State of cancer care in India and opportunities for innovation.

Cancer is one of the leading causes of morbidity and mortality in India. Despite recent medical and technological advances, the cancer burden in India remains high and continues to rise. Moreover, substantial regional disparities in cancer incidence and access to essential medical resources exist throughout the country. While innovative and effective cancer therapies hold promise for improving patient outcomes, several barriers hinder their development and utilization in India. Here we provide an overview of these barriers, including challenges related to patient awareness, inadequate infrastructure, scarcity of trained oncology professionals, and the high cost of cancer care. Furthermore, we discuss the limited availability of cancer clinical trials in the country, along with an examination of potential avenues to enhance cancer care in India. By confronting these hurdles head-on and implementing innovative, pragmatic solutions, we take an indispensable step toward a future where every cancer patient in the country can access quality care.

Cancer is a major cause of illness and death in India. Despite advances in medicine and technology, the number of people with cancer remains high and continues to increase. There are big differences in access to necessary medical resources across different regions of the country. This article focuses on the barriers that hinder the development and use of effective cancer treatments in India. We discuss challenges related to patient awareness, inadequate medical facilities, a shortage of trained cancer specialists and the high cost of cancer treatment. Additionally, we explore the limited availability of cancer clinical trials in India and potential ways to improve cancer care in the country. By finding innovative and practical solutions to these challenges, we can take a crucial step toward a future where all cancer patients in India have access to high-quality care.

AI-Assisted Screening of Oral Potentially Malignant Disorders Using Smartphone-Based Photographic Images.

The prevalence of oral potentially malignant disorders (OPMDs) and oral cancer is surging in low- and middle-income countries. A lack of resources for population screening in remote locations delays the detection of these lesions in the early stages and contributes to higher mortality and a poor quality of life. Digital imaging and artificial intelligence (AI) are promising tools for cancer screening. This study aimed to evaluate the utility of AI-based techniques for detecting OPMDs in the Indian population using photographic images of oral cavities captured using a smartphone. A dataset comprising 1120 suspicious and 1058 non-suspicious oral cavity photographic images taken by trained front-line healthcare workers (FHWs) was used for evaluating the performance of different deep learning models based on convolution (DenseNets) and Transformer (Swin) architectures. The best-performing model was also tested on an additional independent test set comprising 440 photographic images taken by untrained FHWs (set I). DenseNet201 and Swin Transformer (base) models show high classification performance with an F1-score of 0.84 (CI 0.79-0.89) and 0.83 (CI 0.78-0.88) on the internal test set, respectively. However, the performance of models decreases on test set I, which has considerable variation in the image quality, with the best F1-score of 0.73 (CI 0.67-0.78) obtained using DenseNet201. The proposed AI model has the potential to identify suspicious and non-suspicious oral lesions using photographic images. This simplified image-based AI solution can assist in screening, early detection, and prompt referral for OPMDs.

Multi-Institutional Trends in Gynecological Robotic Surgery in India: A Real-World Scenario.

Background Robot-assisted laparoscopic surgery in gynecology has grown exponentially compared to laparoscopic surgery. The probable reasons for the increased uptake of robotics are a shorter learning curve, three-dimensional vision, and increased dexterity compared to laparoscopic surgery, and precise surgery as compared to open surgery. This study compares the time trends of various parameters in robotic gynecological surgery in India over a decade. Material and methods In India, a retrospective analysis of all robot-assisted laparoscopic surgery for gynecologic diseases in five tertiary care hospitals was conducted between July 2011 and June 2021. Data were collected regarding demographic profiles, clinical and disease characteristics, and indications for surgery. Details related to surgery were collected, such as the number of ports, console and docking time, the procedure performed, total operative time, average blood loss, blood transfusion, and length of hospital stay. All the parameters collected were grouped into five years, and a comparison was made between the first five years (2011-2015) and the second five years (2016-2021). Statistical analysis, including descriptive statistics and trend analysis, was performed. Results During the 10 years, the total number of cases included was 1,501, out of which 764 were benign cases and 737 were pre-malignant/malignant cases. The common indications were uterine leiomyoma (31.2%) and carcinoma endometrium (28%). The mean age for benign cases was significantly lower than that for malignant cases (40.84 years and 55.42 years, respectively). Mean blood loss was significantly lower for benign indications (97.48 mL) than for oncological surgery (184.67 mL) and needed fewer transfusions. The mean length of stay (LOS) for benign (2.07 days) and malignant/ pre-malignant cases (2.32 days) and the mean BMI for benign (28.40) and for oncological patients (28.47) were similar in both groups. The docking time reduced significantly in the last five years. Conclusion The current retrospective study demonstrates an increasing uptake of robotic technology in gynecological surgery in India. Of the total cohort of cases, 70.9% of patients underwent gynecological robotic surgery in the last five years. A burst of adaptability happened for malignant cases in 2017 and benign cases in 2018, probably due to the increased availability of robotic platforms and improved awareness of technology and training among medical professionals. The number of cases has grown exponentially over the last five years in both benign and malignant/ pre-malignant scenarios; however, there has been a downward trend in the robotic surgery performed in the previous couple of years due to the uncertainty of the COVID pandemic.

Incidental Findings in CT Scans on Screening for COVID-19.

Incidentalomas on computed tomography (CT) scans are incidental or unsuspected findings that are detected when obtaining a CT examination for an unrelated reason. Incidentalomas on CT scans are common. This study was conducted to examine the rates of incidental findings on CT chest in patients who were screened for COVID-19. Three thousand one hundred ninety-one CT scans were assessed for incidental findings. These CT scans were taken from an urban diagnostics laboratory in Hyderabad (IN) over a period of 2 months (April to May 2021) when the COVID-19 s wave peaked. Data from these reports were tabulated with demographic information and findings. Out of 3191 scans, 277 (8.68%) showed incidental findings, the most common of which was lung nodules and other individual findings. There were 6 total malignancies detected and a further 92 cases that required follow-up. CT scans are important for the detection of incidental findings. Care should be taken to follow up on patients with incidental findings that are undetermined to catch a lesion in the early stage.

Analysis of solid tumor mutation profiles in liquid biopsy.

Liquid biopsy is increasingly gaining traction as an alternative to invasive solid tumor biopsies for prognosis, treatment decisions, and disease monitoring. Matched tumor-plasma samples were collected from 180 patients across different cancers with >90% of the samples below Stage IIIB. Tumors were profiled using next-generation sequencing (NGS) or quantitative PCR (qPCR), and the mutation status was queried in the matched plasma using digital platforms such as droplet digital PCR (ddCPR) or NGS for concordance. Tumor-plasma concordance of 82% and 32% was observed in advanced (Stage IIB and above) and early (Stage I to Stage IIA) stage samples, respectively. Interestingly, the overall survival outcomes correlated to presurgical/at-biopsy ctDNA levels. Baseline ctDNA stratified patients into three categories: (a) high ctDNA correlated with poor survival outcome, (b) undetectable ctDNA with good outcome, and (c) low ctDNA whose outcome was ambiguous. ctDNA could be a powerful tool for therapy decisions and patient management in a large number of cancers across a variety of stages.