Cost-Effectiveness of Adjuvant Abemaciclib and Ribociclib in High-Risk Hormone Receptor-Positive Early Breast Cancer: An Indian Perspective.

PURPOSE: Incorporating adjuvant cyclin-dependent kinase (CDK) 4/6 inhibitors abemaciclib and ribociclib along with endocrine therapy has been shown to improve invasive disease-free survival (iDFS) for hormone receptor-positive (HR+) human epidermal receptor 2-negative (HER2-) early breast cancer (EBC). This study assesses the cost-effectiveness of this strategy, along with adjuvant aromatase inhibitors from an Indian perspective. METHODS: A Markov chain model evaluated the cost-effectiveness of abemaciclib and ribociclib with letrozole compared with letrozole alone for HR+/HER2- EBC from a payer perspective in India. Key measures included lifetime quality-adjusted life-years (QALY), life-years (LY), and total costs. This study explores two scenarios for effectiveness: a best-case (BC) scenario, where the benefit of CDK4/6 inhibitors in improving iDFS lasts a lifetime, and a worst-case (WC) scenario, where benefits disappear after 5 years. Probabilistic sensitivity analyses (PSA) were used to account for simulation uncertainty. RESULTS: In the BC scenario, abemaciclib added 2.17 QALY and 4.96 LY, incurring ₹2,317,957.7 ($27,756.65 in US dollars [USD]) in additional costs. However, the incremental cost-effectiveness ratio (ICER) for abemaciclib exceeded India's willingness-to-pay threshold in the BC and WC scenarios. In the BC scenario, ribociclib added 0.98 QALY and 2.58 LY with added costs of ₹1,711,504.32 ($20,494.6 USD). The ICER for ribociclib also surpassed India's threshold in both scenarios. PSA showed that neither drug was cost-effective at the current market prices in either BC/WC scenario. The cost of abemaciclib and ribociclib needs to be reduced by at least 78.61% and 87.19%, respectively, to be cost-effective in the BC scenario. CONCLUSION: The combination of adjuvant abemaciclib or ribociclib with letrozole is not cost-effective for HR+/HER2- EBC in India in either the BC or WC scenario.

Improving lung nodule segmentation in thoracic CT scans through the ensemble of 3D U-Net models.

PURPOSE: The current study explores the application of 3D U-Net architectures combined with Inception and ResNet modules for precise lung nodule detection through deep learning-based segmentation technique. This investigation is motivated by the objective of developing a Computer-Aided Diagnosis (CAD) system for effective diagnosis and prognostication of lung nodules in clinical settings. METHODS: The proposed method trained four different 3D U-Net models on the retrospective dataset obtained from AIIMS Delhi. To augment the training dataset, affine transformations and intensity transforms were utilized. Preprocessing steps included CT scan voxel resampling, intensity normalization, and lung parenchyma segmentation. Model optimization utilized a hybrid loss function that combined Dice Loss and Focal Loss. The model performance of all four 3D U-Nets was evaluated patient-wise using dice coefficient and Jaccard coefficient, then averaged to obtain the average volumetric dice coefficient (DSCavg) and average Jaccard coefficient (IoUavg) on a test dataset comprising 53 CT scans. Additionally, an ensemble approach (Model-V) was utilized featuring 3D U-Net (Model-I), ResNet (Model-II), and Inception (Model-III) 3D U-Net architectures, combined with two distinct patch sizes for further investigation. RESULTS: The ensemble of models obtained the highest DSCavg of 0.84 ± 0.05 and IoUavg of 0.74 ± 0.06 on the test dataset, compared against individual models. It mitigated false positives, overestimations, and underestimations observed in individual U-Net models. Moreover, the ensemble of models reduced average false positives per scan in the test dataset (1.57 nodules/scan) compared to individual models (2.69-3.39 nodules/scan). CONCLUSIONS: The suggested ensemble approach presents a strong and effective strategy for automatically detecting and delineating lung nodules, potentially aiding CAD systems in clinical settings. This approach could assist radiologists in laborious and meticulous lung nodule detection tasks in CT scans, improving lung cancer diagnosis and treatment planning.

Anti-Emetics in Children Receiving Chemotherapy for Solid Tumors and Leukemia: Pharmacology and Optimization of Therapy for Nausea and Vomiting.

The management of chemotherapy-induced nausea and vomiting (CINV) in children remains challenging due to differences in the chemotherapy regimens, their relative emetogenicity compared to that in adults and differences in drug metabolism and the available formulations. The common four classes of anti-emetics used for the treatment and prophylaxis of CINV in children include dexamethasone, neurokinin-1 receptor antagonists, 5-hydroxytryptamine-3 receptor antagonists (5HT3RAs), and olanzapine. The appropriate dose of dexamethasone for CINV prophylaxis in children is unknown, with a significant variability in dosage ranging between 6 and 32 mg/m2/day. The dose of dexamethasone is decreased by 30% when this drug is combined with (fos)aprepitant in children, in contrast to a decrease of 50% required in adults. The use of aprepitant in younger children (<12 years) is often hampered by the non-availability of oral suspension formulations in many countries; alternatively, 80 mg capsules are administered for 1-3 days in certain institutes to children weighing between 15 and 40 kg. Among the different 5HT3RAs, palonosetron is comparatively metabolized faster in children than in adults, requiring a higher dosage for similar efficacy to that achieved in adults. Olanzapine is a newer agent, used in doses between 0.1 and 0.14 mg/kg/day in children, with good anti-emetic efficacy, but has sedation and hyperglycemia as concerning adverse effects. Drug interactions between anti-emetics and between anti-emetics and chemotherapy/supportive agents (azole antifungals, cyclosporine, arsenic trioxide), especially QTc prolongation, should be considered during prescription.

Knowledge and attitude on childhood cancer survivorship among healthcare trainees: a multicentre study from India.

BACKGROUND: The proportion of childhood cancer survivors (CCS) in low/middle-income countries (LMICs) is rising. CCS often develop several physical and psycho-social long-term adverse effects, with unique healthcare needs. Primary healthcare providers (primary care physicians (PCPs)), especially in LMICs, are often not equipped to handle survivorship care. This study aimed to assess knowledge, and attitude among trainee healthcare providers concerning major issues of paediatric survivorship care. METHODS: A multi-centre, cross-sectional, questionnaire-based study was conducted among nursing and medical undergraduate students, and postgraduate medical residents across three tertiary-care teaching hospitals in India-All India Institute of Medical Sciences, New Delhi; Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry; and Maulana Azad Medical College, New Delhi. A questionnaire with total of 24 questions (14 knowledge-based and 10 attitude-based) was finalised after validation by expert review and piloting. The major domains covered in the questionnaire included knowledge and attitude regarding long-term adverse effects and psychosocial, employment-related issues faced by the survivors. It was administered to the study participants electronically. The knowledge-based questions had true/false responses (scored as 0 or 1 if incorrect or correct, respectively). Attitude-based questions were scored as 5-point Likert scale. RESULTS: Total 898 responses were collected (median age: 21 years, 64% (576/898) female). Among the respondents, 44% were undergraduate medical students, 42% were nursing students and 14% were postgraduate medical residents. The mean (SD) of knowledge score was 8.72 (2.04) (out of 14). On multivariable analysis, only discipline of training predicted knowledge scores regarding survivorship care. Postgraduate medical residents (9.08) as well as undergraduate medical students (8.85), had significantly higher mean knowledge scores than nursing students (8.47) (p=0.004).Two questions were answered incorrectly by the majority; children and siblings of CCS need additional genetic screening (79% incorrectly answered true), and CCS face intimacy issues in relation to normal sexual functioning (59% incorrectly answered false).Nearly half (48%) of respondents believed that their knowledge of cancer survivorship issues was inadequate. Majority of respondents (84%) suggested that oncologists should handle long-term survivorship care rather than PCPs. CONCLUSION: Trainee healthcare providers in India reported inadequate knowledge regarding survivorship care. Improving awareness by incorporating survivorship in teaching curriculum is imperative to equip future PCPs to provide survivorship care across the country.

Humoral and cellular immunity to SARS-CoV-2 following vaccination with non-mRNA vaccines in adolescent/young adults with cancer: A prospective cohort study.

BACKGROUND: Data on SARS-CoV-2 vaccine responsiveness in adolescent/young adult (AYA) cancer patients are sparse. The present study assessed humoral and cellular immune responses post-vaccination in this population. METHODS: In this prospective study, patients aged 12-30 years undergoing cancer therapy ("on therapy") and survivors ("off therapy") were recruited. Anti-receptor binding domain (RBD) protein IgG levels were measured at baseline, four weeks post-first vaccine dose (T1), and six weeks post-second dose (T2). Cellular immunity was assessed using activation-induced markers and intracellular cytokine staining in a patient subset. The primary outcome was to quantify humoral responses in both cohorts at T2 compared to baseline. Clinical predictors of log antibody titres at T2 were identified. RESULTS: Between April-December 2022, 118 patients were recruited of median age 15.4 years. Among them, 77 (65.2 %) were in the "on therapy" group, and 77 (65.2 %) had received the BBV152 vaccine. At baseline, 108 (91.5 %) patients were seropositive for anti-RBD antibody. The log anti-RBD titre rose from baseline to T2 (p-value = 0.001) in the whole cohort; this rise was significant from baseline-T1 (p-value < 0.001), but not from T1 to T2 (p-value = 0.842). A similar pattern was seen in the "on therapy" cohort. BECOV-2 vaccine was independently associated with higher log anti-RBD titres than BBV152 (regression coefficient: 0.41; 95 % CI: 0.10-0.73; p = 0.011). Cellular immune responses were similar in the "on-" and "off therapy" groups at the three time points. CONCLUSION: Among AYA cancer patients, a single non-mRNA vaccine dose confers robust hybrid humoral immunity with limited benefit from a second dose.

Sex Bias in Treatment Abandonment of Childhood Cancer in India.

OBJECTIVES: To explore the magnitude of sex bias and determinants of treatment abandonment (TA) in childhood cancer in India. METHODS: Individual data of children (0-19 y) registered between January 1, 2017 and July 31, 2022, was compiled. TA was defined as defaulting curative intent treatment ≥4 wk. Defaulting treatment irrespective of intent ≥4 wk was defined as Treatment Default (TD). The primary outcome was the proportion of male-to-female children with TA. Secondary outcomes included the proportion of male-to-female children with upfront TA, TA at relapse, TD, TD-p (TD only in the palliative setting). The impact of clinico-demographic factors on TA was analysed using multivariable regression and propensity score matching (PSM). RESULTS: Three thousand two hundred eighty four patients were analysed. The overall male-to-female ratio (MFR) was 2.08 (95% CI 1.94-2.24). Of 2906 patients treated with curative intent, 415 (14·3%) abandoned treatment. TA was higher in females than males (16·4% vs. 13·3%; p = 0·022) with adjusted MFR of 0·81 (0·66-0·98). The adjusted MFR of TA for treatment-naïve and relapsed patients and TD were 0·73 (0·59-0·91), 1·13 (0·65-1·96) and 0·84 (0·71-1·00) respectively. Sex independently predicted TA on multivariable analysis. However, on PSM analysis including socio-economic variables, lower maternal education predicted higher TA in children with cancer (10·1% vs. 6%, p = 0·015). CONCLUSIONS: Child sex predicted TA in childhood cancer in India with more females abandoning treatment. Maternal education is a more crucial factor predicting TA over child sex, when socio-economic factors were considered. Hence, policies promoting female education and gender equality may mitigate sex-based gaps in childhood cancer care.

Treatment outcomes in patients with Ewing sarcoma of the spine in a resource-challenged setting: 17-year experience from a single center in India.

Ewing sarcoma (ES) of the spine is a rare childhood cancer with sparse literature on treatment outcomes. We aimed to describe survival outcomes and prognostic factors in patients with spinal ES treated at a single institute in a resource-challenged setting. We conducted a retrospective analysis of patients with spinal ES registered at a tertiary care oncology center between 2003-2019. Clinical patient data was retrieved from hospital records. Cox regression analysis was used to identify the association of baseline clinical parameters with event free survival (EFS) and overall survival (OS). A cohort of 85 patients was analyzed including 38 (45%) patients with metastatic disease. The median age was 15 years with 73% being male. Local therapy was administered in 62 (72.9%) patients with surgery alone in 8 (9.4%), radiotherapy alone in 36 (42.4%) and both in 18 (21.2%) patients. A higher proportion of males received local therapy than females (80.3% versus 59.1%; p = 0.049). The median EFS and OS were 20.1 and 28.6 months, respectively. On univariable analysis, age ≤ 15 years, female sex, serum albumin ≤3.5 g/dL and hemoglobin ≤11 g/dL were associated with inferior EFS while younger age, female sex, hypoalbuminemia and metastatic disease were associated with inferior OS. On multivariable analysis, only hypoalbuminemia was predictive for inferior EFS (HR:2.41; p = 0.005) while hypoalbuminemia (HR:2.06;p = 0.033) and female sex (HR:1.83; p = 0.046) were associated with inferior OS. We concluded that hypoalbuminemia confers poor prognosis in ES spine. Survival outcomes are poorer in females treated in our setting, possibly due to prevailing sex-based biases.

Translation and Psychometric Evaluation of the Hindi Language Version of the Pediatric Nausea Assessment Tool (PeNAT) in the Indian Population.

OBJECTIVES: To translate the Pediatric Nausea Assessment Tool (PeNAT) into Hindi and validate it in Indian pediatric cancer patients and survivors. METHODS: The PeNAT-Hindi was finalized by forward and backward translations, and pilot testing. The PeNAT-Hindi was administered to 200 Hindi-speaking pediatric (4-18 y) cancer patients/survivors, in three groups. These included pediatric cancer patients who had recently received chemotherapy (n = 150); who received no chemotherapy within 5 d (n = 25) and survivors (n = 25). Construct validity was tested by comparing scores among the three groups. Test-retest reliability and criterion validity were estimated by the correlation of the first PeNAT score with the second (taken 1 h later) PeNAT score and the number of vomiting/retching episodes, respectively. Convergent validity and discriminant validity were estimated by correlating PeNAT scores with parent-assessed nausea severity, and pain, respectively. The responsiveness was tested by comparing second PeNAT scores with subsequent divergent PeNAT scores among patients reporting subjective change (improvement and worsening, respectively) in nausea severity. RESULTS: Test-retest reliability of PeNAT-Hindi was good (intraclass correlation = 0.791). The initial PeNAT score had moderate correlation with the number of vomiting/retching episodes (Spearman ρ = 0.401). Median PeNAT scores in group 1 versus groups 2 and 3 were significantly different (p < 0.001). Initial PeNAT scores showed a moderate correlation with parent-assessed nausea (Spearman ρ = 0.657) and a weak correlation with parent-assessed pain (Spearman ρ = 0.319). The responsiveness (standardized response mean) of PeNAT-Hindi to the change in nausea severity was -1.79 (improvement) and 2.19 (worsening), respectively. CONCLUSION: PeNAT-Hindi showed good reliability and acceptable validity. It may be used among Hindi-speaking children for measuring nausea. The responsiveness of PeNAT-Hindi needs further evaluation.

Olanzapine cost-effectiveness in vomiting and nausea from highly emetogenic chemotherapy in children and adolescents.

OBJECTIVES: To assess the cost-effectiveness of addition of olanzapine to a prophylactic antiemetic regimen containing aprepitant, dexamethasone and ondansetron among children receiving highly emetogenic chemotherapy (HEC) in India, Bangladesh, Indonesia, the UK and the USA. METHODS: Health states were estimated using individual patient-level outcome data from a randomised trial. The incremental cost-utility ratio (ICUR), incremental cost-effectiveness ratio and net monetary benefit (NMB) were calculated from the patient perspective for India, Bangladesh, Indonesia, the UK and the USA. One-way sensitivity analysis was done by varying the cost of olanzapine, cost of hospitalisation and utility values by ±25%. RESULTS: The olanzapine arm had an increment of 0.0018 quality-adjusted life-years (QALY) over the control arm. The mean total expenditure in the olanzapine arm was greater by US$0.51, US$0.43, US$6.73, US$11.05 and US$12.35 in India, Bangladesh, Indonesia, the UK and the USA, respectively. The ICUR($/QALY) was US$282.60 in India, US$241.42 in Bangladesh, US$3755.93 in Indonesia, US$6161.83 in the UK and US$6887.41 in the USA. The NMB was US$9.86, US$10.12, US$14.08, US$44.74 and US$98.79 for India, Bangladesh, Indonesia, the UK and the USA, respectively. The ICUR estimates of the base case and sensitivity analysis were below the willingness-to-pay threshold in all scenarios. CONCLUSION: The addition of olanzapine as a fourth agent for antiemetic prophylaxis is cost-effective despite an increase in overall expenditure. Olanzapine should be uniformly considered for children receiving HEC.

Philadelphia Chromosome Positive and Philadelphia-Like Acute Lymphoblastic Leukemia in Children and Adolescents: Current Management, Controversies and Emerging Concepts.

Philadelphia chromosome positive (Ph+) acute lymphoblastic lymphoma (ALL) is an uncommon subtype of ALL in children, seen in 2-5% cases. Diagnostic evaluation includes conventional karyotyping and detection of BCR-ABL1 translocation by fluorescence in-situ hybridization (FISH) or reverse transcriptase polymerase chain reaction (RT-PCR). For children, the frontline management includes combination of intensive chemotherapy along with imatinib (300-340 mg/m2/d) or dasatinib (60-80 mg/m2/d). Imatinib/dasatinib should be introduced in induction as soon as results for BCR-ABL are available. Minimal residual disease (MRD) monitoring is essential; multi-parametric flowcytometry and immunoglobulin/T-cell receptor rearrangement PCR are the preferred methods. Intrathecal therapy with at least 12 doses of methotrexate is adequate for central nervous system (CNS) prophylaxis, but cranial radiation is necessary for CNS3 involvement. Allogeneic hematopoietic stem cell transplantation (HSCT) in first remission may be considered in high-risk cases (persistent MRD positivity/induction failure). Maintenance therapy with tyrosine kinase inhibitors (TKI) in children is debatable, with potential concerns for long term adverse effects. At relapse, the choice of TKI is guided by the presence of BCR-ABL tyrosine kinase domain resistance mutations, although the frequency of resistance mutations in children are lower. Allogeneic HSCT is essential for consolidation in second remission, if not done. Ph-like ALL is a newly recognized molecular entity, with gene expression profile similar to Ph+ALL and poor survival outcomes. In resource-constrained settings, a stepwise cost-effective diagnostic evaluation should be considered among high-risk patients without recurrent genetic abnormalities. Current treatment strategies remain similar to Ph-negative ALL. Enrolment in clinical trials is encouraged for such children to evaluate potential targeted agents in this subtype.

Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.

PURPOSE: The proposed work aims to develop an algorithm to precisely segment the lung parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a combination of deep learning and traditional image processing algorithms. The initial step utilized a trained convolutional neural network (CNN) to generate preliminary lung masks, followed by the proposed post-processing algorithm for lung boundary correction. METHODS: First, the proposed method trained an improved 2D U-Net CNN model with Inception-ResNet-v2 as its backbone. The model was trained on 32 CT scans from two different sources: one from the VESSEL12 grand challenge and the other from AIIMS Delhi. Further, the model's performance was evaluated on a test dataset of 16 CT scans with juxta-pleural nodules obtained from AIIMS Delhi and the LUNA16 challenge. The model's performance was assessed using evaluation metrics such as average volumetric dice coefficient (DSCavg), average IoU score (IoUavg), and average F1 score (F1avg). Finally, the proposed post-processing algorithm was implemented to eliminate false positives from the model's prediction and to include juxta-pleural nodules in the final lung masks. RESULTS: The trained model reported a DSCavg of 0.9791 ± 0.008, IoUavg of 0.9624 ± 0.007, and F1avg of 0.9792 ± 0.004 on the test dataset. Applying the post-processing algorithm to the predicted lung masks obtained a DSCavg of 0.9713 ± 0.007, IoUavg of 0.9486 ± 0.007, and F1avg of 0.9701 ± 0.008. The post-processing algorithm successfully included juxta-pleural nodules in the final lung mask. CONCLUSIONS: Using a CNN model, the proposed method for lung parenchyma segmentation produced precise segmentation results. Furthermore, the post-processing algorithm addressed false positives and negatives in the model's predictions. Overall, the proposed approach demonstrated promising results for lung parenchyma segmentation. The method has the potential to be valuable in the advancement of computer-aided diagnosis (CAD) systems for automatic nodule detection.

A proposed methodology for detecting the malignant potential of pulmonary nodules in sarcoma using computed tomographic imaging and artificial intelligence-based models.

The presence of lung metastases in patients with primary malignancies is an important criterion for treatment management and prognostication. Computed tomography (CT) of the chest is the preferred method to detect lung metastasis. However, CT has limited efficacy in differentiating metastatic nodules from benign nodules (e.g., granulomas due to tuberculosis) especially at early stages (<5 mm). There is also a significant subjectivity associated in making this distinction, leading to frequent CT follow-ups and additional radiation exposure along with financial and emotional burden to the patients and family. Even 18F-fluoro-deoxyglucose positron emission technology-computed tomography (18F-FDG PET-CT) is not always confirmatory for this clinical problem. While pathological biopsy is the gold standard to demonstrate malignancy, invasive sampling of small lung nodules is often not clinically feasible. Currently, there is no non-invasive imaging technique that can reliably characterize lung metastases. The lung is one of the favored sites of metastasis in sarcomas. Hence, patients with sarcomas, especially from tuberculosis prevalent developing countries, can provide an ideal platform to develop a model to differentiate lung metastases from benign nodules. To overcome the lack of optimal specificity of CT scan in detecting pulmonary metastasis, a novel artificial intelligence (AI)-based protocol is proposed utilizing a combination of radiological and clinical biomarkers to identify lung nodules and characterize it as benign or metastasis. This protocol includes a retrospective cohort of nearly 2,000-2,250 sample nodules (from at least 450 patients) for training and testing and an ambispective cohort of nearly 500 nodules (from 100 patients; 50 patients each from the retrospective and prospective cohort) for validation. Ground-truth annotation of lung nodules will be performed using an in-house-built segmentation tool. Ground-truth labeling of lung nodules (metastatic/benign) will be performed based on histopathological results or baseline and/or follow-up radiological findings along with clinical outcome of the patient. Optimal methods for data handling and statistical analysis are included to develop a robust protocol for early detection and classification of pulmonary metastasis at baseline and at follow-up and identification of associated potential clinical and radiological markers.

Formulation and validation of a baseline prognostic score for osteosarcoma treated uniformly with a non-high dose methotrexate-based protocol from a low middle income healthcare setting: a single centre analysis of 594 patients.

Introduction: The outcomes of osteosarcoma in low middle income countries (LMICs) are different due to patients presenting in advanced stages, resource constraints and the use of non-high-dose-methotrexate (HDMTX)-based regimens. This study derived and validated a prognostic score for osteosarcoma that integrates biologic and social factors and is tailored for patients from an LMIC setting using a non-HDMTX-based protocol. Materials and methods: A retrospective study including osteosarcoma patients enrolled for treatment at a single tertiary care centre in India between 2003-19 was conducted. Baseline biologic and social characteristics were extracted from medical records and survival outcomes were noted. The cohort was randomised into a derivation and validation cohort. Multivariable Cox regression was used to identify baseline characteristics that were independently prognostic for survival outcomes in the derivation cohort. A score was derived from the prognostic factors identified in the derivation cohort and further validated in the validation cohort with estimation of its predictive ability. Results: 594 patients with osteosarcoma were eligible for inclusion in the study. Around one-third of the cohort had metastatic disease with 59% of the patients residing in rural areas. The presence of metastases at baseline (HR 3.39; p<0.001; score=3), elevated serum alkaline phosphatase (SAP) >450 IU/L (HR 1.57; p=0.001; score=1) and baseline tumour size > 10 cm (HR 1.68; p<0.001; score=1) were identified to be independent factors predicting inferior event free survival (EFS) and were included in development of the prognostic score. Patients were categorized as low risk (score 0), intermediate risk (score 1-3) and high risk (4-5). Harrell's c-indices for the score were 0.682, 0.608 and 0.657 respectively for EFS in the derivation, validation and whole cohort respectively. The timed AUC of ROC was 0.67 for predicting 18-month EFS in the derivation, validation and whole cohorts while that for 36-month EFS were 0.68, 0.66 and 0.68 respectively. Conclusions: The study describes the outcomes among osteosarcoma patients from an LMIC treated uniformly with a non-HDMTX-based protocol. Tumor size, baseline metastases and SAP were prognostic factors used to derive a score with good predictive value for survival outcomes. Social factors did not emerge as determinants of survival.

Mitochondrial gene expression signature predicts prognosis of pediatric acute myeloid leukemia patients.

Introduction: Gene expression profile of mitochondrial-related genes is not well deciphered in pediatric acute myeloid leukaemia (AML). We aimed to identify mitochondria-related differentially expressed genes (DEGs) in pediatric AML with their prognostic significance. Methods: Children with de novo AML were included prospectively between July 2016-December 2019. Transcriptomic profiling was done for a subset of samples, stratified by mtDNA copy number. Top mitochondria-related DEGs were identified and validated by real-time PCR. A prognostic gene signature risk score was formulated using DEGs independently predictive of overall survival (OS) in multivariable analysis. Predictive ability of the risk score was estimated along with external validation in The Tumor Genome Atlas (TCGA) AML dataset. Results: In 143 children with AML, twenty mitochondria-related DEGs were selected for validation, of which 16 were found to be significantly dysregulated. Upregulation of SDHC (p<0.001), CLIC1 (p=0.013) and downregulation of SLC25A29 (p<0.001) were independently predictive of inferior OS, and included for developing prognostic risk score. The risk score model was independently predictive of survival over and above ELN risk categorization (Harrell's c-index: 0.675). High-risk patients (risk score above median) had significantly inferior OS (p<0.001) and event free survival (p<0.001); they were associated with poor-risk cytogenetics (p=0.021), ELN intermediate/poor risk group (p=0.016), absence of RUNX1-RUNX1T1 (p=0.027), and not attaining remission (p=0.016). On external validation, the risk score also predicted OS (p=0.019) in TCGA dataset. Discussion: We identified and validated mitochondria-related DEGs with prognostic impact in pediatric AML and also developed a novel 3-gene based externally validated gene signature predictive of survival.

Addition of aprepitant improves acute emesis control in children and adolescents receiving induction chemotherapy for acute myeloid leukaemia: a randomised, open-label trial.

OBJECTIVES: More than 50% patients develop emesis during induction therapy for acute myeloid leukaemia (AML). The addition of aprepitant for emesis control in children receiving induction for AML have not been explored. METHODS: A single-institutional randomised, open-label trial (NCT02979548) was conducted where children between 5 and 18 years with the diagnosis of AML being planned for 3+7 induction regimen were included. All study participants received ondansetron (0.15 mg/kg) every 8 hours for 8 days starting 30 min prior to chemotherapy. Children belonging to aprepitant group additionally received aprepitant capsules (15-40 kg=days 1-3, 80 mg; >40 kg=day 1, 125 mg and days 2-3, 80 mg) starting from 1 hour prior to chemotherapy. The proportion of patients with complete response (CR) in chemotherapy induced vomiting (CIV) in acute phase (day 1-8), delayed phase (day 9-13), overall and initial 96 hours were recorded along with severity of vomiting and adverse effects. RESULTS: Total 78 children were randomised (Aprepitant group: 37 and control group: 41). The proportion of patients with CR in CIV was significantly higher in Aprepitant group in acute phase (p=0.007), overall phase (p=0.007) and in initial 96 hours (p<0.001) but it was not different in delayed phase (p=0.07). The first episode of vomiting was also significantly delayed in aprepitant group (p=0.02). Adverse effect profile was similar in two groups. CONCLUSION: Aprepitant significantly improves emesis control in children receiving induction therapy for AML, especially in acute phase and should be routinely incorporated as part of antiemetic prophylaxis. TRIAL REGISTRATION NUMBER: The study was registered at ClinicalTrials.gov (NCT02979548).