery, treatment 
253 
complications, and overall resource utilization. 
254 
Long-term clinical outcomes will be assessed through regular survival tracking at each scheduled 
255 
follow-up visit. Patient survival status will be documented to analyze survival trends over time and 
256 
the potential impact of nutritional interventions on overall prognosis. The follow-up evaluations will 
257 
categorize patients as alive and disease-free, alive with disease progression, or deceased, with the 
258 
cause of death recorded. 
259 
Adverse Event Recording 
260 
Adverse events (AEs) will be systematically recorded and monitored throughout the study to 
261 
ensure patient safety and data integrity. AEs are defined as any unfavorable or unintended medical 
262 
occurrence, regardless of their direct relationship with nutritional interventions or treatment. These 
263 
may include treatment-related complications, gastrointestinal distress, metabolic imbalances, 
264 
infections, allergic reactions, or other unexpected health changes. 
265 
At each follow-up visit, trained personnel will actively assess AEs by reviewing medical records 
266 
and laboratory findings, while participants will be encouraged to self-report symptoms between 
267 
visits. Serious adverse events (SAEs), including hospitalization, prolonged disability, or life-
268 
threatening conditions, will be reported following institutional and ethical guidelines. 
269 
All AEs and SAEs are classified by severity, duration, and potential causality, with standardized 
270 

 
 
1
procedures for data entry, review, and risk assessment. Necessary medical interventions or protocol 
271 
adjustments will be implemented as needed. This structured monitoring system will increase patient 
272 
safety, reduce risks, and provide insights into the impact of nutritional interventions on clinical 
273 
outcomes. 
274 
Follow-up assessments and data collection timeline 
275 
Follow-up assessments will be conducted at predefined intervals to track longitudinal changes in 
276 
nutritional status, clinical outcomes, and survival trends. In the first year, participants will be closely 
277 
monitored at 1, 2, 3, 6, and 12 months to assess early nutritional changes and treatment-related 
278 
complications. Afterward, annual follow-ups will continue for an additional four years or until death 
279 
or loss to follow-up, with a focus on survival status and disease progression. In-person hospital visits 
280 
will be prioritized for follow-up to ensure a comprehensive evaluation of nutritional status, clinical 
281 
outcomes, and quality of life (Table 1). If in-person visits are not feasible, telephone follow-ups 
282 
serve as an alternative. Research personnel will document each follow-up attempt, including the 
283 
method of contact, date, and details of the interaction. To minimize loss to follow-up, participants 
284 
missing scheduled visits were contacted up to three times via phone calls or text messages. If a 
285 
participant remains unreachable after three attempts, they will be classified as lost to follow-up, and 
286 
their last recorded assessment will be used for analysis. Any known reasons for withdrawal, 
287 
relocation, or health deterioration will be documented to ensure data transparency and completeness. 
288 
 
289 
 
290 
 
291 
 
292 
 
293 
 
294 
Variable 
SV 
Folllow-up 
1st 
month 
2nd 
month 
3rd 
month 
6th 
month 
12th 
month 
Annually 
follow-up for 
another 
4 
years  

 
 
1
Demographics & 
Clinical Data 
√ 
 
 
 
 
 
 
KPS Scoring 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
mPG-SGA 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
NRS2002 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
Standardized 
anthropometric 
measurements 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
SDSAT 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
Nutrition support in and 
out of hospital 
Nutrition support 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
Laboratory biomarkers 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
EORTC QLQ-C30 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
HADS 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
PSQI 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
Leisure-time physical 
activity levels 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
KAP Questionnaire 
√ 
 
 
 
√ 
√ 
√ 
Short-Term Clinical 
Outcome 
 
√ 
√ 
√ 
√ 
√ 
√ 
Long-term clinical 
outcomes 
 
√ 
√ 
√ 
√ 
√ 
√ 
Adverse Event 
Recording 
√ 
√ 
√ 
√ 
√ 
√ 
√ 
Table 1. Follow-up schedule. SV: screening visit; KPS: Karnofsky Performance Status; mPG-SGA: 
295 
Subjective Global Assessment; NRS-2002: Nutritional Risk Screening 2002; SDSAT: Simple Diet Self-
296 
Assessment Tool; EORTC QLQ-C30: European Organization for Research and Treatment of Cancer 
297 

 
 
1
Quality of Life Questionnaire C30; HADS: Hospital Anxiety and Depression Scale; PSQI: Pittsburgh 
298 
Sleep Quality Index; KAP : Knowledge, Attitude, and Practice. 
299 
Statistical analysis plan 
300 
Baseline characteristics are summarized as the means ± standard deviations (SDs) for normally 
301 
distributed variables, medians with interquartile ranges (IQRs) for skewed data, and percentages for 
302 
categorical variables. For group comparisons (e.g., normal vs. mild malnutrition vs. moderate 
303 
malnutrition patients), independent t tests or Mann‒Whitney U tests were used for continuous 
304 
variables, and chi‒square tests or Fisher’s exact tests were used for categorical data. 
305 
The primary outcome analysis will apply multivariate regression models, adjusting for age, sex, 
306 
cancer stage, treatment modality, socioeconomic status, and baseline Karnofsky Performance Status 
307 
(KPS). Logistic regression was used to assess binary outcomes (e.g., nutritional risk, survival), 
308 
whereas linear regression was used to evaluate continuous variables (e.g., BMI changes, weight loss 
309 
percentage). To account for repeated measures, generalized estimating equations (GEEs) model 
310 
longitudinal variations in nutritional status, biomarkers, and quality of life. 
311 
For survival analysis, Kaplan‒Meier curves were used to estimate overall survival (OS) and 
312 
progression-free survival (PFS), with log-rank tests used to compare groups. Cox proportional 
313 
hazards models were used to explore the associations between nutritional status and survival 
314 
outcomes, incorporating time-dependent covariates where applicable. 
315 
Secondary analyses will investigate associations between nutritional status and psychosocial 
316 
factors (e.g., EORTC QLQ-C30, HADS, PSQI) via paired t tests, mixed-effects models, and 
317 
correlation analyses (Spearman or Pearson, depending on distribution). 
318 
To minimize bias and confounding factors, propensity score matching (PSM) will balance 
319 
baseline differences between exposure groups. Multiple imputation will handle missing data to 
320 
prevent systematic bias, and sensitivity analyses will exclude cases with extreme values, incomplete 
321 
follow-ups, or protocol deviations. 
322 
Subgroup analyses will stratify findings by cancer type, treatment modality, and nutritional status 
323 
category. Interaction terms are included in regression models to identify potential effect 
324 
modifications, with exploratory analyses conducted if unexpected patterns arise. 
325 
By integrating multivariate modeling, survival analysis, repeated measures approaches, and 
326 

 
 
1
missing data imputation, this study ensures robust, high-quality, evidence-based insights into the 
327 
impact of nutritional status on clinical outcomes and survival in cancer patients. 
328 
Informed Consent Process 
329 
Participation in this study is voluntary, and individuals may withdraw at any time without 
330 
affecting their medical care. Before enrollment, participants and their families will receive detailed 
331 
study information, including their purpose, methodology, potential risks, and benefits. A written 
332 
informed consent form must be signed, confirming their understanding and voluntary participation. 
333 
The informed consent process will be conducted by trained research personnel, ensuring that 
334 
participants fully understand the study’s objectives and procedures; are aware of their right to 
335 
withdraw at any time without impacting their current or future medical treatment; and have the 
336 
opportunity to ask questions and receive clarifications before signing. 
337 
To accommodate diverse literacy levels, consent materials will be provided in clear, accessible 
338 
language, with verbal explanations when needed. The informed consent form included both English 
339 
and Chinese versions (Supplementary File 1). 
340 
Data Privacy & Confidentiality 
341 
This study strictly adheres to data privacy regulations, ensuring that all participant data remain 
342 
confidential. Personal identifiers will not be recorded, and all collected data will be deidentified and 
343 
stored securely in password-protected electronic databases with restricted access. Data will be used 
344 
exclusively for research purposes and will not be disclosed or shared beyond the study’s scope. 
345 
To further increase confidentiality, the following measures will be implemented: data encryption 
346 
and anonymization before analysis; restricted access to the research database, limited to authorized 
347 
personnel only; and periodic security audits to ensure compliance with institutional and regulatory 
348 
data protection policies. 
349 
Participant Rights & Withdrawal Process 
350 
Participants have the right to withdraw at any time without affecting their treatment or medical 
351 
care. If they choose to withdraw, previously collected data will remain in the research dataset unless 
352 
they explicitly request removal. In such cases, all identifiable information will be deleted while 
353 
preserving the scientific integrity of the study. 
354 

 
 
1
Discussion 
355 
The NCOM study was designed to assess the longitudinal impact of nutritional status on clinical 
356 
outcomes in cancer patients. Through systematic data collection, including demographic, medical, 
357 
and cancer-specific information, this study provides a comprehensive framework for evaluating 
358 
malnutrition, treatment response, and survival. The integration of nutritional assessments, dietary 
359 
intake data, biochemical markers, and inflammatory profiles will enable an in-depth exploration of 
360 
nutritional risk factors and their biological impact on cancer progression(Phillips et al, 2019; Wu et 
361 
al, 2023). Additionally, assessments of quality of life, psychological distress, and physical activity 
362 
will help identify modifiable behavioral factors influencing treatment outcomes(Wu et al, 2024; 
363 
Xiao et al, 2019; Zhu et al, 2024). Further statistical analyses will clarify the relationships between 
364 
nutritional status, treatment tolerance, and long-term survival. 
365 
The prevalence of malnutrition among cancer patients varies widely, with reported rates ranging 
366 
from 20% to over 70%(Beirer, 2021). The preliminary findings of this study align with this range, 
367 
highlighting the variability in cancer type, stage, and assessment methods. Research has indicated 
368 
that 28% of solid tumor patients are at high risk of malnutrition at diagnosis, with substantial 
369 
variation by cancer site(Kadakia et al, 2022). Socioeconomic status (SES) is also a crucial 
370 
determinant, as lower SES is associated with higher malnutrition risk due to disparities in living 
371 
conditions, nutrition, and healthcare access(Sandström et al, 2023). The NCOM study, designed to 
372 
integrate these factors, offers a comprehensive approach to understanding the interplay between 
373 
cancer type, nutritional status, and treatment response. These findings reinforce the importance of 
374 
personalized nutritional interventions, including oral supplements, enteral feeding, and parenteral 
375 
nutrition, which have been shown to enhance immune function, improve treatment response, and 
376 
prolong survival(Li et al, 2024). 
377 
This study also evaluated nutrition-related screening tools in oncology. Early detection of 
378 
malnutrition is critical for timely interventions, and the PG-SGA is widely recognized as a sensitive 
379 
tool for identifying patients at risk(Zhou et al, 2021). Preliminary baseline data revealed that 68.05% 
380 
of patients were classified as at nutritional risk by the mPG-SGA, whereas 23.34% were identified 
381 
via the NRS-2002, highlighting discrepancies in sensitivity between screening tools. These findings 
382 
align with previous findings suggesting the superiority of the PG-SGA in detecting malnutrition 
383 

 
 
1
risk(Chen et al, 2023). 
384 
From a clinical perspective, the NCOM study will also provide more information for the 
385 
improvement of patients' malnutrition and the effects of antitumor-related treatment. Malnutrition 
386 
is associated with poor treatment tolerance, increased toxicity, and reduced survival rates. 
387 
Malnourished patients experience higher rates of treatment-related complications, including 
388 
chemotherapy-related gastrointestinal toxicity and myelosuppression, often leading to dose 
389 
reductions or treatment delays(Li et al, 2024). Another study by the authors confirmed that 
390 
malnutrition exacerbates chemotherapy-related side effects, emphasizing the need for good baseline 
391 
nutritional status to mitigate toxicity and improve survival outcomes(Zhou et al, 2025). Addressing 
392 
nutritional deficits early is crucial for optimizing patient well-being and enhancing treatment 
393 
efficacy. 
394 
Our study has several strengths. As a prospective, multicenter cohort, it enables longitudinal 
395 
assessment of nutritional status with comprehensive data collection, integrating validated screening 
396 
tools, anthropometric measures, biochemical markers, and psychosocial assessments. This robust 
397 
methodology allows for a detailed understanding of the link between nutrition, treatment response, 
398 
and long-term survival. However, some limitations exist. First, self-reported dietary assessments 
399 
may introduce recall bias, but this bias is partially mitigated by objective measures such as 
400 
biochemical markers and anthropometry. Second, loss to follow-up is anticipated due to disease 
401 
progression or dropout, although conservative sample size calculations account for this(Reeves et 
402 
al, 2007; Schwedhelm et al, 2016). Third, the preliminary study is geographically limited to 
403 
hospitals in Xi’an, potentially restricting generalizability. However, Xi’an is a major regional 
404 
referral center attracting diverse cancer populations from Northwest China, which may increase its 
405 
representativeness(Chen et al, 2022). Finally, the study does not include mechanistic investigations, 
406 
such as molecular or metabolic pathway analyses, limiting its ability to explore the biological 
407 
underpinnings of malnutrition in cancer progression. Future research should incorporate biomarker-
408 
driven mechanistic studies to address this gap and further elucidate the impact of malnutrition on 
409 
cancer outcomes. 
410 
Conclusion 
411 
The NCOM study explores the impact of nutritional status on cancer outcomes through a 
412 

 
 
1
comprehensive, multicenter cohort. Preliminary findings highlight the high prevalence of nutritional 
413 
risk and the importance of early detection. The findings of this study will inform evidence-based 
414 
guidelines to optimize oncological care and improve patient outcomes. 
415 
Acknowledgments 
416 
We sincerely thank Xi’an Jiaotong University for providing essential support for this study. We 
417 
are also grateful to all participating patients, healthcare providers from the involved hospitals, as 
418 
well as the data collection and supervision teams for their commitment and contributions to the 
419 
success of this research. 
420 
Author Contributions 
421 
HeXiang Yang and Yaxin Yu contributed equally to this work. They participated in the study 
422 
design, data acquisition, analysis, and manuscript drafting. Haige Cao, Jinglin Li, Feng Liu, Jiahe 
423 
Zhou, and Yuluyuan Tian assisted in data collection and preliminary analysis. Yilan Li contributed 
424 
to data interpretation and manuscript revision. Xiaoqin Luo* supervised the study, provided critical 
425 
revisions, and approved the final manuscript. 
426 
Ethical Approval and consent to participate 
427 
All methods and procedures were conducted in accordance with relevant guidelines and 
428 
regulations, in line with the principles of the Declaration of Helsinki. Ethical approval for this study 
429 
was obtained from the Institutional Review Board of Xi’an Jiaotong University (Approval No. 
430 
2022-1373). The study was registered at ClinicalTrials.gov (NCT06219083). Additionally, all 
431 
participants were fully informed of the purpose and potential benefits of the study, and written 
432 
informed consent was obtained prior to participation. Confidentiality of participant information was 
433 
strictly maintained throughout the study. 
434 
Data availability statement 
435 
The authors declare that all the other data supporting the findings of this study are available within 
436 
the article, its Supplementary Information files or from the corresponding author upon reasonable 
437 
request. 
438 
Competing Interests 
439 
All the authors disclosed no relevant relationships. 
440 
Funding information 
441 
This work was funded by the Natural Science Basic Research Program of Shaanxi Province 
442 
(Program No. 2020JQ-460). 
443 

 
 
1
References 
444 
Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, Filiberti A, Flechtner H, 
445 
Fleishman SB, de Haes JC (1993) The European Organization for Research and Treatment of Cancer 
446 
QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl 
447 
Cancer Inst 85: 365–376, doi:10.1093/jnci/85.5.365. 
448 
Arends J, Bachmann P, Baracos V, Barthelemy N, Bertz H, Bozzetti F, Fearon K, Hütterer E, 
449 
Isenring E, Kaasa S, Krznaric Z, Laird B, Larsson M, Laviano A, Mühlebach S, Muscaritoli M, 
450 
Oldervoll L, Ravasco P, Solheim T, Strasser F, de van der Schueren M, Preiser J-C (2017) ESPEN 
451 
guidelines 
on 
nutrition 
in 
cancer 
patients. 
Clin 
Nutr 
Edinb 
Scotl 
36: 
11–48, 
452 
doi:10.1016/j.clnu.2016.07.015. 
453 
Beirer A (2021) Malnutrition and cancer, diagnosis and treatment. Memo - Mag Eur Med Oncol 
454 
14: 168–173, doi:10.1007/s12254-020-00672-3. 
455 
Bossi 
P, 
Delrio 
P, 
Mascheroni 
A, 
Zanetti 
M 
(2021) 
The 
Spectrum 
of 
456 
Malnutrition/Cachexia/Sarcopenia in Oncology According to Different Cancer Types and Settings: 
457 
A Narrative Review. Nutrients 13: 1980, doi:10.3390/nu13061980. 
458 
Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A Global cancer 
459 
statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 
460 
countries. CA Cancer J Clin n/a: doi:https://doi.org/10.3322/caac.21834. 
461 
Cao W, Chen H-D, Yu Y-W, Li N, Chen W-Q (2021) Changing profiles of cancer burden 
462 
worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chin Med J (Engl) 
463 
134: 783–791, doi:10.1097/CM9.0000000000001474. 
464 
Chen N, Zhang X-Y, Ma L-L, Zhao G-D, Yan Y-X (2022) Trends of cancer mortality in Xi’an 
465 
City, China: 2005–2020. J Cancer Res Clin Oncol 148: 2781–2792, doi:10.1007/s00432-022-
466 
04046-6. 
467 
Chen X, Liu X, Ji W, Zhao Y, He Y, Liu Y, Li Q, Shi H, Cui J (2023) The PG-SGA outperforms 
468 
the NRS 2002 for nutritional risk screening in cancer patients: a retrospective study from China. 
469 
Front Nutr 10: doi:10.3389/fnut.2023.1272420. 
470 
Divani A, Heidari ME, Ghavampour N, Parouhan A, Ahmadi S, Narimani Charan O, Shahsavari 
471 
H (2022) Effect of cancer treatment on sleep quality in cancer patients: A systematic review and 
472 
meta-analysis of Pittsburgh Sleep Quality Index. Support Care Cancer Off J Multinatl Assoc 
473 
Support Care Cancer 30: 4687–4697, doi:10.1007/s00520-021-06767-9. 
474 
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP (2007) 
475 
Strengthening the reporting of observational studies in epidemiology (STROBE) statement: 
476 
guidelines 
for 
reporting 
observational 
studies. 
BMJ 
335: 
806–808, 
477 
doi:10.1136/bmj.39335.541782.AD. 
478 
Fu Z, Zhang R, Wang K-H, Cong M-H, Li T, Weng M, Guo Z-Q, Li Z-N, Li Z-P, Wang C, Xu H-
479 

 
 
2
X, Song C-H, Zhuang C-L, Zhang Q, Li W, Shi H-P, INSCOC Study Group (2022) Development 
480 
and validation of a Modified Patient-Generated Subjective Global Assessment as a nutritional 
481 
assessment tool in cancer patients. J Cachexia Sarcopenia Muscle 13: 343–354, 
482 
doi:10.1002/jcsm.12872. 
483 
Garutti M, Noto C, Pastò B, Cucciniello L, Alajmo M, Casirati A, Pedrazzoli P, Caccialanza R, 
484 
Puglisi F (2023) Nutritional Management of Oncological Symptoms: A Comprehensive Review. 
485 
Nutrients 15: 5068, doi:10.3390/nu15245068. 
486 
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG (2009) Research electronic data 
487 
capture (REDCap)--a metadata-driven methodology and workflow process for providing 
488 
translational 
research 
informatics 
support. 
J 
Biomed 
Inform 
42: 
377–381, 
489 
doi:10.1016/j.jbi.2008.08.010. 
490 
Hébuterne X, Lemarié E, Michallet M, de Montreuil CB, Schneider SM, Goldwasser F (2014) 
491 
Prevalence of malnutrition and current use of nutrition support in patients with cancer. JPEN J 
492 
Parenter Enteral Nutr 38: 196–204, doi:10.1177/0148607113502674. 
493 
Holdoway A, Donald M, Hodge A (2023) Supporting people to manage nutrition throughout their 
494 
cancer journey. Cancer Nurs Pract 22: 34–42, doi:10.7748/cnp.2023.e1830. 
495 
Huo Z, Chong F, Yin L, Li N, Liu J, Zhang M, Guo J, Fan Y, Zhang L, Lin X, Zhang H, Shi M, 
496 
He X, Lu Z, Fu Z, Guo Z, Li Z, Zhou F, Chen Z, Ma H, Zhou C, Chen J, Wu X, Li T, Zhao Q, Weng 
497 
M, Yao Q, Liu M, Yu H, Zheng J, Cui J, Li W, Song C, Shi H, Xu H, Investigation on Nutrition 
498 
Status and Clinical Outcome of Common Cancers (INSCOC) Group (2023a) Comparison of the 
499 
performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and 
500 
predicting survival among lung cancer patients: A multicenter study. Clin Nutr Edinb Scotl 42: 
501 
1048–1058, doi:10.1016/j.clnu.2023.04.021. 
502 
Huo Z, Chong F, Yin L, Li N, Liu J, Zhang M, Guo J, Fan Y, Zhang L, Lin X, Zhang H, Shi M, 
503 
He X, Lu Z, Fu Z, Guo Z, Li Z, Zhou F, Chen Z, Ma H, Zhou C, Chen J, Wu X, Li T, Zhao Q, Weng 
504 
M, Yao Q, Liu M, Yu H, Zheng J, Cui J, Li W, Song C, Shi H, Xu H, Investigation on Nutrition 
505 
Status and Clinical Outcome of Common Cancers (INSCOC) Group (2023b) Comparison of the 
506 
performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and 
507 
predicting survival among lung cancer patients: A multicenter study. Clin Nutr Edinb Scotl 42: 
508 
1048–1058, doi:10.1016/j.clnu.2023.04.021. 
509 
Jin S, Cong M, Zhang L, Wang Y, Qin D, Lu Q (2020) Validation of a simple diet self-assessment 
510 
tool (SDSAT) in head and neck cancer patients undergoing radiotherapy. Eur J Oncol Nurs Off J 
511 
Eur Oncol Nurs Soc 44: 101702, doi:10.1016/j.ejon.2019.101702. 
512 
Kadakia KC, Symanowski JT, Aktas A, Szafranski ML, Salo JC, Meadors PL, Walsh D (2022) 
513 
Malnutrition risk at solid tumor diagnosis: the malnutrition screening tool in a large US cancer 
514 
institute. Support Care Cancer 30: 2237–2244, doi:10.1007/s00520-021-06612-z. 
515 
Kaegi-Braun N, Schuetz P, Mueller B, Kutz A (2021) Association of Nutritional Support With 
516 

 
 
2
Clinical Outcomes in Malnourished Cancer Patients: A Population-Based Matched Cohort Study. 
517 
Front Nutr 7: 603370, doi:10.3389/fnut.2020.603370. 
518 
Keller U (2019) Nutritional Laboratory Markers in Malnutrition. J Clin Med 8: 775, 
519 
doi:10.3390/jcm8060775. 
520 
Kipouros M, Vamvakari K, Kalafati IP, Evangelou I, Kasti AN, Kosti RI, Androutsos O (2023) 
521 
The Level of Adherence to the ESPEN Guidelines for Energy and Protein Intake Prospectively 
522 
Influences Weight Loss and Nutritional Status in Patients with Cancer. Nutrients 15: 4232, 
523 
doi:10.3390/nu15194232. 
524 
Li C, Zhang S, Liu Y, Hu T, Wang C (2024) Effects of nutritional interventions on cancer patients 
525 
receiving neoadjuvant chemoradiotherapy: a meta-analysis of randomized controlled trials. Support 
526 
Care Cancer Off J Multinatl Assoc Support Care Cancer 32: 583, doi:10.1007/s00520-024-08780-
527 
0. 
528 
Liu C, Lu Z, Li Z, Xu J, Cui H, Zhu M (2021) Influence of Malnutrition According to the GLIM 
529 
Criteria on the Clinical Outcomes of Hospitalized Patients With Cancer. Front Nutr 8: 774636, 
530 
doi:10.3389/fnut.2021.774636. 
531 
McNair KM, Zeitlin D, Slivka AM, Lequerica AH, Stubblefield MD (2023) Translation of 
532 
Karnofsky Performance Status (KPS) for use in inpatient cancer rehabilitation. PM R 15: 65–68, 
533 
doi:10.1002/pmrj.12741. 
534 
Moore SC, Lee I-M, Weiderpass E, Campbell PT, Sampson JN, Kitahara CM, Keadle SK, Arem 
535 
H, Berrington de Gonzalez A, Hartge P, Adami H-O, Blair CK, Borch KB, Boyd E, Check DP, 
536 
Fournier A, Freedman ND, Gunter M, Johannson M, Khaw K-T, Linet MS, Orsini N, Park Y, Riboli 
537 
E, Robien K, Schairer C, Sesso H, Spriggs M, Van Dusen R, Wolk A, Matthews CE, Patel AV (2016) 
538 
Association of Leisure-Time Physical Activity With Risk of 26 Types of Cancer in 1.44 Million 
539 
Adults. JAMA Intern Med 176: 816–825, doi:10.1001/jamainternmed.2016.1548. 
540 
Muscaritoli M, Arends J, Aapro M (2019) From guidelines to clinical practice: a roadmap for 
541 
oncologists for nutrition therapy for cancer patients. Ther Adv Med Oncol 11: 1758835919880084, 
542 
doi:10.1177/1758835919880084. 
543 
Nissim M, Rottenberg Y, Karniel N, Ratzon NZ (2024) Effects of aquatic exercise program versus 
544 
on-land exercise program on cancer-related fatigue, neuropathy, activity and participation, quality 
545 
of life, and return to work for cancer patients: study protocol for a randomized controlled trial. BMC 
546 
Complement Med Ther 24: 74, doi:10.1186/s12906-024-04367-8. 
547 
Phillips CM, Chen L-W, Heude B, Bernard JY, Harvey NC, Duijts L, Mensink-Bout SM, 
548 
Polanska K, Mancano G, Suderman M, Shivappa N, Hébert JR (2019) Dietary Inflammatory Index 
549 
and 
Non-Communicable 
Disease 
Risk: A 
Narrative 
Review. 
Nutrients 
11: 
1873, 
550 
doi:10.3390/nu11081873. 
551 
Qiu H, Cao S, Xu R (2021) Cancer incidence, mortality, and burden in China: a time-trend 
552 
analysis and comparison with the United States and United Kingdom based on the global 
553 

 
 
2
epidemiological data released in 2020. Cancer Commun Lond Engl 41: 1037–1048, 
554 
doi:10.1002/cac2.12197. 
555 
Rasschaert M, Vandecandelaere P, Marechal S, D’hondt R, Vulsteke C, Mailleux M, De Roock 
556 
W, Van Erps J, Himpe U, De Man M, Mertens G, Ysebaert D (2024) Malnutrition prevalence in 
557 
cancer patients in Belgium: The ONCOCARE study. Support Care Cancer 32: 135, 
558 
doi:10.1007/s00520-024-08324-6. 
559 
Reeves GK, Pirie K, Beral V, Green J, Spencer E, Bull D (2007) Cancer incidence and mortality 
560 
in relation to body mass index in the Million Women Study: cohort study. BMJ 335: 1134, 
561 
doi:10.1136/bmj.39367.495995.AE. 
562 
Riboli E (2001) The European Prospective Investigation into Cancer and Nutrition (EPIC): Plans 
563 
and Progress. J Nutr 131: 170S-175S, doi:10.1093/jn/131.1.170S. 
564 
Sandström N, Johansson M, Jekunen A, Andersén H (2023) Socioeconomic status and lifestyle 
565 
patterns in the most common cancer types-community-based research. BMC Public Health 23: 1722, 
566 
doi:10.1186/s12889-023-16677-6. 
567 
Schuetz P, Fehr R, Baechli V, Geiser M, Deiss M, Gomes F, Kutz A, Tribolet P, Bregenzer T, 
568 
Braun N, Hoess C, Pavlicek V, Schmid S, Bilz S, Sigrist S, Brändle M, Benz C, Henzen C, Mattmann 
569 
S, Thomann R, Brand C, Rutishauser J, Aujesky D, Rodondi N, Donzé J, Stanga Z, Mueller B (2019) 
570 
Individualised nutritional support in medical inpatients at nutritional risk: a randomised clinical trial. 
571 
Lancet Lond Engl 393: 2312–2321, doi:10.1016/S0140-6736(18)32776-4. 
572 
Schwedhelm C, Boeing H, Hoffmann G, Aleksandrova K, Schwingshackl L (2016) Effect of diet 
573 
on mortality and cancer recurrence among cancer survivors: a systematic review and meta-analysis 
574 
of cohort studies. Nutr Rev 74: 737–748, doi:10.1093/nutrit/nuw045. 
575 
Snaith RP (2003) The Hospital Anxiety And Depression Scale. Health Qual Life Outcomes 1: 29, 
576 
doi:10.1186/1477-7525-1-29. 
577 
Tang H, Wang R, Yan P, Zhang W, Yang F, Guo S, Li T, Yi L, Bai X, Lin S, Zhang Y, Shang L 
578 
(2023) Dietary Behavior and Its Association with Nutrition Literacy and Dietary Attitude Among 
579 
Breast Cancer Patients Treated with Chemotherapy: A Multicenter Survey of Hospitals in China. 
580 
Patient Prefer Adherence 17: 1407–1419, doi:10.2147/ppa.s413542. 
581 
Webb N, Fricke J, Hancock E, Trueman D, Ghosh S, Winstone J, Miners A, Shepelev J, Valle JW 
582 
(2020) The clinical and cost-effectiveness of supplemental parenteral nutrition in oncology. ESMO 
583 
Open 5: e000709, doi:10.1136/esmoopen-2020-000709. 
584 
Wu J, Yu C, Shivappa N, Hébert JR, Xu X (2023) Dietary inflammatory index and renal cancer 
585 
risk: a prospective study. Food Funct 14: 9287–9294, doi:10.1039/d3fo02158k. 
586 
Wu Y, Xu J, Gao Y, Zheng J (2024) The relationship between health behaviors and quality of life: 
587 
the mediating roles of activities of daily living and psychological distress. Front Public Health 12: 
588 
doi:10.3389/fpubh.2024.1398361. 
589 

 
 
2
Xiao Y, Wang H, Zhang T, Ren X (2019) Psychosocial predictors of physical activity and health-
590 
related quality of life among Shanghai working adults. Health Qual Life Outcomes 17: 72, 
591 
doi:10.1186/s12955-019-1145-6. 
592 
Yang S, Zhao K, Ding X, Jiang H, Lu H (2019) Prognostic Significance of Hematological 
593 
Markers for Patients with Nasopharyngeal Carcinoma: A Meta-analysis. J Cancer 10: 2568–2577, 
594 
doi:10.7150/jca.26770. 
595 
Ye Y, Zeng K, Qin L, Luo J, Liu S, Miao J, Liang J, Yu Y, Zhao M, Zhang L (2024) Differential 
596 
Characteristics of Fatigue-Pain-Sleep Disturbance-Depression Symptom Cluster and Influencing 
597 
Factors of Patients With Advanced Cancer During Treatment: A Latent Class Analysis. Cancer Nurs 
598 
doi:10.1097/NCC.0000000000001316. 
599 
Yuan S, Chen J, Ruan X, Sun Y, Zhang K, Wang X, Li X, Gill D, Burgess S, Giovannucci E, 
600 
Larsson SC (2023) Smoking, alcohol consumption, and 24 gastrointestinal diseases: Mendelian 
601 
randomization analysis. eLife 12: e84051, doi:10.7554/eLife.84051. 
602 
Zhang Z, Wan Z, Zhu Y, Zhang L, Zhang L, Wan H (2021) Prevalence of malnutrition comparing 
603 
NRS2002, MUST, and PG-SGA with the GLIM criteria in adults with cancer: A multi-center study. 
604 
Nutr Burbank Los Angel Cty Calif 83: 111072, doi:10.1016/j.nut.2020.111072. 
605 
Zhou H-J, Deng L-J, Wang T, Chen J-X, Jiang S-Z, Yang L, Liu F, Weng M-H, Hu J-W, Tan J-Y 
606 
(2021) Clinical practice guidelines for the nutritional risk screening and assessment of cancer 
607 
patients: a systematic quality appraisal using the AGREE II instrument. Support Care Cancer 29: 
608 
2885–2893, doi:10.1007/s00520-021-06094-z. 
609 
Zhou Q, Yang H, Wang X, Wang L, Yan X, Zhang B, Ma X, Li G, Li J, Zhang J, Yan Z, Bao N, 
610 
Li C, Ge P, Liu J, Luo X (2025) The dynamic effects of nutritional status on chemotherapy-related 
611 
toxicity in patients with non-Hodgkin’s lymphoma. Eur J Clin Nutr 1–8, doi:10.1038/s41430-025-
612 
01565-6. 
613 
Zhu C, Lian Z, Arndt V, Thong MSY (2024) Combined healthy lifestyle factors and psychosocial 
614 
outcomes among cancer survivors: a systematic review and meta-analysis. J Cancer Surviv 
615 
doi:10.1007/s11764-024-01705-0. 
616 
 
617