Clinical and immune features associated with chromosome 13q deletion and PRKCSH downregulation in newly diagnosed multiple myeloma.

Rare variants in inborn errors of immunity genes in young adults with severe COVID-19: Insights from a Brazilian cohort.

Background : Recurrent infections in children may occur despite normal baseline immune function, highlighting the need for targeted immunomodulatory interventions. Prior use of other immunomodulators, such as bacterial lysates and beta-glucans, can influence immune parameters and should be considered when interpreting treatment effects. Objective : To evaluate the short-term effects of inosine acedoben dimepranol (IAD) on immune cell subsets and activation markers in two pediatric patients with recurrent infections. Methods : Two children aged 3 years with frequent infections but normal routine immunological screening were treated with IAD for a brief 7-day period as part of a broader adjunctive immunotherapy regimen, including other immunomodulators. Comprehensive immunophenotyping of T, B, and natural killer (NK) cells, as well as subset-specific naïve, memory, and activation markers (CD38, CD25, and HLA-DR), was performed before and after therapy using flow cytometry. Results : Baseline analysis revealed distinct immune dysregulation patterns: B-cell predominance in one patient and T-cell, mainly CD4+, expansion in the other, accompanied by evidence of chronic immune activation. Following short-term IAD administration, both patients demonstrated case-specific, transient immunological changes, including partial normalization of naïve CD4+ T-cell proportions, reduction of some activation markers, and modest changes in memory B-cell subsets. Absolute lymphocyte counts and subset dynamics were consistent with short-term clinical observations. No adverse effects were observed during treatment. Conclusion : Short-term IAD therapy was associated with preliminary, case-specific modulation of lymphocyte compartments and partial attenuation of chronic immune activation. Given the brief duration and concurrent use of other immunomodulators, these findings should be interpreted cautiously. Nevertheless, detailed immunophenotyping can provide valuable insights to guide individualized adjunctive immunomodulatory therapy in pediatric patients.

Exacerbations of asthma-chronic obstructive pulmonary disease overlap (EACO) are associated with high mortality, yet the acute-phase heterogeneity remains poorly characterized. This study aimed to identify distinct inflammatory phenotypes of EACO during hospitalization and evaluate their associations with clinical outcomes. A prospective two-centre cohort study enrolled 2444 EACO patients (training and validation cohort). Baseline inflammatory markers and clinical data were collected. Unsupervised k-means clustering identified inflammatory phenotypes, with sensitivity analysis excluding demographic variables. In-hospital clinical outcomes (ICU admission, invasive ventilation, in-hospital mortality) were assessed. Logistic regression and causal mediation analysis evaluated phenotype-outcome associations. A nomogram was developed and validated using receiver operating characteristic curves (AUC). Three distinct phenotypes were identified: Cluster T1 (neutrophil-to-lymphocyte ratio [NLR]-elevated hypoeosinophilic systemic inflammatory), Cluster T2 (eosinophilic), and Cluster T3 (eosinophil-neutrophil balanced). Cluster T1 exhibited systemic hyperinflammation (elevated white blood cell count, neutrophils, NLR, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6)), and the highest composite adverse outcome rate (24.2%; p < 0.001). Logistic regression revealed absolute neutrophil count (β = 0.38, p < 0.001), D-dimer (β = 0.25, p < 0.001), and absolute lymphocyte count (β = -0.41, p < 0.001) as key outcome predictors, confirmed by causal mediation analysis. The nomogram showed robust predictive performance (AUC training = 0.775; validation = 0.766). Inflammatory phenotypes during EACO predict differential in-hospital outcomes, with neutrophil-dominant phenotypes conferring the highest risk. Early phenotype-based risk stratification using simple blood biomarkers may guide individualized EACO management.

Background Sepsis is a life-threatening syndrome of immune dysregulation; preexisting lymphopenia and an elevated neutrophil-to-lymphocyte ratio (NLR) heighten host susceptibility. Chronic low-dose exposure to lead (Pb), cadmium (Cd), and mercury (Hg) is immunotoxic, but its association with these pre-sepsis markers in the general population remains unclear. Methods We analyzed 12,580 adults from NHANES 2011–2018. Outcomes were lymphopenia (absolute lymphocyte count <1.0 × 109/L) and high NLR (top quartile). Survey-weighted logistic and Weighted Quantile Sum (WQS) regressions evaluated individual and joint mixture effects. Restricted cubic splines modeled dose–response relationships. Continuous exposure models were also constructed to minimize information loss. Results Fully adjusted models showed higher quartiles of Pb, Cd, and Hg were each associated with greater odds of lymphopenia and high NLR. Comparing highest to lowest quartiles, ORs for lymphopenia were 1.85 (95% CI 1.42–2.41) for Pb, 1.66 (95% CI 1.28–2.15) for Cd, and 1.52 (95% CI 1.15–2.01) for Hg. Continuous models confirmed that each log2-fold increase in blood metals was associated with significantly reduced absolute lymphocyte counts and elevated NLR (all p < 0.05). The WQS index was positively associated with lymphopenia (OR 1.63) and high NLR (OR 1.48). Conclusion In a nationally representative sample, chronic low-level exposure to Pb, Cd, and Hg was independently associated with an immune profile linked to sepsis susceptibility, suggesting environmental metal reduction as a potential population-level strategy to reduce sepsis risk.

Inborn errors of energy metabolism (IEEM) are inherited conditions that typically present with impaired mitochondrial energy production and multisystem involvement, leading to adverse developmental outcomes. Iron is essential for mitochondrial function, and its deficiency may influence disease manifestations. The study aimed to evaluate the frequency of anemia and assess red blood cell indices, including the Mentzer Index (MI), in children with IEEM. This prospective observational study analyzed RBC indices in children (0-3 years) with clinically detected IEEM. Anemia was defined as per WHO criteria: hemoglobin < 11g/dL (6-59 months). The MI was calculated and compared with age-matched controls. Anemia was observed in both the IEEM and control groups, with no significant difference between the two. Among individuals with IEEM, 78.3% had an MI ≥ 13, compared with 88.5% of controls; the difference was not statistically significant. Network analysis of complete blood count parameters demonstrated distinct clustering patterns in the IEEM group compared to controls. Although the proportion of lymphocytes and absolute lymphocyte counts were higher in the IEEM group, these differences were not statistically significant. Anemia was prevalent in both groups, with no significant difference observed between IEEM and controls. Network analysis demonstrated variations in hematological patterns; however, these findings are exploratory and do not establish underlying mechanisms. They may reflect complex interactions between metabolic and hematological factors. CTRI Number: CTRI/2023/11/060330.

Postoperative refractory hypoxemia (PRH) remains a clinically important pulmonary complication after surgery for acute type A aortic dissection (ATAAD). Because inflammation, coagulation activation, pulmonary vulnerability, and operative stress converge during ATAAD repair, a composite biomarker may provide more useful risk information than a single leukocyte-derived index. We evaluated whether the preoperative systemic immune-inflammation index (SII) was independently associated with PRH and whether it improved risk prediction beyond conventional clinical, pulmonary, and biomarker variables. In this single-center retrospective cohort study, 490 patients undergoing surgery for ATAAD between January 2018 and December 2024 were analyzed. SII was calculated from absolute platelet, neutrophil, and lymphocyte counts and modeled primarily as a log2-transformed continuous variable, so that odds ratios represented the association per doubling of SII. The primary preoperative model included admission/preoperative variables, whereas an expanded perioperative model was used as a sensitivity analysis. Model discrimination, reclassification, decision-curve performance, and calibration were evaluated, and internal validation was performed using 1000 bootstrap resamples. PRH occurred in 158 of 490 patients (32.2%). Preoperative SII was higher in patients who developed PRH than in those who did not [1899.5 (1140.1-3043.6) vs. 667.5 (408.7-1173.7), P < 0.001]. In the primary preoperative prediction model, each doubling of SII was independently associated with PRH [adjusted odds ratio (OR), 2.80; 95% CI, 2.20-3.56; P < 0.001]. The base preoperative model had an AUC of 0.750 (95% CI, 0.705-0.794), whereas the SII-augmented model had an AUC of 0.846 (95% CI, 0.810-0.880). SII yielded the numerically largest incremental discrimination among SII, NLR, PLR, and MLR. Bootstrap validation of the SII-augmented model produced an optimism-corrected AUC of 0.834, calibration slope of 1.00, calibration intercept of 0.00, and Brier score of 0.153. Preoperative SII was independently associated with PRH after ATAAD surgery and provided incremental predictive information beyond conventional preoperative clinical, pulmonary, and biomarker variables. These findings support SII as a clinically accessible adjunctive risk-stratification marker rather than a stand-alone decision tool; external or temporal validation is required before routine implementation.

Development and validation of a nomogram model for mortality risk in burn patients: Triglyceride-glucose index as an independent novel prognostic marker.

Lymphopenia has been associated with poor outcomes in metastatic breast cancer (BC), but its prognostic relevance in early-stage disease remains unclear. This study aimed to evaluate the prognostic value of baseline lymphopenia in patients with non-metastatic BC using data from the prospective French CANTO cohort (NCT01993498). 10,854 patients with baseline absolute lymphocyte count (ALC) were analysed. Lymphopenia was defined as ALC < 1.0 × 10⁹ cells/L, measured before any cancer treatment. Relapse-free survival (RFS), overall survival (OS), and treatment-related toxicities were assessed using Kaplan-Meier estimates, piecewise-Cox regression models, and cause-specific hazard analyses considering pre-specified time periods. Baseline lymphopenia was observed in 342 patients (3.1%). It was associated with ECOG performance status > 0, hypoalbuminemia, and prior neoplasia. Lymphopenia correlated with inferior 5-year RFS (89.1% vs. 92.9%) and OS (92.5% vs. 96.4%). In multivariable analyses, lymphopenia was associated with increased risk of early relapse during the first 24 months (HR = 2.11; 95%CI: 1.28-3.48; p = 0.003), but not beyond, and no independent prognostic impact on OS was observed. No significant differences were found in surgical complications or chemotherapy dose intensity, though granulocyte colony-stimulating factor use was higher among lymphopenic patients. Baseline lymphopenia is uncommon in early BC but may serve as a marker of early relapse risk. Although it does not independently predict long-term survival, its presence could reflect underlying tumour aggressiveness or patient frailty. These findings support further investigation of lymphocyte subpopulations to refine prognostic stratification in early BC. Approved by French ethics committee in 2011 (ID-RCB:2011-A01095- 36,11-039 /NCT01993498 [20FEB2012]).

This study assessed the diagnostic value of complete blood count (CBC) and derived immune-inflammatory indicators for Mycoplasma pneumoniae pneumonia (MPP) in children and developed a practical scoring system for early diagnosis. A total of 1662 MP-infected children were divided into pneumonia (n = 844) and non-pneumonia (n = 818) groups. CBC parameters, derived immune-inflammatory indicators and C-reactive protein (CRP) were compared. Diagnostic performance was assessed using ROC curve analysis, and diagnostic models were constructed using multivariate logistic regression. Age-stratified analysis addressed confounding. Model stability was evaluated via repeated stratified 10-fold cross-validation, calibration curves with Brier score, and decision curve analysis (DCA). A simplified scoring system was established and validated for clinical application. Children in the pneumonia group were significantly younger (mean age 5.78 ± 3.41 years vs. 8.62 ± 4.92 years, p < 0.001). Lymphocyte count (LYM), lymphocyte percentage (LYM%), platelet count (PLT), plateletcrit (PCT), and the product of absolute lymphocyte count and platelet count (PLT × LYM) in the pneumonia group were significantly higher than in the non-pneumonia group. Age-stratified analysis confirmed these differences across all age subgroups (all p < 0.001). PLT × LYM, LYM%, PLT, and PCT were independent predictors. Internal validation showed a mean AUC of 0.7824 ± 0.0353, good calibration (Brier score = 0.1918 ± 0.0164), and positive net benefit on DCA. The scoring system achieved diagnostic rates of 71.5%, 51.2%, and 29.6% for high-, medium-, and low-risk groups, respectively. MPP predominantly affects children under 7 years old. The simple scoring system, supported by robust internal validation, effectively stratifies pneumonia risk and offers a practical early diagnostic tool for primary care.

Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide. Tools based on routinely collected variables may help identify prevalent CRC status and support clinical evaluation. Traditional approaches often rely on limited predictors and may not capture the multidimensional nature of CRC. Data were obtained from the National Health and Nutrition Examination Survey 1999–2018. Among 53,881 participants, 420 reported physician-diagnosed CRC (MCQ220). A 1:10 stratified case-control sample was constructed (420 cases, 4200 controls) and randomly split into training (70%) and internal validation (30%) sets. Missing data were imputed separately in the training and validation sets using a random forest–based method. SMOTE was applied only to the training set. Logistic regression, random forest, support vector machine, k-nearest neighbors, and extreme gradient boosting (XGBoost) were compared. Performance was primarily assessed by discrimination in the held-out validation set. For the final XGBoost model, exploratory post hoc probability calibration analyses were performed on validation-set predictions using raw probabilities, prior prevalence correction, and Platt scaling. Model interpretability was examined using Shapley Additive Explanations (SHAP), and a web-based CRC status classifier was developed. XGBoost showed the best discrimination in the validation cohort, with an area under the receiver operating characteristic curve of 0.787 (95% confidence interval 0.749–0.825). At the Youden-index cutoff, sensitivity was 77.0%, specificity 67.6%, PPV 19.2%, and NPV 96.7%. In exploratory probability-based analyses, decision curve analysis using Platt-scaled probabilities showed greater net benefit than treat-all and treat-none strategies across low-to-moderate threshold probabilities. post hoc calibration analyses fitted and assessed on the validation-set predictions showed improved apparent agreement after Platt scaling, with a Brier score of 0.191 and a Hosmer–Lemeshow P value of 0.086. SHAP identified key predictors, including alcohol use, hypertension, age, triglycerides, absolute lymphocyte count, blood lead, serum cotinine, and neutrophil-to-lymphocyte ratio. An interpretable machine learning framework integrating multidomain predictors enabled effective CRC status classification in a large population-based cohort. Discrimination was strong, whereas probability-based outputs after post hoc calibration should be considered exploratory pending independent confirmation. The model may support clinical evaluation and triage for individuals requiring further assessment.

Erectile dysfunction (ED) is a vascular disease associated with systemic inflammation and endothelial dysfunction. The role of inflammatory markers in the pathogenesis of ED is gaining increasing importance. This study aimed to evaluate the relationship between the Inflammatory Burden Index (IBI), calculated by combining C-reactive protein (CRP) and neutrophil-lymphocyte ratio (NLR), and erectile dysfunction. This retrospective study included 126 patients with erectile dysfunction and 128 healthy controls who presented to the urology outpatient clinic between January 2023 and October 2025. Erectile function was assessed using the International Index of Erectile Function-5 (IIEF-5). NLR was calculated as the ratio of absolute neutrophil count to absolute lymphocyte count, and IBI was obtained using the formula CRP × NLR. Diagnostic performance was examined using ROC analysis. Multivariate logistic regression analysis was performed to identify independent risk factors for erectile dysfunction. IBI values were found to be significantly higher in the ED group compared to the control group (median 3.31 vs. 0.91, p < 0.001). No significant difference was found between the groups in terms of NLR. There was no significant difference in IBI values between the ED severity groups (p = 0.346). ROC analysis showed modest discriminatory ability of IBI for ED (AUC = 0.754; 95% CI: 0.696-0.813; p < 0.001). Based on the Youden index, the optimal cutoff value was 3.785, with sensitivity 43.7% and specificity 84.3% (Youden index = 0.280). Additionally, a weak positive correlation was found between IBI and body mass index (r = 0.197; p = 0.027). In multivariate logistic regression analysis, diabetes mellitus and cardiovascular disease were identified as independent predictors of erectile dysfunction, while IBI was not found to be an independent predictor. IBI levels were significantly higher in patients with erectile dysfunction and may reflect systemic inflammatory burden associated with ED. However, because IBI was not an independent predictor in multivariable analysis and its discriminatory performance remained modest, its clinical utility as a standalone diagnostic or screening marker appears limited.

Correlation of skeletal muscle and visceral adipose tissue measured by computed tomography with neoadjuvant chemoradiotherapy related efficacy and toxicity in esophageal squamous cell carcinoma: A retrospective analysis from a large prospective cohort.

To evaluate the clinical value of serum superoxide dismutase (SOD) in anti-synthetase syndrome-related interstitial lung disease (ASyS-ILD). We conducted a retrospective study of 153 patients with anti-synthetase syndrome-associated interstitial lung disease (ASyS-ILD) at the Second Affiliated Hospital of Chongqing Medical University. Data collected included demographics, laboratory parameters [hemoglobin, absolute neutrophil count, absolute lymphocyte count, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), creatine kinase (CK), lactate dehydrogenase (LDH), serum ferritin, serum superoxide dismutase (SOD), and myositis-specific antibodies], lung high-resolution computed tomography (HRCT) findings, treatment regimens, and recurrence. For comparison, serum SOD levels were also measured in 153 healthy individuals who served as the control group. Compared with the healthy control group, the serum SOD level in the ASyS-ILD group was significantly decreased (P < 0.001). The serum SOD level after treatment was higher than that before treatment (P < 0.001). In ASyS-ILD patients, the serum SOD level was significantly negatively correlated with ESR (r = - 0.281, P < 0.001); CRP (r = - 0.262, P < 0.001); CK (r = - 0.3678, P < 0.001); LDH (r = - 0.446, P < 0.001); and ferritin (r = - 0.508, P < 0.001). The serum SOD level in patients with anti-PL-7 antibodies was significantly lower than that in the anti-EJ group (P = 0.039). The serum SOD level in the ASyS-ILD recurrence group was significantly lower than that in the stable group (P = 0.001). The serum SOD level was an independent risk factor for disease recurrence in ASyS-ILD patients (P = 0.037). In patients with ASyS-ILD, low serum SOD levels indicate the presence of oxidative stress. Serum SOD levels decrease in response to increasing inflammation in ASyS-ILD, suggesting that SOD can be used as a valid indicator of disease activity. The serum SOD levels in patients with ASyS-ILD are closely related to recurrence and deserve attention from rheumatologists. Key Points • Our study is the first to explore the relationship between SOD and ASyS-ILD. • This study demonstrates that SOD can serve as a simple and effective biomarker for evaluating the disease activity and recurrence of ASyS-ILD, which provides relevant information for clinical practice and a reliable basis for follow-up studies.

Recombinant human interleukin-7 for patients with infection-associated lymphopenia: a systematic review and meta-analysis.

This study aimed to develop an artificial intelligence (AI) web application for predicting chemotherapy-induced neutropenia (CIN) in patients with non-small cell lung cancer (NSCLC). We conducted a prospective study including 310 patients who underwent 1047 chemotherapy cycles with NSCLC patients between 2019 and 2024 from Tianjin Medical University General Hospital. Detailed clinical information and laboratory data were collected. The dataset was randomly split into a training set (80%) and a test set (20%) at the patient level. Machine learning was employed to develop the model. After completing training and hyperparameter optimization (HPO) through cross-validation on the training set, the performance was compared through the test set. Meanwhile, a stacking ensemble model was developed by integrating these optimized base learners described above. Standard evaluation metrics, such as area under the receiver operating curve (AUC), Accuracy, Recall, Precision, and F1 score, and Brier score, were used for discrimination of the model. To enhance the transparency of the optimal model, the shapley additive explanations (SHAP) were used together with the Local interpretable model-agnostic explanations (LIME) and the partial dependence plot (PDP) techniques. Based on the best machine learning-based model, an AI application was developed on the Internet. The categorical boosting (CatBoost) model with an AUC of 0.849 (95% Cl: 0.788-0.905), an accuracy of 0.813, a recall of 0.814, a specificity of 0.813, a F1 score of 0.642, and a Brier score of 0.141 had a higher discriminatory capability than other models. The five most significant features in the model were identified as body surface area, lymphocyte count, body mass index (BMI), absolute neutrophil count, and chemotherapy regimen. Notably, body surface area emerged as the most influential factor for predicting outcomes. Specifically, higher body surface area level was associated with an increased risk of CIN. The chemotherapy regimen of Paclitaxel + Carboplatin and Paclitaxel + Cisplatin showed a positive correlation with the risk of CIN. Lower lymphocyte count, BMI, and absolute neutrophil count were indicative of a higher risk of CIN. The AI application has been deployed online at http://39.96.172.15/, based on the CatBoost model. The CatBoost model exhibited strong discriminatory ability in predicting CIN risk in NSCLC patients. The developed AI model serves as a valuable tool to enhance clinical decision-making.

The impact of rabbit anti-thymocyte globulin (thymoglobulin) timing and dosing on pediatric stem cell transplantation outcomes: Time to move forward.

Sepsis is a syndrome in which immune recovery is impaired and the clinical course becomes more severe, particularly in older patients. Although lymphopenia is an easily monitored indicator of sepsis-associated immune dysfunction, the clinical significance of daily lymphocyte changes during the first week in older intensive care patients remains unclear. This study evaluated associations between absolute lymphocyte count (ALC) dynamics, 28-day mortality, and a culture-based secondary microbiological outcome in patients aged ≥ 65 years with sepsis. In this single-center retrospective cohort, patients aged ≥ 65 years admitted from the emergency department to the ICU with sepsis between January 1, 2022 and December 31, 2025 were included. Daily ALC during days 1-7 was categorized as no lymphopenia (≥ 1000 cells/mm³), moderate lymphopenia (500-999 cells/mm³), or severe lymphopenia (< 500 cells/mm³). The primary outcome was 28-day all-cause mortality; the secondary outcome was 28-day nosocomial culture positivity. Among 566 patients, the mean age was 80.7 ± 8.0 years, 48.2% were female, and 28-day mortality was 41.0%. ALC was available for all patients through ICU day 3 and for 514/566 patients (90.8%) on ICU day 7; later non-availability reflected shortened observation time rather than random laboratory omission. Severe lymphopenia declined from 33.9% on day 1 to 24.7% on day 7. Mortality was highest in severe lymphopenia, with FDR-corrected significance on day 2 and days 4-7. In the prespecified day-4 multivariable model, severe lymphopenia was independently associated with mortality (aOR 1.84, 95% CI 1.08-3.14; p = 0.025), whereas moderate lymphopenia was not. Increasing severe-lymphopenia burden was also associated with mortality during days 1-4 (aOR 1.16; p = 0.033) and days 1-7 (aOR 1.13; p = 0.013). Nosocomial culture positivity showed unadjusted late-week associations, but not after adjustment. In older ICU patients with sepsis, day-4 severe lymphopenia and first-week severe-lymphopenia burden were associated with 28-day mortality. The culture-based secondary outcome was not confirmed after adjustment and should be considered exploratory. First-week ALC monitoring may aid bedside risk stratification, but prospective multicenter validation is needed.

Glioblastoma is a highly aggressive primary brain malignancy characterized by poor median survival despite trimodal therapy. While established prognostic factors exist, significant heterogeneity in patient outcomes persist. This study aims to evaluate whether white-cell differentials predict oncologic outcomes in glioblastoma (GBM). We retrospectively analyzed 85 GBM patients treated with standard surgery, radiotherapy (60Gy in 30 fractions), and temozolomide. Clinical data (age, Karnofsky performance status, extent of resection, MGMT methylation, corticosteroid use, dosimetric data) and hematologic indices (absolute lymphocyte count (ALC), neutrophil-to-lymphocyte ratio (NLR), absolute eosinophil (AEC) and basophil counts, etc.) were collected at baseline and up to 3 months post-chemoradiation. Median overall survival (OS) in our cohort was 22.5 months (95% CI, 20.4-32.2). On univariate analysis, higher AEC correlated with improved OS at baseline (HR 0.68; p = 0.013) and at 2 months (HR 0.58; p = 0.019). In the combined multivariable model-controlling for age, extent of resection, MGMT status, KPS, steroid use, and % of brain volume receiving 60Gy) -baseline AEC remained independently prognostic (aHR 0.64; p = 0.021). Baseline eosinophils were independently associated with improved survival. Such findings highlight the importance of host immunity and baseline eosinophils as a potential prognostic marker of OS in GBM and warrant larger, prospective studies on prognostic marker validation.

BackgroundImmune checkpoint inhibitor (ICI) eligibility is primarily guided by tumor-centric biomarkers that do not fully account for the host's systemic immune competence. Emerging evidence suggests that readily available hematologic indices absolute lymphocyte count (ALC) and neutrophil-to-lymphocyte ratio (NLR) are associated with treatment outcomes in patients receiving ICIs, yet these markers are not routinely integrated into pre-treatment assessment.ObjectiveTo propose a structured, pharmacist-led pre-infusion screening approach using ALC and NLR as adjunctive markers of host immune reserve prior to ICI therapy.MethodsA pragmatic traffic-light workflow is described in which oncology pharmacists review complete blood count results within 48 h before infusion and flag patients with lymphopenia or elevated inflammatory indices for clinician reassessment during early ICI cycles.Key FindingsALC and NLR are inexpensive, routinely available biomarkers associated with clinical outcomes in ICI-treated patients. Evidence supporting definitive treatment thresholds remains limited and heterogeneous; the proposed framework should therefore function as a structured prompt for multidisciplinary reassessment rather than a rigid eligibility criterion.ConclusionThe conceptual integration of host immune indices into oncology pharmacy practice is worthy of structured investigation. A pharmacist-led screening workflow may support safer and more deliberate ICI initiation by identifying reversible causes of immune suppression. Prospective validation is required before routine implementation.