KP HARESH

Dr. KP HARESH


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 April 2017 in Child's Nervous System
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Journal Article
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SGSubhash Gupta
Subhash Gupta
SMSupriya Mallick
Supriya Mallick
RBRony Benson
Rony Benson
KHKP HARESH
KP HARESH
PJPramod Kumar Julka
Pramod Kumar Julka
GRGoura Kishor Rath
Goura Kishor Rath

28 April 2023 in Current Oncology
Verified
Journal Article
Open access
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VGVikas Garg
Vikas Garg
MRM D Ray
M D Ray
KHKP HARESH
KP HARESH
RSRanjit Kumar Sahoo
Ranjit Kumar Sahoo
ASAtul Sharma
Atul Sharma
ABAtul Batra
Atul Batra
Background: Carcinoma penis is a rare neoplasm, and the literature is scarce on long-term survival and its predictors. The aim of the study was to determine the clinical profile and management patterns, identify predictors of survival, and the impact of education and rural/urban dwelling on survival. Methods: Patients with a histological diagnosis of carcinoma penis from January 2015 to December 2019 were included in the study. Demographics, clinical profile, education status, primary residence address, and outcomes were obtained from the case records. Distance from the treatment centre was obtained from the postal code. The primary objectives were to assess relapse-free survival (RFS) and overall survival (OS). The secondary objectives were to identify the predictors of RFS and OS and to determine the clinical profile and treatment patterns in patients with carcinoma penis in India. Time-to-event was calculated by Kaplan–Meir analysis and survival was compared by the log-rank test. Univariate and multivariable Cox regression analyses were used to find independent predictors of relapse and mortality. Logistic regression analyses to examine the associations of rural residence, education status, and distance from the treatment centre with the relapse adjusting for measured confounding variables. Results: Case records of 102 patients treated during the above period were retrieved. The median age was 55.5 (interquartile range [IQR] 42–65 years). Ulcero-proliferative growth (65%), pain (57%), and dysuria (36%) were the most common presenting features. Clinical examination or imaging revealed inguinal lymphadenopathy in 70.6% of patients, however, only 42% of these lesions were pathologically involved. A total of 58.8% of patients were from rural areas, 46.9% had no formal education, and 50.9% had a primary residence ≥100 km from the hospital. Patients with lower education and rural households had higher TNM stages and nodal involvement. Median RFS and OS were 57.6 months (15.8 months to not reached) and 83.9 months (32.5 months to not reached), respectively. On univariate analysis tumor stage, involvement of lymph nodes, T stage, performance status, and albumin was predictive for relapse and survival. However, on multivariate analysis, the stage remained the only predictor of RFS and nodal involvement, and metastatic disease was a predictor of OS. Education status, rural habitation, and distance from the treatment centre were not predictors for relapse or survival. Conclusions: Patients with carcinoma have locally advanced disease at presentation. Rural dwellings and lower education were associated with the advanced stage but did not have a significant bearing on the survival outcomes. The stage at diagnosis and nodal involvement is the most important predictor of RFS and OS.

4 April 2022 in International Journal of Radiation Biology
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Journal Article
Closed access
ASAstha Srivastava
Astha Srivastava
KHKP HARESH
KP HARESH
ARAnjali V. Ramdulari
Anjali V. Ramdulari
HSHarsh Saxena
Harsh Saxena
RKRishabh Kumar
Rishabh Kumar
BJBabban Jee
Babban Jee
The prognosis of hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT) is dismal. Despite best treatment and care, the patients with this malignancy only showed 2.7–4 months of overall survival. It is debatable whether liver transplantation helps PVTT sufferers. The effectiveness of radiation therapy in treating HCC patients with PVTT should not be undervalued. By limiting the high dosage region to a small planning target volume, stereotactic radiation delivery has shifted toward hypofractionation, limiting the radiation exposure to healthy organs and tissues. Stereotactic body radiotherapy (SBRT) has a local control rate of 75–100%, depending on the treatment. The major limitation in SBRT for hepatocellular carcinoma with PVTT is the paucity of prospective evidence for longer periods beyond the first two years after treatment. More prospective studies/randomized clinical trials with a longer follow-up, larger sample size, and adequate statistical power are the dire need of the present situation to ascertain the curative effect of SBRT as primary therapy for advanced HCC with PVTT. SBRT can improve survival, particularly for patients receiving multidisciplinary treatment. This review sums up our most current understanding of how radiation therapy, notably SBRT, can be used to treat hepatocellular carcinoma when combined with PVTT. Recent research has led us to believe that irradiation in the form of SBRT may cure hepatocellular carcinoma complicated by PVTT.

26 August 2024 in Current Oncology
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Journal Article
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CMChetanya Mittal
Chetanya Mittal
HGHardik Gupta
Hardik Gupta
CNChitrakshi Nagpal
Chitrakshi Nagpal
RSRanjit K. Sahoo
Ranjit K. Sahoo
ASAparna Sharma
Aparna Sharma
ABAtul Batra
Atul Batra
Introduction: Prostate cancer is one of the most prevalent malignancies affecting men globally, with a significant impact on health-related quality of life (HRQOL). With the recent therapeutic advancements and improvements in survival, there is a need to understand the determinants of HRQOL in metastatic prostate cancer patients to optimize treatment strategies for quality of life as the number of survivors increases. The aim of this study was to identify clinical variables that affect HRQOL and its domains in patients with metastatic prostate cancer. Methods: We conducted a cross-sectional questionnaire-based study in patients diagnosed with metastatic prostate cancer at a tertiary cancer center in India. Baseline clinical features, treatment details, and completed Functional Assessment of Cancer Therapy—Prostate (FACT-P), composed of FACT-general (FACT-G) and prostate cancer-specific concerns subscale (PCS) and FACT-P Trial Outcome Index (FACT-P TOI) questionnaires, were collected. The mean total, as well as individual domain scores, were calculated. Additionally, these were stratified by the current treatment being received by patients. Linear regression was used to identify independent factors affecting HRQOL in these patients. Results: Of the 106 enrolled patients, 84 completed the FACT-P questionnaire and were included in the analysis. The median age was 66 years, and at the time of assessment, 3 patients (3.6%) were receiving androgen deprivation therapy only, 53 patients (63.1%) were on ADT + androgen receptor-targeted agents (ARTAs), and 18 patients (21.4%) patients received ADT + chemotherapy. The mean (±standard deviation) of the FACT-P TOI score was 70.33 (±15.16); the PCS subscale was the most affected, followed by functional well-being. Patients on chemotherapy scored significantly higher on PCS, but the composite scores were not significantly different. Univariable regression identified obesity (body mass index > 25 kg/m2) and duration of first-line treatment as significant predictors of better HRQOL; however, obesity was the only independent predictor in multivariable analysis (β = 8.2; 95% confidence interval, 1.2 to 15.0; p = 0.022). Obesity also independently predicted a better FACT-P and its physical well-being domain score and PCS. Conclusion: Prostate cancer patients experience impaired QoL, especially in the prostate cancer-specific and functional well-being domains. Lower BMI is an independent predictor of poor QoL, and this requires efforts to assess the impact of strategies to manage the nutritional status of patients with metastatic disease on QoL outcomes.

21 January 2025 in Indian Journal of Surgery
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Journal Article
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SISharmin Islam
Sharmin Islam
AGAjay Gogia
Ajay Gogia
KHKP HARESH
KP HARESH
IJIsmail Jatoi
Ismail Jatoi
CHChintamani
Chintamani
ASAnurag Srivastava
Anurag Srivastava

11 April 2025 in medRxiv
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Preprint
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JCJagrati Chaudhary
Jagrati Chaudhary
APAnil Kumar Pandey
Anil Kumar Pandey
PSParam Dev Sharma
Param Dev Sharma
SKSanjay Kumar
Sanjay Kumar
KHKP HARESH
KP HARESH
RKRakesh Kumar
Rakesh Kumar
Introduction Gallium-68 Prostate specific membrane antigen (Ga-68 PSMA) PET/CT has significantly improved prostate cancer imaging by offering superior sensitivity and specificity over conventional modalities. However, the effectiveness of this diagnostic tool depends on the quality and consistency of reporting. This study evaluates the adequacy, consistency, and AI compatibility of semi-structured Ga-68 PSMA PET/CT reports. Methods Essential reporting elements were determined through consensus among nuclear medicine physicians, urologists, and radiotherapists. Two hundred Ga-68 PSMA PET/CT reports from prostate cancer patients (January 2020–June 2024) were analysed. Reporting Adequacy Score (RAS) assessed the percentage of clinical needs met, while Variability Index (VI) quantified inconsistencies in terminology. Statistical analyses, including descriptive statistics, frequency distribution, and boxplots, were performed to evaluate reporting trends. Results RAS ranged from 31% to 78%, with 91% of reports being partially adequate (50– 80% RAS) and 9% inadequate (<50% RAS). Key clinical details, such as Lesion Maximum Standardized Uptake Value (SUVmax), Neurovascular bundle involvement, and Bone metastasis lesion count, were frequently missing. Inconsistent terminology was observed in lesion descriptions, lymph node involvement, and uptake patterns, with VI ranging from minimal (4%) to high (67%). Reports with lower RAS and high VI were less suitable for AI- based data extraction, posing challenges to automation. Conclusion The majority of Ga-68 PSMA PET/CT reports were partially adequate, with significant missing details and considerable variability in terminology. The variability was evenly distributed across minimal, moderate, and high levels. Training an AI model on such reports would likely result in slower learning and compromised performance.