Predictive Patient Characteristics for Chemotherapy-Induced Nausea and Vomiting in Solid Organ Cancers: An Observational Study from a Tertiary Care Setting

Predictive Patient Characteristics for Chemotherapy-Induced Nausea and Vomiting in Solid Organ Cancers: An Observational Study from a Tertiary Care Setting | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Predictive Patient Characteristics for Chemotherapy-Induced Nausea and Vomiting in Solid Organ Cancers: An Observational Study from a Tertiary Care Setting Mayank Kapoor, Deepak Sundriyal, Yogesh Bahurupi, Sweety Gupta, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8607432/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Background: Chemotherapy-induced nausea and vomiting (CINV) persists in a substantial proportion of patients despite guideline-based antiemetic prophylaxis. Current preventive strategies largely emphasize chemotherapy-related risk, with limited consideration of patient-specific factors. This study aimed to identify patient-related predictors of CINV. Methods: This single-center longitudinal observational study was conducted at a tertiary care center in North India. Adult patients (≥ 18 years) with solid organ malignancies treated with carboplatin–paclitaxel and uniform antiemetic prophylaxis were enrolled. Demographic, clinical, biochemical, lifestyle, psychological, and disease-related variables were assessed. Multivariate logistic regression analysis was performed to identify independent predictors of CINV. Results: A total of 192 patients were included (mean age 53.7 ± 12.0 years), of whom 71.4% were female and 45.8% had metastatic disease. Gynecological cancers were the most common (45.8%), followed by lung (23.4%), breast (14.6%), and gastrointestinal malignancies (11.4%). The overall incidence of CINV was 46.8%. Univariate analysis demonstrated higher CINV risk in patients aged < 60 years (OR 2.03), females (OR 2.28), those with higher BMI (OR 1.05) and creatinine clearance (OR 1.01), and those with gynecological cancers (OR 2.91), while alcohol use (OR 0.59) and smoking (OR 0.66) were associated with lower risk. On multivariate analysis, female sex was the only independent predictor of CINV (OR 2.05). Conclusions: Nearly half of patients experienced CINV despite standardized prophylaxis. Female sex emerged as the strongest independent risk factor, underscoring the importance of incorporating patient-specific characteristics into individualized antiemetic decision-making to improve symptom control and treatment outcomes CINV LMIC Incidence Chemotherapy induced nausea vomiting Lower-middle-income countries Patient specific factors Figures Figure 1 Figure 2 1. Background Chemotherapy-induced nausea and vomiting (CINV) is amongst the commonest burdening side effects of chemotherapeutic drugs, significantly affecting the quality of life (QoL). These symptoms not only contribute to physical discomfort, but also lead to dehydration, malnutrition, and a reduction in the patient’s ability to continue with the prescribed cancer treatment. Estimates suggest around 40% of patients receiving chemotherapy are affected by CINV.( 1 ) The incidence and severity of CINV can vary widely among individuals, influenced by the specific chemotherapy regimen, patient's age, gender, and medical history, which play a crucial role in the onset and intensity of these symptoms. Medical professionals should preemptively be aware of CINV and plan anti-emetic regimens accordingly.( 2 ) This will help in managing the symptoms to improve patient comfort and treatment compliance, which in turn will further help in the goal towards long term disease control. Chemotherapeutic agents are usually classified as minimal, low, moderate, and highly emetogenic based on the risk of emesis ( 90% respectively). This classification helps in making the decision of chosing the antiemetic prophylaxis.( 3 , 4 ) Drugs like 5-hydroxytryptamine (serotonin) type 3 receptor antagonists (5-HT3 RAs), neurokinin-1 receptor antagonists (NK-1 RAs), and dexamethasone are amongst the medications used.( 5 ) Guidelines for the usage of anti-emetic medications have been formulated by various agencies including Multinational Association of Supportive Care in Cancer (MASCC), European Society of Medical Oncology (ESMO), the American Society of Clinical Oncology (ASCO) and the National Comprehensive Cancer Network (NCCN). This system has drawbacks. It overlooks several patient-specific variables that may also influence the incidence of CINV, thus contributing to the risk of emesis. The prediction and management of CINV in these patients remains complex due to the heterogeneity of patient-specific factors. Factors include psychological anticipation of emetic symptoms, younger age, and female gender, amongst others.( 6 , 7 ) Guidelines for other complications of chemotherapy, including utilization of white blood cell colony-stimulating factors for febrile neutropenia include individual patient factors like age and functional status.( 8 ) To incorporate patient-associated risk factors for selecting anti-emetic therapy, some studies have been done but with limitations.( 1 , 9 , 10 ) The major limitation is that these studies utilize different chemotherapy regimen combinations which in turn have different emetogenicity. Hence, the results may be deceptive, as patients may have different emetic response to different drug classes. To overcome these limitations, in our study patients were exposed to standard chemotherapeutic combination regimen of carboplatin and paclitaxel, and they were given uniform anti-emetic prophylaxis as described in the methodology. Following this, the patient-related factors which predict the development of CINV were assessed. 2. Methods This single-centre, longitudinal observational study was conducted in a tertiary care centre, involving both out-patients and in-patients. The study spanned 18 months, and patients were enrolled after obtaining informed consent and screened using predefined inclusion and exclusion criteria. In this exploratory study, fifteen independent variables were included in the logistic regression analysis. A sample size of 150 was taken as per convenience. We calculated the required sample size as ten times the number of predictor variables. To account for a dropout rate of 10%, the final sample size was taken as 165.( 11 ) All patients ≥ 18 years of age and diagnosed with a solid organ malignancy by histopathology/cytopathology and planned to receive paclitaxel (175 mg/m 2 ) and carboplatin (AUC 6 mg/ml.min) chemotherapy regimen (given every 21 days) and Eastern Cooperative Oncology Group performance status (ECOG-PS) of 0, 1, or 2 were included in the study. Evaluation for all the patients included comprehensive medical history, physical assessment and blood investigations. At the beginning of the study, the participants were given a diary and MASCC anti-emesis tool (MAT), for recording the incidence, severity, frequency, and duration of CINV, the oral intake, and/or hospitalization records.( 12 ) The questions include whether the patient developed CINV or not, the frequency of vomiting per day, and the grading of nausea. Nausea is rated on a scale from 0 to 10, where 0 indicates no nausea and 10 represents the most severe level. The anti-emetic regime consisted of a combination of an NK1-RA (fosaprepitant 150 mg on day 1), a 5-HT3 RA (palonosetron 0.25 mg on day 1), and steroid (dexamethasone 12 mg on day 1, then 8 mg on days 2 through 4).( 4 , 13 , 14 ). Following this the chemotherapy drugs were administered. Patients then documented vomiting frequency, as well as the presence and severity of nausea during both the acute (first 24 hours) and delayed phase (day 2 to 5). Additionally, they recorded oral intake and any hospital admissions following chemotherapy. To ensure accurate entries into the diary, compliance was checked telephonically and/or via text messaging. Grading of CINV was done according to Common Terminology Criteria for Adverse Events (CTCAE). The primary endpoint was CTCAE grade 3 nausea and/or grade ≥ 2 vomiting.( 15 ) Patient related factors which included gender, age, hemoglobin value, creatinine clearance (using Cockroft-Gault equation), serum albumin, serum C- Reactive Protein (CRP), alcohol consumption (≥ 5 standard drinks per week) ( 6 , 16 ), smoking history, history of motion sickness, expectation of CINV, anxiety [score ≥ 10 on the generalized anxiety disorder-7 (GAD-7) anxiety scale] ( 17 ), having meals before chemotherapy (within 6 hours), body mass index (BMI), metastatic versus non-metastatic disease, and location of the primary (gastrointestinal, gynaecological, lung, breast, and others) were assessed. (Fig. 1 ) 2.1 Statistical Analysis Data analysis involved descriptive statistics, with means and standard deviations (SDs) calculated for continuous variables, and frequencies and percentages for categorical variables. Additionally, odds ratios (OR) and 95% confidence intervals (CI) were employed to evaluate the factors predicting emesis and nausea. The dependent variable was development of CINV. After univariate analysis, to identify the factors with the greatest potential contribution for the development of CINV, a removal criterion of p > 0.20 was applied, and factors having p < 0.20 were retained for further analysis.( 18 ) Utilizing these variables, multivariate logistic regression analysis using stepwise forward selection method was done. A p-value of less than 0.05 was regarded as statistically significant. 2.2 Patient and Public Involvement Patients and members of the public were not involved in the design, conduct, reporting, or dissemination plans of this research 3. Results Table 1 Participant baseline demographics and clinical profile Characteristics Number (%) n = 192 Age (years) (mean ± SD) 53.7 ± 12.0 Gender Male 55 (28.6) Female 137 (71.4) ECOG PS 0 33 ( 17 ) 1 113 ( 59 ) 2 46 ( 24 ) Metastatic disease Yes 88 (45.8) No 104 (54.2) Site of the cancer Gynecological 88 (45.8) Lung 45 (23.4) Breast 28 (14.6) GI 22 (11.4) Others 9 (4.8) Clinical Factors (mean ± SD) Hemoglobin (gm/dL) 11.4 ± 1.6 Creatinine clearance (mL/min) 78.1 ± 26.4 Serum albumin (mg/dL) 3.7 ± 0.6 CRP (mg/dL) 33.2 ± 49.2 Nutritional BMI (kg/m 2 ) (mean ± SD) 23.3 ± 5.4 Pre-treatment meal intake 96 ( 50 ) Behavioral and psychological Alcohol use 42 (21.8) Smoking history 55 (28.6) History of motion sickness 67 (34.8) Expectation of CINV 106 (55.2) Anxiety 110 (57.7) SD- Standard Deviation; ECOG PS- Eastern Cooperative Oncology Group Performance Status; CINV- Chemotherapy induced nausea vomiting; GI- Gastrointestinal; CRP- C-Reactive protein; BMI- Body Mass Index The study comprised 192 patients in total, with 137 (71.4%) females. Mean age (± SD) of the participants was 53.7 (± 12.0) years. 88 patients (45.8%) presented with metastatic disease at diagnosis. The primary cancer types were distributed as follows: gynecological (45.8%), lung (23.4%), breast (14.6%), gastrointestinal (11.4%), and other sites (4.8%). Other characteristics are as shown in Table 1 . Table 2 CINV result Characteristics Number (%) CTCAE Grade (Median) Nausea score/ Vomiting frequency/day (Mean ± SD) Acute (Day 1) Nausea 58 ( 30 ) 3 4.3 ± 1.4 Vomiting 29 ( 15 ) 3 4.5 ± 1.6 Delayed (Day 2 to Day 5) Nausea 67 ( 35 ) 3 4.4 ± 1.8 Vomiting 40 ( 21 ) 3 5.1 ± 2.8 Overall Nausea 89 ( 46 ) 3 4.4 ± 1.8 Vomiting 50 ( 26 ) 3 5.0 ± 2.6 Nausea and/or Vomiting 90 ( 47 ) 3 CTCAE- Common Terminology Criteria for Adverse Events; SD- Standard Deviation As shown in Table 2 , 90 patients (46.8%) developed CINV. As per the MAT response recorded, the mean (± SD) score given for nausea severity was 4.4 (± 1.8), whereas mean (± SD) frequency of vomiting per day was 5.0 (± 2.6). Table 3 Identification of CINV predictors through univariate and multivariate analyses Univariate analysis OR 95% CI P-value Age < 60 years 2.03 1.08–3.82 0.02 Female sex 2.28 1.18–4.38 0.01 BMI (kg/m 2 ) 1.05 0.99–1.11 0.08 Motion sickness 1.38 0.76–2.52 0.29 Meals prior to Chemotherapy 0.98 0.55–1.74 0.94 Expectation of CINV 1.27 0.72–2.26 0.41 Anxiety 0.93 0.52–1.66 0.81 Alcohol use 0.59 0.29–1.21 0.15 Smoking history 0.66 0.35–1.24 0.19 Hemoglobin (gm/dL) 0.89 0.75–1.07 0.21 CrCl (mL/min) 1.01 0.99–1.02 0.12 Albumin (mg/dL) 0.92 0.55–1.53 0.74 CRP (mg/dL) 0.99 0.98-1.00 0.33 Metastatic disease 0.76 0.43–1.34 0.35 Site of the cancer Gynecological 2.91 1.36–6.22 0.006 Breast 1.66 0.62–4.42 0.31 GI 1.84 0.65–5.27 0.25 Others 1.77 0.41–7.62 0.44 Multivariate analysis AOR 95% CI P-value Female sex 2.05 1.03–4.07 0.04 Age < 60 years 1.77 0.91–3.43 0.09 CINV- Chemotherapy induced nausea vomiting; OR- Odds Ratio; CI- Confidence Interval; BMI- Body Mass Index; CrCl- Creatinine clearance; CRP- C-Reactive protein; GI- Gastrointestinal; AOR- Adjusted Odds Ratio Results of univariate and multivariate logistic regression analysis are as shown in Table 3 and Fig. 2 . The final model retained the variables female sex and age (< 60 years). Variables not retained in the model but considered included BMI, alcohol use, smoking history, creatinine clearance, and the site of cancer. It reveals that females have 2.28 times higher odds of developing CINV as compared to males. Age < 60 years (OR = 2.03) and BMI (OR = 1.05) also revealed correlation with CINV. There was an inverse relationship between alcohol consumption (OR = 0.59) and smoking (OR = 0.66). In relation to the site of the cancer, gynecological site had an OR of 2.91 for CINV development, which was statistically significant. Biochemical parameter analysis revealed creatinine clearance having an OR of 1.01. Multivariate logistic regression analysis showed female patients have 2.05 times odds of developing CINV as compared to male patients, which was statistically significant. 4. Discussion Chemotherapy constitutes a fundamental component in the management of cancer and is commonly associated with a range of adverse effects including CINV, bone marrow suppression, diarrhoea, and hypersensitivity, amongst others. CINV is among the commonest adverse effects of chemotherapy, with an incidence of approximately 40% in various studies.( 1 , 19 , 20 ) CINV is generally categorized into two types: acute, which arises within the first 24 hours following treatment, and delayed, which occurs between 24 and 120 hours after chemotherapy administration.( 21 , 22 ) In our study, the incidence of CINV was found to be 46.8%. Several factors may contribute to this increased incidence. Variations in patient specific factors influence susceptibility to CINV in different populations. This maybe a result of genetic variations in different populations affecting drug metabolism and receptor sensitivity. More patients developed delayed as compared to acute CINV. In the acute phase, 30% of the patients developed nausea and 15% had vomiting, whereas in the delayed phase, 35% of the patients had nausea and 21% had vomiting. Comparable findings have been reported in other studies, with acute nausea and vomiting occurring in 13% and 37% of patients, respectively, and delayed in 52% and 28%, respectively.( 23 ) In order to minimize the occurrence of delayed CINV, it is essential to improve patient education by emphasizing the importance of continuing prescribed antiemetics at home, even in the absence of symptoms. Additionally, follow-up calls or tele-health check-ins within a few days of chemotherapy can reinforce adherence and allow timely management of emerging symptoms. For analyzing factors which predict CINV, initial univariate logistic regression analysis was done. A statistically significant association was observed between female sex and the risk of CINV (OR = 2.28, 95% CI: 1.18–4.38, p = 0.01), indicating that females have 2.28 times higher odds of developing CINV as compared to males. This maybe due to a combination of hormonal, physiological, and pharmacological factors. Hormonal influences, particularly the presence of estrogen and progesterone, are believed to increase the sensitivity of the vomiting center, making women more susceptible to nausea. Difference in the body composition may also play a role, as females usually have a lower body surface area and body weight compared to males, which can affect the pharmacokinetics of chemotherapeutic drugs and increase their toxicity. Studies have shown an important correlation between single-nucleotide polymorphisms (SNPs) within estrogen-responsive elements of the TACR1 gene, which encodes the neurokinin-1 (NK1) receptor, and an increased occurrence of postoperative nausea and vomiting ( 24 – 28 ) Younger age (< 60 years) (OR = 2.03, 95% CI: 1.08–3.82, p = 0.02) also revealed positive correlation with CINV. Studies have shown younger patients have higher incidence of CINV.( 29 ) This maybe due to more active central nervous system (CNS) and emetic reflex, making them more sensitive to chemotherapy. Older patients often have a diminished nausea and vomiting response, possibly due to age-related changes in the CNS or altered drug metabolism and clearance. Additionally, younger patients are usually given more aggressive chemotherapy regimens and tend to have fewer comorbidities, allowing for the administration of higher doses, which may increase the risk of CINV. Eighty-eight (45.8%) patients had metastatic disease. Presence of metastatic disease showed inverse correlation (OR = 0.76, p = 0.35) with the risk of CINV, although it was not statistically significant. Possible explanation for this may be psychological—patients with non-metastatic disease often have higher expectations for cure and may be more anxious or emotionally reactive to treatment, which can heighten nausea perception. Additionally, they may receive more aggressive or high-dose chemotherapy regimens, especially in curative settings, which increases the emetogenic potential. Patients with advanced disease may have a blunted emetic response, possibly due to general debility, altered physiology, or adaptation over time to ongoing treatment.( 30 , 31 ) Gynecological malignancies had an OR of 2.91 (95% CI: 1.36–6.22, p = 0.006) for predicting CINV. Various studies have shown inconsistent results in regards to CINV risk correlation with the site of malignancy. While some reveal higher risk for breast cancer patients, others show lower risk for gynecological or genitourinary malignancies.( 30 , 32 ) Biological differences between tumor types may influence how patients metabolize chemotherapeutic agents, potentially affecting emetogenic responses. Moreover, the site of cancer itself may be a risk factor for heightened gastrointestinal symptoms.( 33 ) The study revealed no statistically meaningful relationship between hemoglobin levels (OR = 0.89, p = 0.21) and the occurrence of CINV. CrCl revealed an OR of 1.01 for CINV, which was not statistically significant (p = 0.12). Age-related physiological changes may increase the risk of chemotherapy-related toxicity. Reduced CrCl has been linked to a higher incidence of fever, neutropenia, and hematologic toxicity. Therefore, assessing CrCl is essential when determining appropriate chemotherapy dosing so as to avoid toxicities.( 34 ) CRP levels did not show a significant correlation with CINV. CRP elevation has shown correlation with mortality.( 35 ) As far as nutritional factors are concerned, serum albumin is a proven marker of the nutritional well-being of patients. In our study higher serum albumin levels (OR = 0.92, 95% CI: 0.55–1.53, p = 0.74) correlated with lower CINV risk, although the results were not statistically significant. Higher serum albumin level correlates with better survival also, whereas lower albumin level has shown correlation with higher incidence of chemotherapy induced toxicity.( 36 , 37 ) This shows the importance of good nutrition and the value of a proper diet in the cancer patient undergoing chemotherapy. BMI (OR = 1.05, 95% CI: 0.99–1.1, p = 0.08) demonstrated a correlation with CINV, although this association did not reach statistical significance. In other studies, lower BMI has shown correlation with higher risk of CINV.( 38 ) To address the risks associated with poor nutrition, it is essential to prioritize nutritional assessment and intervention in cancer patients receiving chemotherapy. Early involvement of a clinical dietitian can help tailor individualized nutrition plans aimed at improving protein intake and overall caloric balance. Having meals prior to chemotherapy was protective of CINV, although it was not statistically significant.(OR = 0.98, 95% CI 0.55–1.74, p = 0.94) Patients who do not eat prior to receiving chemotherapy were shown to be around seven times more prone to develop CINV compared to those who had a meal beforehand.( 39 , 40 ) Patients must be encouraged to consume a light, well-balanced meal prior to chemotherapy, which can help reduce the CINV risk. An empty stomach may become more sensitive to the effects of chemotherapy, leading to greater irritation and discomfort. Without food to buffer the stomach lining, the risk of nausea increases. Additionally, low blood sugar levels caused by not having meals can contribute to feelings of weakness, dizziness, and nausea, compounding the effects of chemotherapy. Skipping meals can also lead to a heightened stress response, which may exacerbate gastrointestinal symptoms. Meal consumption can maintain the normal physiologic rhythm of the stomach, leading to reduced symptoms of nausea and vomiting. This demonstrates the importance of having small meals before starting treatment.( 39 , 41 ) History of motion sickness showed no statistically significant correlation with CINV (OR = 1.38, 95% CI: 0.76–2.52, p = 0.29), although it revealed a positive association. Prior motion sickness is a risk factor for CINV.( 42 ) Both CINV and motion sickness are mediated through the activation of the vomiting center located in brain which processes signals from the gastrointestinal tract, vestibular system, and bloodstream. Individuals prone to motion sickness often have a heightened sensitivity to nausea-inducing stimuli, such as movement or sensory mismatch, which may reflect a generally lower threshold for nausea that also increases susceptibility to CINV. Additionally, common neuro-chemical pathways, particularly involving serotonin (5-HT3) and dopamine, may play a role in both conditions, and certain genetic or receptor-based differences may predispose some individuals to experience both. The expectation of CINV was linked to an increased risk of experiencing CINV, with an OR of 1.27, 95% CI: 0.72–2.26; however, this association was not statistically significant (p = 0.49). Similar results have been reported in other studies.( 43 , 44 ) The expectation of nausea is believed to be driven largely by psychological mechanisms. The CNS, particularly regions involved in memory, emotion, and stress including the amygdala and hypothalamus, plays a pivotal role in modulating this response. To mitigate this, behavioral interventions such as relaxation techniques, guided imagery, and meditation may be helpful. Factors like anxiety can further exacerbate this effect by causing alterations in gastric motility and secretions. It may lead to enhanced perception of nausea and vomiting.( 43 , 45 ) However, anxiety (OR = 0.93, p = 0.81) did not demonstrate a statistically significant correlation with CINV in our study. Alcohol consumption (OR = 0.59, 95% CI: 0.29–1.21, p = 0.15) and smoking history (OR = 0.66, 95% CI: 0.35–1.24, p = 0.19) were found to inversely associate with CINV. Many studies have demonstrated this inverse correlation.( 44 , 46 ) Chronic alcohol exposure results in desensitization of the central vomiting center, particularly the chemoreceptor trigger zone (CTZ), thereby decreasing sensitivity to emetogenic stimuli. Additionally, alcohol affects key neurotransmitter systems involved in nausea and vomiting, such as serotonin, dopamine, and gamma-aminobutyric acid (GABA). Regular alcohol use may modulate these pathways in a way that diminishes the emetic response. While not a recommendation for alcohol consumption, this observed inverse relationship provides insight into the complex neurobiological factors influencing individual susceptibility to CINV.( 47 ) Similarly smokers have shown a lower incidence of CINV, although the results are contrasting for some studies.( 48 , 49 ) Natural killer (NK) cells, a type of large granular lymphocyte, play a key role in limiting the proliferation of damages cells. Studies have indicated that individuals who smoke tend to have fewer NK cells in circulation compared to non-smokers. This reduction in NK cell count has been linked to faster tumor growth and may intensify the adverse effects associated with cancer therapies.( 50 – 52 ) The final model for CINV prediction retained the variable female sex (AOR = 2.05, 95% CI: 1.03–4.07, p = 0.04), which was statistically significant. This implies that female patients have 2.05 times odds of developing CINV as compared to male patients. The higher CINV risk in females has been replicated in multiple studies.( 27 , 53 – 57 ) To address this increased risk, clinicians can employ more aggressive antiemetic strategies in female patients. This highlights the importance of personalized antiemetic strategies, particularly for high-risk groups like females. Uncontrolled CINV can lead to multiple clinical and treatment-related complications, including inadequate nutritional intake, weight loss, dehydration, and electrolyte imbalance, which can further compromise a patient's ability to tolerate ongoing treatment. It can also impair the quality of life, including physical, emotional, and social well-being, causing anxiety, sleep disturbances, and fatigue, which may persist even beyond the acute phase. The fear or experience of CINV may lead patients to delay or even refuse further chemotherapy cycles, potentially reducing the efficacy of cancer treatment. Recurrent or severe CINV episodes may necessitate additional medications, emergency visits, or hospital admissions, placing extra burden on healthcare systems already operating under resource constraints.( 58 – 61 ) These issues along with the high CINV rates observed in our study underline the need for improved implementation of antiemetic prophylaxis, better patient education on early reporting of symptoms, and perhaps tailored antiemetic regimens based on patient-specific factors. Our study is the only study from an LMIC like India which has determined the incidence of CINV under routine clinic practice. This adds valuable real-world data to the existing literature, which is largely dominated by studies from high-income countries. In LMICs, where resource constraints and variability in treatment delivery are common, understanding the actual incidence and burden of chemotherapy-related side effects becomes even more critical for optimizing patient care. Our study has certain limitations. All CINV results could not be monitored in-hospital and patient recorded data was collected, although diligent care was taken to record the data correctly and compliance was also ensured telephonically. 5.Conclusions This study highlights the crucial need to account for individual patient characteristics when developing and implementing antiemetic strategies for the control of CINV. While current clinical practice often follows standardized, guideline-recommended antiemetic protocols, these universal approaches may not adequately look into the diversity of the patients, particularly in lower-middle-income countries (LMICs). Despite appropriate adherence to these guidelines, a considerable number of patients in LMICs continue to suffer from significant CINV, suggesting that a one-size-fits-all model may fall short in practice. This disparity emphasizes the urgent necessity for more personalized and nuanced prophylactic strategies. Notably, female patients appear to be disproportionately affected and may benefit from more aggressive or tailored antiemetic interventions. Enhancing individualized care by integrating demographic and physiological variables such as gender could improve symptom control, patient comfort, and overall treatment adherence during chemotherapy. This can help reduce the psychological, physiological, and financial burden, especially in LMICs. Abbreviations • AOR Adjusted Odds Ratio • BMI Body mass index • CI Confidence interval • CINV Chemotherapy-induced nausea and vomiting • CRP C-Reactive Protein • CTCAE Common Terminology Criteria for Adverse Events • ECOG PS Eastern Cooperative Oncology Group Performance Status • GI Gastrointestinal • LMIC Low- and middle-income countries • MASCC Multinational Association of Supportive Care in Cancer • MAT MASCC anti-emesis tool • OR Odds ratio • QoL Quality of Life Declarations Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee, AIIMS Rishikesh, AIIMS/IEC/23/359 Consent for publication: Not applicable Availability of data and materials: Available on request to the corresponding author Competing interests: The authors declare that they have no competing interests Funding: None Authors' contributions: Conceptualization, MK and DS ; methodology MK,DS,AS,SG ; formal analysis, MK,DS,YB ; writing—original draft preparation, MK ; writing—review and editing, MK,DS ; supervision, DS,AS All authors have read and agreed to the published version of the manuscript. Acknowledgements: This article is a revised and expanded version of a paper entitled Patient-specific factors as predictors of chemotherapy-induced nausea and vomiting: Insights from a lower-middle-income setting, which was presented at the ASCO 2025 annual meeting held at Chicago, Illinois, the USA on May 28, 2025 as E-poster.(62) References Dranitsaris G, Molassiotis A, Clemons M, Roeland E, Schwartzberg L, Dielenseger P et al. The development of a prediction tool to identify cancer patients at high risk for chemotherapy-induced nausea and vomiting. Ann Oncol. 2017 June 1;28(6):1260–7. Gupta K, Walton R, Kataria SP. Chemotherapy-Induced Nausea and Vomiting: Pathogenesis, Recommendations, and New Trends. Cancer Treat Res Commun. 2021;26:100278. Aapro M, Gralla RJ, Herrstedt J, Molassiotis A, Roila F. MASCC/ESMO ANTIEMETIC GUIDELINE 2016. Hesketh PJ, Kris MG, Basch E, Bohlke K, Barbour SY, Clark-Snow RA, et al. Antiemetics: ASCO Guideline Update. J Clin Oncol. 2020;38(24):2782–97. 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Incidence of chemotherapy-induced nausea and vomiting with moderately emetogenic chemotherapy: ADVICE (Actual Data of Vomiting Incidence by Chemotherapy Evaluation) study. Support Care Cancer. 2015;23(9):2833–40. Dranitsaris G, Molassiotis A, Clemons M, Roeland E, Schwartzberg L, Dielenseger P, et al. The development of a prediction tool to identify cancer patients at high risk for chemotherapy-induced nausea and vomiting. Ann Oncol. 2017 June;28(6):1260–7. Hesketh PJ. Chemotherapy-Induced Nausea and Vomiting. N Engl J Med. 2008 June;5(23):2482–94. Rapoport BL. Delayed Chemotherapy-Induced Nausea and Vomiting: Pathogenesis, Incidence, and Current Management. Front Pharmacol. 2017;8:19. Grunberg SM, Deuson RR, Mavros P, Geling O, Hansen M, Cruciani G, et al. Incidence of chemotherapy-induced nausea and emesis after modern antiemetics. Cancer. 2004;100(10):2261–8. Rapoport BL. Efficacy of a triple antiemetic regimen with aprepitant for the prevention of chemotherapy-induced nausea and vomiting: effects of gender, age, and region. Curr Med Res Opin. 2014 Sept;30(1):1875–81. Kirkova J, Rybicki L, Walsh D, Aktas A. Symptom Prevalence in Advanced Cancer: Age, Gender, and Performance Status Interactions. Am J Hosp Palliat Med. 2012;29(2):139–45. Hayase T, Sugino S, Moriya H, Yamakage M. TACR1 gene polymorphism and sex differences in postoperative nausea and vomiting. Anaesthesia. 2015;70(10):1148–59. Sekine I, Segawa Y, Kubota K, Saeki T. Risk factors of chemotherapy-induced nausea and vomiting: Index for personalized antiemetic prophylaxis. Cancer Sci. 2013;104(6):711–7. Hesketh PJ, Bohlke K, Lyman GH, Basch E, Chesney M, Clark-Snow RA, et al. Antiemetics: American Society of Clinical Oncology Focused Guideline Update. J Clin Oncol. 2016;34(4):381–6. Hashimoto K, Yokokawa T, Nonomiya Y, Shibata N, Soejima A, Kobayashi K et al. Age-Stratified Risk of Carboplatin-Induced Nausea and Vomiting in Lung Cancer Patients. Oncology [Internet]. 2025 Mar 10 [cited 2025 May 29]; Available from: https://doi.org/10.1159/000544875 Dranitsaris G, Bouganim N, Milano C, Vandermeer L, Dent S, Wheatley-Price P, et al. Prospective validation of a prediction tool for identifying patients at high risk for chemotherapy-induced nausea and vomiting. J Support Oncol. 2013;11(1):14–21. Dranitsaris G, Joy A, Young S, Clemons M, Callaghan W, Petrella T. Identifying patients at high risk for nausea and vomiting after chemotherapy: the development of a practical prediction tool. I. Acute nausea and vomiting. J Support Oncol. 2009;7(4):W1–8. Roscoe JA, Morrow GR, Colagiuri B, Heckler CE, Pudlo BD, Colman L et al. Insight in the prediction of chemotherapy-induced nausea. Support Care Cancer. 2010 July 1;18(7):869–76. Grunberg SM, Deuson RR, Mavros P, Geling O, Hansen M, Cruciani G, et al. Incidence of chemotherapy-induced nausea and emesis after modern antiemetics. Cancer. 2004;100(10):2261–8. Hurria A, Hurria A, Brogan K, Panageas KS, Pearce C, Norton L et al. Effect of Creatinine Clearance on Patterns of Toxicity in Older Patients Receiving Adjuvant Chemotherapy for Breast Cancer. Drugs Aging. 2005 Sept 1;22(9):785–91. Allin KH, Bojesen SE, Nordestgaard BG. Baseline C-Reactive Protein Is Associated With Incident Cancer and Survival in Patients With Cancer. J Clin Oncol. 2009;27(13):2217–24. Gupta D, Lis CG. Pretreatment serum albumin as a predictor of cancer survival: A systematic review of the epidemiological literature. Nutr J. 2010;9(1):69. Arrieta O, Michel Ortega RM, Villanueva-Rodríguez G, Serna-Thomé MG, Flores-Estrada D, Diaz-Romero C, et al. Association of nutritional status and serum albumin levels with development of toxicity in patients with advanced non-small cell lung cancer treated with paclitaxel-cisplatin chemotherapy: a prospective study. BMC Cancer. 2010;10(1):50. Kawazoe H, Murakami A, Yamashita M, Nishiyama K, Kobayashi-Taguchi K, Komatsu S, et al. Patient-related Risk Factors for Nausea and Vomiting with Standard Antiemetics in Patients with Breast Cancer Receiving Anthracycline-based Chemotherapy: A Retrospective Observational Study. Clin Ther. 2018;40(12):2170–9. Booth CM, Clemons M, Dranitsaris G, Joy A, Young S, Callaghan W, et al. Chemotherapy-induced nausea and vomiting in breast cancer patients: a prospective observational study. J Support Oncol. 2007 Sept;5(8):374–80. Bloechl-Daum B, Deuson RR, Mavros P, Hansen M, Herrstedt J. Delayed Nausea and Vomiting Continue to Reduce Patients’ Quality of Life After Highly and Moderately Emetogenic Chemotherapy Despite Antiemetic Treatment. J Clin Oncol 2006 Sept 20;24(27):4472–8. Marx W, Kiss N, McCarthy AL, McKavanagh D, Isenring L. Chemotherapy-Induced Nausea and Vomiting: A Narrative Review to Inform Dietetics Practice. J Acad Nutr Diet. 2016;116(5):819–27. Tsuji Y, Baba,Hideo T et al. Koji, Kobayashi, Michiya, Oki, Eiji, Gotoh, Masahiro,. Chemotherapy-induced nausea and vomiting (CINV) in 190 colorectal cancer patients: a prospective registration study by the CINV study group of Japan. Expert Opin Pharmacother. 2017;18(8):753–8. Molassiotis A, Lee PH, Burke TA, Dicato M, Gascon P, Roila F et al. Anticipatory Nausea, Risk Factors, and Its Impact on Chemotherapy-Induced Nausea and Vomiting: Results From the Pan European Emesis Registry Study. J Pain Symptom Manage. 2016 June 1;51(6):987–93. Mosa ASM, Hossain AM, Lavoie BJ, Yoo I. Patient-Related Risk Factors for Chemotherapy-Induced Nausea and Vomiting: A Systematic Review. Front Pharmacol [Internet]. 2020 [cited 2023 Apr 19];11. Available from: https://www.frontiersin.org/articles/ 10.3389/fphar.2020.00329 Andrykowski MA. The role of anxiety in the development of anticipatory nausea in cancer chemotherapy: a review and synthesis. Psychosom Med. 1990;52(4):458–75. Risk factors of chemotherapy-induced nausea. and vomiting: Index for personalized antiemetic prophylaxis. [cited 2025 June 1]; Available from: https://onlinelibrary.wiley.com/doi/ 10.1111/cas.12146 Sekine I, Segawa Y, Kubota K, Saeki T. Risk factors of chemotherapy-induced nausea and vomiting: index for personalized antiemetic prophylaxis. Cancer Sci. 2013 June;104(6):711–7. Ye E, U YA, Z GG. B M, E Y, Is chemotherapy-induced nausea and vomiting lower in smokers? Int J Clin Pharmacol Ther [Internet]. 2011 Dec [cited 2025 July 26];49(12). Available from: https://pubmed.ncbi.nlm.nih.gov/22122812/ Peppone LJ, Mustian KM, Morrow GR, Dozier AM, Ossip DJ, Janelsins MC, et al. The Effect of Cigarette Smoking on Cancer Treatment–Related Side Effects. Oncologist. 2011;16(12):1784–92. Peppone LJ, Mahoney MC, Cummings KM, Michalek AM, Reid ME, Moysich KB et al. Colorectal cancer occurs earlier in those exposed to tobacco smoke: implications for screening. J Cancer Res Clin Oncol. 2008 July 1;134(7):743–51. Tartter PI, Steinberg B, Barron DM, Martinelli G. The Prognostic Significance of Natural Killer Cytotoxicity in Patients With Colorectal Cancer. Arch Surg. 1987;122(11):1264–8. Ferson M, Edwards A, Lind A, Milton GW, Hersey P. Low natural killer-cell activity and immunoglobulin levels associated with smoking in human subjects. Int J Cancer. 1979;23(5):603–9. Schmetzer O, Flörcken A. Sex Differences in the Drug Therapy for Oncologic Diseases. In: Regitz-Zagrosek V, editor. Sex and Gender Differences in Pharmacology [Internet]. Berlin, Heidelberg: Springer; 2012 [cited 2025 June 1]. pp. 411–42. Available from: https://doi.org/10.1007/978-3-642-30726-3_19 Tsuji D, Suzuki K, Kawasaki Y, Goto K, Matsui R, Seki N, et al. Risk factors associated with chemotherapy-induced nausea and vomiting in the triplet antiemetic regimen including palonosetron or granisetron for cisplatin-based chemotherapy: analysis of a randomized, double-blind controlled trial. Support Care Cancer. 2019;27(3):1139–47. Hilarius DL, Kloeg PH, van der Wall E, van den Heuvel JJG, Gundy CM, Aaronson NK. Chemotherapy-induced nausea and vomiting in daily clinical practice: a community hospital-based study. Support Care Cancer. 2012;20(1):107–17. Liaw CC, Chang HK, Liau CT, Huang JS, Lin YC, Chen JS. Reduced Maintenance of Complete Protection From Emesis for Women During Chemotherapy Cycles. Am J Clin Oncol. 2003;26(1):12. Iihara H, Fujii H, Yoshimi C, Yamada M, Suzuki A, Matsuhashi N, et al. Control of chemotherapy-induced nausea in patients receiving outpatient cancer chemotherapy. Int J Clin Oncol. 2016;21(2):409–18. Aapro M. CINV: still troubling patients after all these years. Support Care Cancer. 2018;26(1):5–9. Lyman GH, Dale DC, Crawford J. Incidence and Predictors of Low Dose-Intensity in Adjuvant Breast Cancer Chemotherapy: A Nationwide Study of Community Practices. J Clin Oncol. 2003;21(24):4524–31. Vandyk AD, Harrison MB, Macartney G, Ross-White A, Stacey D. Emergency department visits for symptoms experienced by oncology patients: a systematic review. Support Care Cancer. 2012;20(8):1589–99. Klepin HD, Pitcher BN, Ballman KV, Kornblith AB, Hurria A, Winer EP, et al. Comorbidity, Chemotherapy Toxicity, and Outcomes Among Older Women Receiving Adjuvant Chemotherapy for Breast Cancer on a Clinical Trial: CALGB 49907 and CALGB 361004 (Alliance). J Oncol Pract. 2014 Sept;10(5):e285–92. Kapoor M, Sundriyal D, Sehrawat A, Bahurupi YA. Patient-specific factors as predictors of chemotherapy-induced nausea and vomiting: Insights from a lower-middle-income setting. J Clin Oncol. 2025 June;43(16suppl):e24075–24075. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8607432","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":591753110,"identity":"e397f962-ef67-414d-b4f2-32936a7aebaf","order_by":0,"name":"Mayank Kapoor","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYDACHgST8QEDwwEo24A4LcwGJGthk0BowQN0ew4/e/Ch4p49v3SPWTVPzR05fgbmhw8YCu7g1GJ2ts3ccMaZ4sSZc86Y3eY59sxYsoHN2IDB4BluLecZzKR52xISDG7kALWwHU7ccIAH6EKDw3i0sH8DabEHaSnm+UeMlrM9YFsYNwC1MPO2EaPlzJlyoF8SEmfOSCuWnNt32FiyGeiXBLxa0rcBQyzBnl8ieeOHN98Oy/GzNz988OEPbi1AwAZnMYEjiRmIE/BpQNbC+AO/ylEwCkbBKBihAAArNlMLCYDNbgAAAABJRU5ErkJggg==","orcid":"","institution":"All India Institute of Medical Sciences Rishikesh","correspondingAuthor":true,"prefix":"","firstName":"Mayank","middleName":"","lastName":"Kapoor","suffix":""},{"id":591753114,"identity":"3c59a823-acc2-4c56-9473-4ebc25233486","order_by":1,"name":"Deepak Sundriyal","email":"","orcid":"","institution":"All India Institute of Medical Sciences Rishikesh","correspondingAuthor":false,"prefix":"","firstName":"Deepak","middleName":"","lastName":"Sundriyal","suffix":""},{"id":591753117,"identity":"a3d67d3b-79bb-4956-aeea-a8e38e299e51","order_by":2,"name":"Yogesh Bahurupi","email":"","orcid":"","institution":"All India Institute of Medical Sciences Nagpur","correspondingAuthor":false,"prefix":"","firstName":"Yogesh","middleName":"","lastName":"Bahurupi","suffix":""},{"id":591753119,"identity":"0ddf1c6c-74a6-4c5e-bd4a-1f2e7a0f85b8","order_by":3,"name":"Sweety Gupta","email":"","orcid":"","institution":"All India Institute of Medical Sciences Rishikesh","correspondingAuthor":false,"prefix":"","firstName":"Sweety","middleName":"","lastName":"Gupta","suffix":""},{"id":591753120,"identity":"a3c71680-5593-402b-8716-f12c7ca7e4a2","order_by":4,"name":"Amit Sehrawat","email":"","orcid":"","institution":"All India Institute of Medical Sciences Rishikesh","correspondingAuthor":false,"prefix":"","firstName":"Amit","middleName":"","lastName":"Sehrawat","suffix":""}],"badges":[],"createdAt":"2026-01-15 06:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8607432/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8607432/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102837756,"identity":"25ff311b-5d6f-4492-bdee-cb12004c23a0","added_by":"auto","created_at":"2026-02-17 11:25:49","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":373786,"visible":true,"origin":"","legend":"\u003cp\u003eStudy Flow\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8607432/v1/d71854c37db9e301cf70a982.jpeg"},{"id":102837752,"identity":"c6dcb989-1cad-4e28-a3b6-745585456b9b","added_by":"auto","created_at":"2026-02-17 11:25:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":179113,"visible":true,"origin":"","legend":"\u003cp\u003eDepicting the Odds Ratio (OR) for univariate analysis (blue lines) and Adjusted Odds Ratio (AOR) for multivariate analysis (red lines). The values above the circles represent OR and squares, the AOR\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8607432/v1/3e707f56049fca387cdb9606.png"},{"id":102837821,"identity":"3ce65660-48e8-4fd3-b4ff-9e14bc3f8a24","added_by":"auto","created_at":"2026-02-17 11:26:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1381888,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8607432/v1/03926ce9-1b93-4b9c-936c-3000af83a6a9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictive Patient Characteristics for Chemotherapy-Induced Nausea and Vomiting in Solid Organ Cancers: An Observational Study from a Tertiary Care Setting","fulltext":[{"header":"1. Background","content":"\u003cp\u003eChemotherapy-induced nausea and vomiting (CINV) is amongst the commonest burdening side effects of chemotherapeutic drugs, significantly affecting the quality of life (QoL). These symptoms not only contribute to physical discomfort, but also lead to dehydration, malnutrition, and a reduction in the patient\u0026rsquo;s ability to continue with the prescribed cancer treatment. Estimates suggest around 40% of patients receiving chemotherapy are affected by CINV.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The incidence and severity of CINV can vary widely among individuals, influenced by the specific chemotherapy regimen, patient's age, gender, and medical history, which play a crucial role in the onset and intensity of these symptoms. Medical professionals should preemptively be aware of CINV and plan anti-emetic regimens accordingly.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) This will help in managing the symptoms to improve patient comfort and treatment compliance, which in turn will further help in the goal towards long term disease control.\u003c/p\u003e \u003cp\u003eChemotherapeutic agents are usually classified as minimal, low, moderate, and highly emetogenic based on the risk of emesis (\u0026lt;\u0026thinsp;10%, 10\u0026ndash;30%, 30\u0026ndash;90%, and \u0026gt;\u0026thinsp;90% respectively). This classification helps in making the decision of chosing the antiemetic prophylaxis.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Drugs like 5-hydroxytryptamine (serotonin) type 3 receptor antagonists (5-HT3 RAs), neurokinin-1 receptor antagonists (NK-1 RAs), and dexamethasone are amongst the medications used.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Guidelines for the usage of anti-emetic medications have been formulated by various agencies including Multinational Association of Supportive Care in Cancer (MASCC), European Society of Medical Oncology (ESMO), the American Society of Clinical Oncology (ASCO) and the National Comprehensive Cancer Network (NCCN).\u003c/p\u003e \u003cp\u003eThis system has drawbacks. It overlooks several patient-specific variables that may also influence the incidence of CINV, thus contributing to the risk of emesis. The prediction and management of CINV in these patients remains complex due to the heterogeneity of patient-specific factors. Factors include psychological anticipation of emetic symptoms, younger age, and female gender, amongst others.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e Guidelines for other complications of chemotherapy, including utilization of white blood cell colony-stimulating factors for febrile neutropenia include individual patient factors like age and functional status.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) To incorporate patient-associated risk factors for selecting anti-emetic therapy, some studies have been done but with limitations.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) The major limitation is that these studies utilize different chemotherapy regimen combinations which in turn have different emetogenicity. Hence, the results may be deceptive, as patients may have different emetic response to different drug classes.\u003c/p\u003e \u003cp\u003eTo overcome these limitations, in our study patients were exposed to standard chemotherapeutic combination regimen of carboplatin and paclitaxel, and they were given uniform anti-emetic prophylaxis as described in the methodology. Following this, the patient-related factors which predict the development of CINV were assessed.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis single-centre, longitudinal observational study was conducted in a tertiary care centre, involving both out-patients and in-patients. The study spanned 18 months, and patients were enrolled after obtaining informed consent and screened using predefined inclusion and exclusion criteria.\u003c/p\u003e \u003cp\u003eIn this exploratory study, fifteen independent variables were included in the logistic regression analysis. A sample size of 150 was taken as per convenience. We calculated the required sample size as ten times the number of predictor variables. To account for a dropout rate of 10%, the final sample size was taken as 165.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) All patients\u0026thinsp;\u0026ge;\u0026thinsp;18 years of age and diagnosed with a solid organ malignancy by histopathology/cytopathology and planned to receive paclitaxel (175 mg/m\u003csup\u003e2\u003c/sup\u003e) and carboplatin (AUC 6 mg/ml.min) chemotherapy regimen (given every 21 days) and Eastern Cooperative Oncology Group performance status (ECOG-PS) of 0, 1, or 2 were included in the study. Evaluation for all the patients included comprehensive medical history, physical assessment and blood investigations.\u003c/p\u003e \u003cp\u003eAt the beginning of the study, the participants were given a diary and MASCC anti-emesis tool (MAT), for recording the incidence, severity, frequency, and duration of CINV, the oral intake, and/or hospitalization records.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) The questions include whether the patient developed CINV or not, the frequency of vomiting per day, and the grading of nausea. Nausea is rated on a scale from 0 to 10, where 0 indicates no nausea and 10 represents the most severe level.\u003c/p\u003e \u003cp\u003eThe anti-emetic regime consisted of a combination of an NK1-RA (fosaprepitant 150 mg on day 1), a 5-HT3 RA (palonosetron 0.25 mg on day 1), and steroid (dexamethasone 12 mg on day 1, then 8 mg on days 2 through 4).(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Following this the chemotherapy drugs were administered. Patients then documented vomiting frequency, as well as the presence and severity of nausea during both the acute (first 24 hours) and delayed phase (day 2 to 5). Additionally, they recorded oral intake and any hospital admissions following chemotherapy. To ensure accurate entries into the diary, compliance was checked telephonically and/or via text messaging.\u003c/p\u003e \u003cp\u003eGrading of CINV was done according to Common Terminology Criteria for Adverse Events (CTCAE). The primary endpoint was CTCAE grade 3 nausea and/or grade\u0026thinsp;\u0026ge;\u0026thinsp;2 vomiting.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) Patient related factors which included gender, age, hemoglobin value, creatinine clearance (using Cockroft-Gault equation), serum albumin, serum C- Reactive Protein (CRP), alcohol consumption (\u0026ge;\u0026thinsp;5 standard drinks per week) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), smoking history, history of motion sickness, expectation of CINV, anxiety [score\u0026thinsp;\u0026ge;\u0026thinsp;10 on the generalized anxiety disorder-7 (GAD-7) anxiety scale] (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), having meals before chemotherapy (within 6 hours), body mass index (BMI), metastatic versus non-metastatic disease, and location of the primary (gastrointestinal, gynaecological, lung, breast, and others) were assessed. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Statistical Analysis\u003c/h2\u003e \u003cp\u003eData analysis involved descriptive statistics, with means and standard deviations (SDs) calculated for continuous variables, and frequencies and percentages for categorical variables. Additionally, odds ratios (OR) and 95% confidence intervals (CI) were employed to evaluate the factors predicting emesis and nausea. The dependent variable was development of CINV. After univariate analysis, to identify the factors with the greatest potential contribution for the development of CINV, a removal criterion of p\u0026thinsp;\u0026gt;\u0026thinsp;0.20 was applied, and factors having p\u0026thinsp;\u0026lt;\u0026thinsp;0.20 were retained for further analysis.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) Utilizing these variables, multivariate logistic regression analysis using stepwise forward selection method was done. A p-value of less than 0.05 was regarded as statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Patient and Public Involvement\u003c/h2\u003e \u003cp\u003ePatients and members of the public were not involved in the design, conduct, reporting, or dissemination plans of this research\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant baseline demographics and clinical profile\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (%)\u003c/p\u003e \u003cp\u003en =\u0026nbsp;192\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u0026nbsp;(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.7\u0026nbsp;\u0026plusmn; 12.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (28.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (71.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eECOG PS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMetastatic disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88\u0026nbsp;(45.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104 (54.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSite of the cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynecological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88\u0026nbsp;(45.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026nbsp;(23.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u0026nbsp;(14.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u0026nbsp;(11.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026nbsp;(4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical\u0026nbsp;Factors\u0026nbsp;(mean\u0026nbsp;\u0026plusmn; SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u0026nbsp;(gm/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4\u0026nbsp;\u0026plusmn; 1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u0026nbsp;clearance\u0026nbsp;(mL/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.1\u0026nbsp;\u0026plusmn; 26.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum\u0026nbsp;albumin\u0026nbsp;(mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7\u0026nbsp;\u0026plusmn; 0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u0026nbsp;(mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.2\u0026nbsp;\u0026plusmn; 49.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNutritional\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026nbsp;(kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-treatment\u0026nbsp;meal\u0026nbsp;intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u0026nbsp;(\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBehavioral\u0026nbsp;and\u0026nbsp;psychological\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u0026nbsp;(21.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (28.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of\u0026nbsp;motion\u0026nbsp;sickness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67\u0026nbsp;(34.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpectation of\u0026nbsp;CINV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106\u0026nbsp;(55.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110\u0026nbsp;(57.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSD- Standard Deviation; ECOG PS- Eastern Cooperative Oncology Group Performance Status; CINV- Chemotherapy induced nausea vomiting; GI- Gastrointestinal; CRP- C-Reactive protein; BMI- Body Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe study comprised 192 patients in total, with 137 (71.4%) females. Mean age (\u0026plusmn;\u0026thinsp;SD) of the participants was 53.7 (\u0026plusmn;\u0026thinsp;12.0) years. 88 patients (45.8%) presented with metastatic disease at diagnosis. The primary cancer types were distributed as follows: gynecological (45.8%), lung (23.4%), breast (14.6%), gastrointestinal (11.4%), and other sites (4.8%). Other characteristics are as shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCINV result\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTCAE Grade (Median)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNausea score/ Vomiting frequency/day\u003c/p\u003e \u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute (Day 1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNausea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u0026nbsp;(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDelayed (Day 2 to Day 5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNausea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67\u0026nbsp;(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026nbsp;(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNausea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89\u0026nbsp;(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNausea and/or Vomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCTCAE- Common Terminology Criteria for Adverse Events; SD- Standard Deviation\u003c/p\u003e \u003cp\u003eAs shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, 90 patients (46.8%) developed CINV. As per the MAT response recorded, the mean (\u0026plusmn;\u0026thinsp;SD) score given for nausea severity was 4.4 (\u0026plusmn;\u0026thinsp;1.8), whereas mean (\u0026plusmn;\u0026thinsp;SD) frequency of vomiting per day was 5.0 (\u0026plusmn;\u0026thinsp;2.6).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIdentification of CINV predictors through univariate and multivariate analyses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnivariate\u0026nbsp;analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95%\u0026nbsp;CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026lt;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08\u0026ndash;3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u0026nbsp;sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18\u0026ndash;4.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMotion\u0026nbsp;sickness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u0026ndash;2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeals\u0026nbsp;prior\u003c/p\u003e \u003cp\u003eto\u0026nbsp;Chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55\u0026ndash;1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpectation of CINV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72\u0026ndash;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.52\u0026ndash;1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol\u0026nbsp;use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u0026ndash;1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35\u0026ndash;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (gm/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrCl (mL/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55\u0026ndash;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastatic\u0026nbsp;disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSite\u0026nbsp;of\u0026nbsp;the cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynecological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36\u0026ndash;6.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u0026ndash;4.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65\u0026ndash;5.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u0026ndash;7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMultivariate\u0026nbsp;analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAOR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95%\u0026nbsp;CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u0026nbsp;sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03\u0026ndash;4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026lt;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026ndash;3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCINV- Chemotherapy induced nausea vomiting; OR- Odds Ratio; CI- Confidence Interval; BMI- Body Mass Index; CrCl- Creatinine clearance; CRP- C-Reactive protein; GI- Gastrointestinal; AOR- Adjusted Odds Ratio\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eResults of univariate and multivariate logistic regression analysis are as shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The final model retained the variables female sex and age (\u0026lt;\u0026thinsp;60 years). Variables not retained in the model but considered included BMI, alcohol use, smoking history, creatinine clearance, and the site of cancer. It reveals that females have 2.28 times higher odds of developing CINV as compared to males. Age\u0026thinsp;\u0026lt;\u0026thinsp;60 years (OR\u0026thinsp;=\u0026thinsp;2.03) and BMI (OR\u0026thinsp;=\u0026thinsp;1.05) also revealed correlation with CINV. There was an inverse relationship between alcohol consumption (OR\u0026thinsp;=\u0026thinsp;0.59) and smoking (OR\u0026thinsp;=\u0026thinsp;0.66). In relation to the site of the cancer, gynecological site had an OR of 2.91 for CINV development, which was statistically significant. Biochemical parameter analysis revealed creatinine clearance having an OR of 1.01. Multivariate logistic regression analysis showed female patients have 2.05 times odds of developing CINV as compared to male patients, which was statistically significant.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eChemotherapy constitutes a fundamental component in the management of cancer and is commonly associated with a range of adverse effects including CINV, bone marrow suppression, diarrhoea, and hypersensitivity, amongst others. CINV is among the commonest adverse effects of chemotherapy, with an incidence of approximately 40% in various studies.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) CINV is generally categorized into two types: acute, which arises within the first 24 hours following treatment, and delayed, which occurs between 24 and 120 hours after chemotherapy administration.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) In our study, the incidence of CINV was found to be 46.8%.\u003c/p\u003e \u003cp\u003eSeveral factors may contribute to this increased incidence. Variations in patient specific factors influence susceptibility to CINV in different populations. This maybe a result of genetic variations in different populations affecting drug metabolism and receptor sensitivity. More patients developed delayed as compared to acute CINV. In the acute phase, 30% of the patients developed nausea and 15% had vomiting, whereas in the delayed phase, 35% of the patients had nausea and 21% had vomiting. Comparable findings have been reported in other studies, with acute nausea and vomiting occurring in 13% and 37% of patients, respectively, and delayed in 52% and 28%, respectively.(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) In order to minimize the occurrence of delayed CINV, it is essential to improve patient education by emphasizing the importance of continuing prescribed antiemetics at home, even in the absence of symptoms. Additionally, follow-up calls or tele-health check-ins within a few days of chemotherapy can reinforce adherence and allow timely management of emerging symptoms.\u003c/p\u003e \u003cp\u003eFor analyzing factors which predict CINV, initial univariate logistic regression analysis was done. A statistically significant association was observed between female sex and the risk of CINV (OR\u0026thinsp;=\u0026thinsp;2.28, 95% CI: 1.18\u0026ndash;4.38, p\u0026thinsp;=\u0026thinsp;0.01), indicating that females have 2.28 times higher odds of developing CINV as compared to males. This maybe due to a combination of hormonal, physiological, and pharmacological factors. Hormonal influences, particularly the presence of estrogen and progesterone, are believed to increase the sensitivity of the vomiting center, making women more susceptible to nausea. Difference in the body composition may also play a role, as females usually have a lower body surface area and body weight compared to males, which can affect the pharmacokinetics of chemotherapeutic drugs and increase their toxicity. Studies have shown an important correlation between single-nucleotide polymorphisms (SNPs) within estrogen-responsive elements of the TACR1 gene, which encodes the neurokinin-1 (NK1) receptor, and an increased occurrence of postoperative nausea and vomiting (\u003cspan additionalcitationids=\"CR25 CR26 CR27\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eYounger age (\u0026lt;\u0026thinsp;60 years) (OR\u0026thinsp;=\u0026thinsp;2.03, 95% CI: 1.08\u0026ndash;3.82, p\u0026thinsp;=\u0026thinsp;0.02) also revealed positive correlation with CINV. Studies have shown younger patients have higher incidence of CINV.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) This maybe due to more active central nervous system (CNS) and emetic reflex, making them more sensitive to chemotherapy. Older patients often have a diminished nausea and vomiting response, possibly due to age-related changes in the CNS or altered drug metabolism and clearance. Additionally, younger patients are usually given more aggressive chemotherapy regimens and tend to have fewer comorbidities, allowing for the administration of higher doses, which may increase the risk of CINV.\u003c/p\u003e \u003cp\u003eEighty-eight (45.8%) patients had metastatic disease. Presence of metastatic disease showed inverse correlation (OR\u0026thinsp;=\u0026thinsp;0.76, p\u0026thinsp;=\u0026thinsp;0.35) with the risk of CINV, although it was not statistically significant. Possible explanation for this may be psychological\u0026mdash;patients with non-metastatic disease often have higher expectations for cure and may be more anxious or emotionally reactive to treatment, which can heighten nausea perception. Additionally, they may receive more aggressive or high-dose chemotherapy regimens, especially in curative settings, which increases the emetogenic potential. Patients with advanced disease may have a blunted emetic response, possibly due to general debility, altered physiology, or adaptation over time to ongoing treatment.(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eGynecological malignancies had an OR of 2.91 (95% CI: 1.36\u0026ndash;6.22, p\u0026thinsp;=\u0026thinsp;0.006) for predicting CINV. Various studies have shown inconsistent results in regards to CINV risk correlation with the site of malignancy. While some reveal higher risk for breast cancer patients, others show lower risk for gynecological or genitourinary malignancies.(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) Biological differences between tumor types may influence how patients metabolize chemotherapeutic agents, potentially affecting emetogenic responses. Moreover, the site of cancer itself may be a risk factor for heightened gastrointestinal symptoms.(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe study revealed no statistically meaningful relationship between hemoglobin levels (OR\u0026thinsp;=\u0026thinsp;0.89, p\u0026thinsp;=\u0026thinsp;0.21) and the occurrence of CINV. CrCl revealed an OR of 1.01 for CINV, which was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.12). Age-related physiological changes may increase the risk of chemotherapy-related toxicity. Reduced CrCl has been linked to a higher incidence of fever, neutropenia, and hematologic toxicity. Therefore, assessing CrCl is essential when determining appropriate chemotherapy dosing so as to avoid toxicities.(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) CRP levels did not show a significant correlation with CINV. CRP elevation has shown correlation with mortality.(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAs far as nutritional factors are concerned, serum albumin is a proven marker of the nutritional well-being of patients. In our study higher serum albumin levels (OR\u0026thinsp;=\u0026thinsp;0.92, 95% CI: 0.55\u0026ndash;1.53, p\u0026thinsp;=\u0026thinsp;0.74) correlated with lower CINV risk, although the results were not statistically significant. Higher serum albumin level correlates with better survival also, whereas lower albumin level has shown correlation with higher incidence of chemotherapy induced toxicity.(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) This shows the importance of good nutrition and the value of a proper diet in the cancer patient undergoing chemotherapy. BMI (OR\u0026thinsp;=\u0026thinsp;1.05, 95% CI: 0.99\u0026ndash;1.1, p\u0026thinsp;=\u0026thinsp;0.08) demonstrated a correlation with CINV, although this association did not reach statistical significance. In other studies, lower BMI has shown correlation with higher risk of CINV.(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) To address the risks associated with poor nutrition, it is essential to prioritize nutritional assessment and intervention in cancer patients receiving chemotherapy. Early involvement of a clinical dietitian can help tailor individualized nutrition plans aimed at improving protein intake and overall caloric balance.\u003c/p\u003e \u003cp\u003eHaving meals prior to chemotherapy was protective of CINV, although it was not statistically significant.(OR\u0026thinsp;=\u0026thinsp;0.98, 95% CI 0.55\u0026ndash;1.74, p\u0026thinsp;=\u0026thinsp;0.94) Patients who do not eat prior to receiving chemotherapy were shown to be around seven times more prone to develop CINV compared to those who had a meal beforehand.(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) Patients must be encouraged to consume a light, well-balanced meal prior to chemotherapy, which can help reduce the CINV risk. An empty stomach may become more sensitive to the effects of chemotherapy, leading to greater irritation and discomfort. Without food to buffer the stomach lining, the risk of nausea increases. Additionally, low blood sugar levels caused by not having meals can contribute to feelings of weakness, dizziness, and nausea, compounding the effects of chemotherapy. Skipping meals can also lead to a heightened stress response, which may exacerbate gastrointestinal symptoms. Meal consumption can maintain the normal physiologic rhythm of the stomach, leading to reduced symptoms of nausea and vomiting. This demonstrates the importance of having small meals before starting treatment.(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eHistory of motion sickness showed no statistically significant correlation with CINV (OR\u0026thinsp;=\u0026thinsp;1.38, 95% CI: 0.76\u0026ndash;2.52, p\u0026thinsp;=\u0026thinsp;0.29), although it revealed a positive association. Prior motion sickness is a risk factor for CINV.(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e) Both CINV and motion sickness are mediated through the activation of the vomiting center located in brain which processes signals from the gastrointestinal tract, vestibular system, and bloodstream. Individuals prone to motion sickness often have a heightened sensitivity to nausea-inducing stimuli, such as movement or sensory mismatch, which may reflect a generally lower threshold for nausea that also increases susceptibility to CINV. Additionally, common neuro-chemical pathways, particularly involving serotonin (5-HT3) and dopamine, may play a role in both conditions, and certain genetic or receptor-based differences may predispose some individuals to experience both.\u003c/p\u003e \u003cp\u003eThe expectation of CINV was linked to an increased risk of experiencing CINV, with an OR of 1.27, 95% CI: 0.72\u0026ndash;2.26; however, this association was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.49). Similar results have been reported in other studies.(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e) The expectation of nausea is believed to be driven largely by psychological mechanisms. The CNS, particularly regions involved in memory, emotion, and stress including the amygdala and hypothalamus, plays a pivotal role in modulating this response. To mitigate this, behavioral interventions such as relaxation techniques, guided imagery, and meditation may be helpful. Factors like anxiety can further exacerbate this effect by causing alterations in gastric motility and secretions. It may lead to enhanced perception of nausea and vomiting.(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e) However, anxiety (OR\u0026thinsp;=\u0026thinsp;0.93, p\u0026thinsp;=\u0026thinsp;0.81) did not demonstrate a statistically significant correlation with CINV in our study.\u003c/p\u003e \u003cp\u003eAlcohol consumption (OR\u0026thinsp;=\u0026thinsp;0.59, 95% CI: 0.29\u0026ndash;1.21, p\u0026thinsp;=\u0026thinsp;0.15) and smoking history (OR\u0026thinsp;=\u0026thinsp;0.66, 95% CI: 0.35\u0026ndash;1.24, p\u0026thinsp;=\u0026thinsp;0.19) were found to inversely associate with CINV. Many studies have demonstrated this inverse correlation.(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e) Chronic alcohol exposure results in desensitization of the central vomiting center, particularly the chemoreceptor trigger zone (CTZ), thereby decreasing sensitivity to emetogenic stimuli. Additionally, alcohol affects key neurotransmitter systems involved in nausea and vomiting, such as serotonin, dopamine, and gamma-aminobutyric acid (GABA). Regular alcohol use may modulate these pathways in a way that diminishes the emetic response. While not a recommendation for alcohol consumption, this observed inverse relationship provides insight into the complex neurobiological factors influencing individual susceptibility to CINV.(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e) Similarly smokers have shown a lower incidence of CINV, although the results are contrasting for some studies.(\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) Natural killer (NK) cells, a type of large granular lymphocyte, play a key role in limiting the proliferation of damages cells. Studies have indicated that individuals who smoke tend to have fewer NK cells in circulation compared to non-smokers. This reduction in NK cell count has been linked to faster tumor growth and may intensify the adverse effects associated with cancer therapies.(\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe final model for CINV prediction retained the variable female sex (AOR\u0026thinsp;=\u0026thinsp;2.05, 95% CI: 1.03\u0026ndash;4.07, p\u0026thinsp;=\u0026thinsp;0.04), which was statistically significant. This implies that female patients have 2.05 times odds of developing CINV as compared to male patients. The higher CINV risk in females has been replicated in multiple studies.(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR54 CR55 CR56\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e) To address this increased risk, clinicians can employ more aggressive antiemetic strategies in female patients. This highlights the importance of personalized antiemetic strategies, particularly for high-risk groups like females.\u003c/p\u003e \u003cp\u003eUncontrolled CINV can lead to multiple clinical and treatment-related complications, including inadequate nutritional intake, weight loss, dehydration, and electrolyte imbalance, which can further compromise a patient's ability to tolerate ongoing treatment. It can also impair the quality of life, including physical, emotional, and social well-being, causing anxiety, sleep disturbances, and fatigue, which may persist even beyond the acute phase. The fear or experience of CINV may lead patients to delay or even refuse further chemotherapy cycles, potentially reducing the efficacy of cancer treatment. Recurrent or severe CINV episodes may necessitate additional medications, emergency visits, or hospital admissions, placing extra burden on healthcare systems already operating under resource constraints.(\u003cspan additionalcitationids=\"CR59 CR60\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThese issues along with the high CINV rates observed in our study underline the need for improved implementation of antiemetic prophylaxis, better patient education on early reporting of symptoms, and perhaps tailored antiemetic regimens based on patient-specific factors. Our study is the only study from an LMIC like India which has determined the incidence of CINV under routine clinic practice. This adds valuable real-world data to the existing literature, which is largely dominated by studies from high-income countries. In LMICs, where resource constraints and variability in treatment delivery are common, understanding the actual incidence and burden of chemotherapy-related side effects becomes even more critical for optimizing patient care.\u003c/p\u003e \u003cp\u003eOur study has certain limitations. All CINV results could not be monitored in-hospital and patient recorded data was collected, although diligent care was taken to record the data correctly and compliance was also ensured telephonically.\u003c/p\u003e"},{"header":"5.Conclusions","content":"\u003cp\u003eThis study highlights the crucial need to account for individual patient characteristics when developing and implementing antiemetic strategies for the control of CINV. While current clinical practice often follows standardized, guideline-recommended antiemetic protocols, these universal approaches may not adequately look into the diversity of the patients, particularly in lower-middle-income countries (LMICs). Despite appropriate adherence to these guidelines, a considerable number of patients in LMICs continue to suffer from significant CINV, suggesting that a one-size-fits-all model may fall short in practice. This disparity emphasizes the urgent necessity for more personalized and nuanced prophylactic strategies. Notably, female patients appear to be disproportionately affected and may benefit from more aggressive or tailored antiemetic interventions. Enhancing individualized care by integrating demographic and physiological variables such as gender could improve symptom control, patient comfort, and overall treatment adherence during chemotherapy. This can help reduce the psychological, physiological, and financial burden, especially in LMICs.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; AOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; BMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CINV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChemotherapy-induced nausea and vomiting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-Reactive Protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CTCAE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommon Terminology Criteria for Adverse Events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; ECOG PS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEastern Cooperative Oncology Group Performance Status\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; GI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGastrointestinal\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; LMIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow- and middle-income countries\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; MASCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMultinational Association of Supportive Care in Cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; MAT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMASCC anti-emesis tool\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; OR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; QoL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuality of Life\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee, AIIMS Rishikesh, AIIMS/IEC/23/359\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eAvailable on request to the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, MK and DS ; methodology MK,DS,AS,SG ; formal analysis, MK,DS,YB ; writing\u0026mdash;original draft preparation, MK ; \u0026nbsp; writing\u0026mdash;review and editing, MK,DS ; supervision, DS,AS All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eThis article is a revised and expanded version of a paper entitled Patient-specific factors as predictors of chemotherapy-induced nausea and vomiting: Insights from a lower-middle-income setting, which was presented at the ASCO 2025 annual meeting held at Chicago, Illinois, the USA on May 28, 2025 as E-poster.(62)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDranitsaris G, Molassiotis A, Clemons M, Roeland E, Schwartzberg L, Dielenseger P et al. 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J Clin Oncol. 2003;21(24):4524\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVandyk AD, Harrison MB, Macartney G, Ross-White A, Stacey D. Emergency department visits for symptoms experienced by oncology patients: a systematic review. Support Care Cancer. 2012;20(8):1589\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlepin HD, Pitcher BN, Ballman KV, Kornblith AB, Hurria A, Winer EP, et al. Comorbidity, Chemotherapy Toxicity, and Outcomes Among Older Women Receiving Adjuvant Chemotherapy for Breast Cancer on a Clinical Trial: CALGB 49907 and CALGB 361004 (Alliance). J Oncol Pract. 2014 Sept;10(5):e285\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKapoor M, Sundriyal D, Sehrawat A, Bahurupi YA. Patient-specific factors as predictors of chemotherapy-induced nausea and vomiting: Insights from a lower-middle-income setting. J Clin Oncol. 2025 June;43(16suppl):e24075\u0026ndash;24075.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CINV, LMIC, Incidence, Chemotherapy induced nausea vomiting, Lower-middle-income countries, Patient specific factors","lastPublishedDoi":"10.21203/rs.3.rs-8607432/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8607432/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003e Chemotherapy-induced nausea and vomiting (CINV) persists in a substantial proportion of patients despite guideline-based antiemetic prophylaxis. Current preventive strategies largely emphasize chemotherapy-related risk, with limited consideration of patient-specific factors. This study aimed to identify patient-related predictors of CINV.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eThis single-center longitudinal observational study was conducted at a tertiary care center in North India. Adult patients (\u0026ge;\u0026thinsp;18 years) with solid organ malignancies treated with carboplatin\u0026ndash;paclitaxel and uniform antiemetic prophylaxis were enrolled. Demographic, clinical, biochemical, lifestyle, psychological, and disease-related variables were assessed. Multivariate logistic regression analysis was performed to identify independent predictors of CINV.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eA total of 192 patients were included (mean age 53.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0 years), of whom 71.4% were female and 45.8% had metastatic disease. Gynecological cancers were the most common (45.8%), followed by lung (23.4%), breast (14.6%), and gastrointestinal malignancies (11.4%). The overall incidence of CINV was 46.8%. Univariate analysis demonstrated higher CINV risk in patients aged\u0026thinsp;\u0026lt;\u0026thinsp;60 years (OR 2.03), females (OR 2.28), those with higher BMI (OR 1.05) and creatinine clearance (OR 1.01), and those with gynecological cancers (OR 2.91), while alcohol use (OR 0.59) and smoking (OR 0.66) were associated with lower risk. On multivariate analysis, female sex was the only independent predictor of CINV (OR 2.05).\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eNearly half of patients experienced CINV despite standardized prophylaxis. Female sex emerged as the strongest independent risk factor, underscoring the importance of incorporating patient-specific characteristics into individualized antiemetic decision-making to improve symptom control and treatment outcomes\u003c/p\u003e","manuscriptTitle":"Predictive Patient Characteristics for Chemotherapy-Induced Nausea and Vomiting in Solid Organ Cancers: An Observational Study from a Tertiary Care Setting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-17 11:23:20","doi":"10.21203/rs.3.rs-8607432/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-11T12:27:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T09:39:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-12T15:44:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50712651017406643277821321143397884677","date":"2026-02-12T07:11:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327241866421672226795228314746939569410","date":"2026-02-11T06:10:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-11T05:15:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-19T11:11:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-15T12:27:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-15T12:25:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2026-01-15T06:04:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8f0db36e-801e-47b4-b4f6-59d841f7f718","owner":[],"postedDate":"February 17th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-11T12:27:19+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T12:58:53+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-17 11:23:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8607432","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8607432","identity":"rs-8607432","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}