A cross-sectional survey study on the correlation analysis of nutritional status and intestinal flora in patients with esophageal cancer Article Swipe
Liya Li
,
Xinsheng Zhang
,
Xiang Huang
,
Zhao Liu
,
Lu Liu
,
Lv XiuMing
,
Ye Li
,
Jing Chen
,
Keming Zhang
,
Wang HongChi
,
Jing Xia
,
Cong Yang
,
Cui Xiu
,
Long HongBo
,
You ShuQin
,
Fang Liu
,
Yinghua Liu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3389/fnut.2024.1424039
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3389/fnut.2024.1424039
Objective This study aims to examine the nutritional status of individuals diagnosed with esophageal cancer and compare the nutritional indicators and intestinal flora between malnourished and non-malnourished patients. The findings aim to contribute to the early prevention of malnutrition and the development of interventions targeting the intestinal flora to treat esophageal cancer. Methods An 80-patient sample of hospitalized individuals with esophageal cancer was selected from the radiotherapy department of our hospital between July 2021 and July 2022 to evaluate NRS2002 scores and PG-SGA scores. This cross-sectional analysis aimed to examine the disparities in dietary nutrient intake, blood indicators, body composition, and fecal intestinal flora between malnourished and non-malnourished patients with esophageal cancer. Additionally, we randomly selected 40 cases to predict and analyze the relationship between intestinal flora and malnutrition. Results The incidence of nutritional risk and malnutrition in patients with esophageal cancer was 62.5% and 60%, respectively. The low intake of carbohydrates and dietary fiber in the malnutrition group was statistically significant compared to those in the non-malnutrition group ( P < 0.05). The albumin (ALB) level was lower in the malnutrition group than in the non-malnutrition group, while the C-reactive protein (CRP) level was higher; these differences were also statistically significant ( P < 0.05). The basal metabolic rate, phase angle, body cell mass, muscle mass, skeletal muscle index, and fat-free mass index in the malnutrition group all decreased compared to the non-malnutrition group. The extracellular water/total body water was higher than that in the non-malnutrition group, which was also statistically significant ( P < 0.05). As shown by 16S rDNA sequencing of fecal intestinal flora, there was no significant difference in α and β diversity between the malnutrition and non-malnutrition groups; at the genus level, significant differences were observed for Selimonas, Clostridioides, Dielma, Lactobacillus, and [Eubacterium]_siraeum_group. However, Dielma, Sellimonas, and Clostridioides were significantly lower in the malnutrition group than in the non-malnutrition group, while Anaerococcus, Atopobium, Eubacterium_siraeum_group, and Lactobacillus were significantly higher in the malnutrition group. Correlation analysis between different genera and clinical indicators showed that Lactobacillus was positively correlated with ALB, dietary energy, intracellular water/total body water (ICW/TBW), phase angle (PA), muscle mass (MM), skeletal muscle mass (SMM), body cell mass (BCM), basal metabolic rate (BMR), appendicular skeletal muscle mass (ASMM), total body water (TBW), fat-free mass index (FFMI), skeletal muscle index (SMI), fat-free mass (FFM), Weight, body mass index (BMI) ( r > 0, P < 0.05), but negatively correlated with PG-SGA score, NRS2002 score, and extracellular water/total body water (ECW/TBW) ( r < 0 , P < 0.05). Based on PG-SGA, there was only a low accuracy for identifying nutrient deficiency (most areas under curve (AUC) values fell within 0.5 to 0.7, or even lower), with Lachnoclostridium's AUC being 0.688 (CI = 0.518–0.858) and Lactobacillus_salivarius_g_Lactobacillus's AUC being 0.257 (CI = 0.098–0.416). A KEGG functional analysis based on 16S data indicated potential differences affecting glucose metabolism pathways and the synthesis or division of DNA, influencing the onset, development, and prognosis of esophageal cancer patients. Conclusion Esophageal cancer patients are more likely to be malnourished. The nutritional status of these patients is closely linked to the intake of carbohydrates and fiber, albumin levels, inflammation levels, and lean body mass. Furthermore, the patient's intestinal flora composition plays a significant role in their nutritional well-being. Consequently, modulating the intestinal flora holds promise as a potential therapeutic approach for addressing malnutrition in esophageal cancer patients. Clinical trial registration ChiCTR2100048141
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fnut.2024.1424039
- OA Status
- gold
- Cited By
- 5
- References
- 63
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400581304
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4400581304Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fnut.2024.1424039Digital Object Identifier
- Title
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A cross-sectional survey study on the correlation analysis of nutritional status and intestinal flora in patients with esophageal cancerWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-12Full publication date if available
- Authors
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Liya Li, Xinsheng Zhang, Xiang Huang, Zhao Liu, Lu Liu, Lv XiuMing, Ye Li, Jing Chen, Keming Zhang, Wang HongChi, Jing Xia, Cong Yang, Cui Xiu, Long HongBo, You ShuQin, Fang Liu, Yinghua LiuList of authors in order
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https://doi.org/10.3389/fnut.2024.1424039Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.3389/fnut.2024.1424039Direct OA link when available
- Concepts
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Malnutrition, Medicine, Esophageal cancer, Internal medicine, Gastroenterology, Body mass index, Cancer, Incidence (geometry), Wasting, Cross-sectional study, Pathology, Optics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 5Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.there | 267, 426 |
| abstract_inverted_index.these | 196, 512 |
| abstract_inverted_index.those | 164 |
| abstract_inverted_index.total | 374 |
| abstract_inverted_index.treat | 49 |
| abstract_inverted_index.trial | 566 |
| abstract_inverted_index.under | 438 |
| abstract_inverted_index.water | 239, 349, 376, 413 |
| abstract_inverted_index.which | 248 |
| abstract_inverted_index.while | 188, 315 |
| abstract_inverted_index.(BCM), | 364 |
| abstract_inverted_index.(BMR), | 368 |
| abstract_inverted_index.(FFM), | 388 |
| abstract_inverted_index.(SMI), | 385 |
| abstract_inverted_index.(SMM), | 360 |
| abstract_inverted_index.(TBW), | 377 |
| abstract_inverted_index.0.05), | 400 |
| abstract_inverted_index.0.05). | 172, 205, 256, 422 |
| abstract_inverted_index.PG-SGA | 82, 405 |
| abstract_inverted_index.angle, | 211 |
| abstract_inverted_index.cancer | 14, 61, 141, 496, 500, 563 |
| abstract_inverted_index.fiber, | 523 |
| abstract_inverted_index.flora, | 266 |
| abstract_inverted_index.genera | 332 |
| abstract_inverted_index.group, | 187, 247, 314 |
| abstract_inverted_index.group. | 234, 327 |
| abstract_inverted_index.higher | 241, 323 |
| abstract_inverted_index.index, | 219 |
| abstract_inverted_index.intake | 149, 519 |
| abstract_inverted_index.level, | 286 |
| abstract_inverted_index.likely | 504 |
| abstract_inverted_index.linked | 516 |
| abstract_inverted_index.muscle | 215, 218, 354, 358, 371, 383 |
| abstract_inverted_index.onset, | 490 |
| abstract_inverted_index.sample | 55 |
| abstract_inverted_index.score, | 406, 408 |
| abstract_inverted_index.scores | 80 |
| abstract_inverted_index.showed | 336 |
| abstract_inverted_index.status | 8, 510 |
| abstract_inverted_index.values | 441 |
| abstract_inverted_index.within | 443 |
| abstract_inverted_index.(ASMM), | 373 |
| abstract_inverted_index.(FFMI), | 381 |
| abstract_inverted_index.Dielma, | 294, 299 |
| abstract_inverted_index.Methods | 52 |
| abstract_inverted_index.NRS2002 | 79, 407 |
| abstract_inverted_index.PG-SGA, | 425 |
| abstract_inverted_index.Results | 129 |
| abstract_inverted_index.Weight, | 389 |
| abstract_inverted_index.albumin | 174, 524 |
| abstract_inverted_index.analyze | 121 |
| abstract_inverted_index.between | 23, 71, 104, 124, 277, 330 |
| abstract_inverted_index.cancer. | 51, 111 |
| abstract_inverted_index.closely | 515 |
| abstract_inverted_index.compare | 16 |
| abstract_inverted_index.dietary | 93, 153, 344 |
| abstract_inverted_index.energy, | 345 |
| abstract_inverted_index.examine | 5, 89 |
| abstract_inverted_index.glucose | 478 |
| abstract_inverted_index.groups; | 282 |
| abstract_inverted_index.higher; | 195 |
| abstract_inverted_index.intake, | 95 |
| abstract_inverted_index.levels, | 525, 527 |
| abstract_inverted_index.lower), | 449 |
| abstract_inverted_index.predict | 119 |
| abstract_inverted_index.promise | 552 |
| abstract_inverted_index.protein | 191 |
| abstract_inverted_index.scores. | 83 |
| abstract_inverted_index.&gt; | 396 |
| abstract_inverted_index.&lt; | 171, 204, 255, 399, 417, 421 |
| abstract_inverted_index.Clinical | 565 |
| abstract_inverted_index.However, | 298 |
| abstract_inverted_index.accuracy | 431 |
| abstract_inverted_index.analysis | 86, 329, 469 |
| abstract_inverted_index.approach | 557 |
| abstract_inverted_index.clinical | 334 |
| abstract_inverted_index.compared | 162, 230 |
| abstract_inverted_index.division | 485 |
| abstract_inverted_index.evaluate | 78 |
| abstract_inverted_index.fat-free | 221, 378, 386 |
| abstract_inverted_index.findings | 29 |
| abstract_inverted_index.hospital | 70 |
| abstract_inverted_index.nutrient | 94, 434 |
| abstract_inverted_index.observed | 290 |
| abstract_inverted_index.pathways | 480 |
| abstract_inverted_index.patients | 108, 138, 501, 513 |
| abstract_inverted_index.randomly | 114 |
| abstract_inverted_index.selected | 63, 115 |
| abstract_inverted_index.skeletal | 217, 357, 370, 382 |
| abstract_inverted_index.(ECW/TBW) | 414 |
| abstract_inverted_index.Objective | 0 |
| abstract_inverted_index.affecting | 477 |
| abstract_inverted_index.decreased | 229 |
| abstract_inverted_index.diagnosed | 11 |
| abstract_inverted_index.different | 331 |
| abstract_inverted_index.diversity | 276 |
| abstract_inverted_index.incidence | 131 |
| abstract_inverted_index.indicated | 474 |
| abstract_inverted_index.metabolic | 208, 366 |
| abstract_inverted_index.patient's | 534 |
| abstract_inverted_index.patients. | 27, 497, 564 |
| abstract_inverted_index.potential | 475, 555 |
| abstract_inverted_index.prognosis | 493 |
| abstract_inverted_index.synthesis | 483 |
| abstract_inverted_index.targeting | 44 |
| abstract_inverted_index.(ICW/TBW), | 350 |
| abstract_inverted_index.80-patient | 54 |
| abstract_inverted_index.Atopobium, | 317 |
| abstract_inverted_index.C-reactive | 190 |
| abstract_inverted_index.Conclusion | 498 |
| abstract_inverted_index.Esophageal | 499 |
| abstract_inverted_index.Selimonas, | 292 |
| abstract_inverted_index.addressing | 559 |
| abstract_inverted_index.contribute | 32 |
| abstract_inverted_index.correlated | 341, 403 |
| abstract_inverted_index.deficiency | 435 |
| abstract_inverted_index.department | 67 |
| abstract_inverted_index.difference | 271 |
| abstract_inverted_index.esophageal | 13, 50, 60, 110, 140, 495, 562 |
| abstract_inverted_index.functional | 468 |
| abstract_inverted_index.indicators | 19, 335 |
| abstract_inverted_index.intestinal | 21, 46, 102, 125, 265, 535, 549 |
| abstract_inverted_index.metabolism | 479 |
| abstract_inverted_index.modulating | 547 |
| abstract_inverted_index.negatively | 402 |
| abstract_inverted_index.positively | 340 |
| abstract_inverted_index.prevention | 36 |
| abstract_inverted_index.sequencing | 262 |
| abstract_inverted_index.Correlation | 328 |
| abstract_inverted_index.Sellimonas, | 300 |
| abstract_inverted_index.composition | 537 |
| abstract_inverted_index.development | 41 |
| abstract_inverted_index.differences | 197, 288, 476 |
| abstract_inverted_index.disparities | 91 |
| abstract_inverted_index.identifying | 433 |
| abstract_inverted_index.indicators, | 97 |
| abstract_inverted_index.individuals | 10, 58 |
| abstract_inverted_index.influencing | 488 |
| abstract_inverted_index.nutritional | 7, 18, 133, 509, 544 |
| abstract_inverted_index.significant | 161, 201, 252, 270, 287, 540 |
| abstract_inverted_index.therapeutic | 556 |
| abstract_inverted_index.water/total | 237, 347, 411 |
| abstract_inverted_index.well-being. | 545 |
| abstract_inverted_index.Furthermore, | 532 |
| abstract_inverted_index.appendicular | 369 |
| abstract_inverted_index.composition, | 99 |
| abstract_inverted_index.development, | 491 |
| abstract_inverted_index.hospitalized | 57 |
| abstract_inverted_index.inflammation | 526 |
| abstract_inverted_index.malnourished | 24, 105 |
| abstract_inverted_index.malnutrition | 38, 136, 157, 181, 226, 279, 308, 326, 560 |
| abstract_inverted_index.radiotherapy | 66 |
| abstract_inverted_index.registration | 567 |
| abstract_inverted_index.relationship | 123 |
| abstract_inverted_index.Additionally, | 112 |
| abstract_inverted_index.Anaerococcus, | 316 |
| abstract_inverted_index.Consequently, | 546 |
| abstract_inverted_index.Lactobacillus | 320, 338 |
| abstract_inverted_index.carbohydrates | 151, 521 |
| abstract_inverted_index.extracellular | 236, 410 |
| abstract_inverted_index.interventions | 43 |
| abstract_inverted_index.intracellular | 346 |
| abstract_inverted_index.malnourished. | 507 |
| abstract_inverted_index.malnutrition. | 128 |
| abstract_inverted_index.respectively. | 146 |
| abstract_inverted_index.significantly | 304, 322 |
| abstract_inverted_index.statistically | 160, 200, 251 |
| abstract_inverted_index.0.518–0.858) | 457 |
| abstract_inverted_index.Clostridioides | 302 |
| abstract_inverted_index.Lactobacillus, | 295 |
| abstract_inverted_index.0.098–0.416). | 465 |
| abstract_inverted_index.Clostridioides, | 293 |
| abstract_inverted_index.cross-sectional | 85 |
| abstract_inverted_index.ChiCTR2100048141 | 568 |
| abstract_inverted_index.non-malnourished | 26, 107 |
| abstract_inverted_index.non-malnutrition | 167, 186, 233, 246, 281, 313 |
| abstract_inverted_index.Lachnoclostridium's | 451 |
| abstract_inverted_index.Eubacterium_siraeum_group, | 318 |
| abstract_inverted_index.[Eubacterium]_siraeum_group. | 297 |
| abstract_inverted_index.Lactobacillus_salivarius_g_Lactobacillus's | 459 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| corresponding_author_ids | https://openalex.org/A5100453126, https://openalex.org/A5101706361 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 17 |
| corresponding_institution_ids | https://openalex.org/I4210160531 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.8100000023841858 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.88573245 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |