{"title":"Observational studies: practical tips for avoiding common statistical pitfalls","authors":"Anna Freni Sterrantino","doi":"10.1016/j.lansea.2024.100415","DOIUrl":"https://doi.org/10.1016/j.lansea.2024.100415","url":null,"abstract":"<div><p>This Personal View is intended for early-career researchers who are not yet experts in statistics. The Personal View focuses on common but usually avoidable flaws in the context of observational studies. I point out how study design, data collection, and statistical methods impact statistical results and research conclusions. With particular attention to study planning, sample selection, biases, lack of transparency and results misinterpretations.</p></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368224000659/pdfft?md5=6559a3da2b3e56f434cc29711a421238&pid=1-s2.0-S2772368224000659-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140894271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tuck Seng Cheng , Farzana Zahir , Solomi V. Carolin , Ashok Verma , Sereesha Rao , Saswati Sanyal Choudhury , Gitanjali Deka , Pranabika Mahanta , Swapna Kakoty , Robin Medhi , Shakuntala Chhabra , Anjali Rani , Amrit Bora , Indrani Roy , Bina Minz , Omesh Kumar Bharti , Rupanjali Deka , Charles Opondo , David Churchill , Marian Knight , Manisha Nair
{"title":"Risk factors for labour induction and augmentation: a multicentre prospective cohort study in India","authors":"Tuck Seng Cheng , Farzana Zahir , Solomi V. Carolin , Ashok Verma , Sereesha Rao , Saswati Sanyal Choudhury , Gitanjali Deka , Pranabika Mahanta , Swapna Kakoty , Robin Medhi , Shakuntala Chhabra , Anjali Rani , Amrit Bora , Indrani Roy , Bina Minz , Omesh Kumar Bharti , Rupanjali Deka , Charles Opondo , David Churchill , Marian Knight , Manisha Nair","doi":"10.1016/j.lansea.2024.100417","DOIUrl":"https://doi.org/10.1016/j.lansea.2024.100417","url":null,"abstract":"<div><h3>Background</h3><p>Guidelines for labour induction/augmentation involve evaluating maternal and fetal complications, and allowing informed decisions from pregnant women. This study aimed to comprehensively explore clinical and non-clinical factors influencing labour induction and augmentation in an Indian population.</p></div><div><h3>Methods</h3><p>A prospective cohort study included 9305 pregnant women from 13 hospitals across India. Self-reported maternal socio-demographic and lifestyle factors, and maternal medical and obstetric histories from medical records were obtained at recruitment (≥28 weeks of gestation), and women were followed up within 48 h after childbirth. Maternal and fetal clinical information were classified based on guidelines into four groups of clinical factors: (i) ≥2 indications, (ii) one indication, (iii) no indication and (iv) contraindication. Associations of clinical and non-clinical factors (socio-demographic, healthcare utilisation and lifestyle related) with labour induction and augmentation were investigated using multivariable logistic regression analyses.</p></div><div><h3>Findings</h3><p>Over two-fifths (n = 3936, 42.3%, 95% confidence interval [CI] 41.3–43.3%) of the study population experienced labour induction and more than a quarter (n = 2537, 27.3%, 95% CI 26.4–28.2%) experienced augmentation. Compared with women with ≥2 indications, those with one (adjusted odds ratio [aOR] 0.50, 95% CI 0.42–0.58) or no indication (aOR 0.24, 95% CI 0.20–0.28) or with contraindications (aOR 0.12, 95% CI 0.07–0.20) were less likely to be induced, adjusting for non-clinical characteristics. These associations were similar for labour augmentation. Notably, 34% of women who were induced or augmented did not have any clinical indication. Several maternal demographic (age at labour, parity and body mass index in early pregnancy), healthcare utilization (number of antenatal check-ups, duration of iron-folic acid supplementation and individuals managing childbirth) and socio-economic factors (religion, living below poverty line, maternal education and partner’s occupation) were independently associated with labour induction and augmentation.</p></div><div><h3>Interpretation</h3><p>Although decisions about induction and augmentation of labour in our study population in India were largely guided by clinical recommendations, we cannot ignore that more than a third of the women did not have an indication. Decisions could also be influenced by non-clinical factors which need further research.</p></div><div><h3>Funding</h3><p>The MaatHRI platform is funded by a <span>Medical Research Council Career Development Award</span> (Grant Ref: <span>MR/P022030/1</span>) and a <span>Transition Support Award</span> (Grant Ref: <span>MR/W029294/1</span>).</p></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368224000672/pdfft?md5=4859f1d317421cfb41f20454d959b124&pid=1-s2.0-S2772368224000672-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140879834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sok King Ong , Sarah K. Abe , Gillian Li Gek Phua , Harindra Jayasekara , Kayo Togawa , Laureline Gatellier , Jeongseon Kim , Yawei Zhang , Siti Zuhrini Kahan , Siti Norbayah Yusof , Jong Soo Han , C.S. Pramesh , Manju Sengar , Abhishek Shankar , Clarito Cairo , Suleeporn Sangrajran , Erdenekhuu Nansalmaa , Tseveen Badamsuren , Tashi Dendup , Kinley Tshering , Tomohiro Matsuda
{"title":"Mapping recommendations towards an Asian Code Against Cancer (ACAC) as part of the World Code Against Cancer Framework: an Asian National Cancer Centers Alliance (ANCCA) initiative","authors":"Sok King Ong , Sarah K. Abe , Gillian Li Gek Phua , Harindra Jayasekara , Kayo Togawa , Laureline Gatellier , Jeongseon Kim , Yawei Zhang , Siti Zuhrini Kahan , Siti Norbayah Yusof , Jong Soo Han , C.S. Pramesh , Manju Sengar , Abhishek Shankar , Clarito Cairo , Suleeporn Sangrajran , Erdenekhuu Nansalmaa , Tseveen Badamsuren , Tashi Dendup , Kinley Tshering , Tomohiro Matsuda","doi":"10.1016/j.lansea.2023.100316","DOIUrl":"10.1016/j.lansea.2023.100316","url":null,"abstract":"<div><p>This paper outlines the process undertaken by Asian National Cancer Centers Alliance (ANCCA) members in working towards an Asian Code Against Cancer (ACAC). The process involves: (i) identification of the criteria for selecting the existing set of national recommendations for ACAC (ii) compilation of existing national codes or recommendations on cancer prevention (iii) reviewing the scientific evidence on cancer risk factors in Asia and (iv) establishment of one or more ACAC under the World Code Against Cancer Framework. A matrix of national codes or key recommendations against cancer in ANCCA member countries is presented. These include taking actions to prevent or control tobacco consumption, obesity, unhealthy diet, physical inactivity, alcohol consumption, exposure to occupational and environmental toxins; and to promote breastfeeding, vaccination against infectious agents and cancer screening. ANCCA will continue to serve as a supportive platform for collaboration, development, and advocacy of an ACAC jointly with the International Agency for Research on Cancer/World Health Organization (IARC/WHO).</p></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368223001762/pdfft?md5=6d317d5563e37db062567d5270a06f4e&pid=1-s2.0-S2772368223001762-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139300539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Deep-learning enabled ultrasound based detection of gallbladder cancer in northern India: a prospective diagnostic study","authors":"Pankaj Gupta , Soumen Basu , Pratyaksha Rana , Usha Dutta , Raghuraman Soundararajan , Daneshwari Kalage , Manika Chhabra , Shravya Singh , Thakur Deen Yadav , Vikas Gupta , Lileswar Kaman , Chandan Krushna Das , Parikshaa Gupta , Uma Nahar Saikia , Radhika Srinivasan , Manavjit Singh Sandhu , Chetan Arora","doi":"10.1016/j.lansea.2023.100279","DOIUrl":"10.1016/j.lansea.2023.100279","url":null,"abstract":"<div><h3>Background</h3><p>Gallbladder cancer (GBC) is highly aggressive. Diagnosis of GBC is challenging as benign gallbladder lesions can have similar imaging features. We aim to develop and validate a deep learning (DL) model for the automatic detection of GBC at abdominal ultrasound (US) and compare its diagnostic performance with that of radiologists.</p></div><div><h3>Methods</h3><p>In this prospective study, a multiscale, second-order pooling-based DL classifier model was trained (training and validation cohorts) using the US data of patients with gallbladder lesions acquired between August 2019 and June 2021 at the Postgraduate Institute of Medical Education and research, a tertiary care hospital in North India. The performance of the DL model to detect GBC was evaluated in a temporally independent test cohort (July 2021–September 2022) and was compared with that of two radiologists.</p></div><div><h3>Findings</h3><p>The study included 233 patients in the training set (mean age, 48 ± (2SD) 23 years; 142 women), 59 patients in the validation set (mean age, 51.4 ± 19.2 years; 38 women), and 273 patients in the test set (mean age, 50.4 ± 22.1 years; 177 women). In the test set, the DL model had sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of 92.3% (95% CI, 88.1–95.6), 74.4% (95% CI, 65.3–79.9), and 0.887 (95% CI, 0.844–0.930), respectively for detecting GBC which was comparable to both the radiologists. The DL-based approach showed high sensitivity (89.8–93%) and AUC (0.810–0.890) for detecting GBC in the presence of stones, contracted gallbladders, lesion size <10 mm, and neck lesions, which was comparable to both the radiologists (p = 0.052–0.738 for sensitivity and p = 0.061–0.745 for AUC). The sensitivity for DL-based detection of mural thickening type of GBC was significantly greater than one of the radiologists (87.8% vs. 72.8%, p = 0.012), despite a reduced specificity.</p></div><div><h3>Interpretation</h3><p>The DL-based approach demonstrated diagnostic performance comparable to experienced radiologists in detecting GBC using US. However, multicentre studies are warranted to explore the potential of DL-based diagnosis of GBC fully.</p></div><div><h3>Funding</h3><p>None.</p></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368223001397/pdfft?md5=ec711d990a668397721c2ca0e9a08ce0&pid=1-s2.0-S2772368223001397-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135249078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Survival of patients with cervical cancer in India – findings from 11 population based cancer registries under National Cancer Registry Programme","authors":"Krishnan Sathishkumar , Jayasankar Sankarapillai , Aleyamma Mathew , Rekha A. Nair , Nitin Gangane , Sushma Khuraijam , Debabrata Barmon , Shashank Pandya , Gautam Majumdar , Vinay Deshmane , Eric Zomawia , Tseten Wangyal Bhutia , Kaling Jerang , Preethi Sara George , Swapna Maliye , Rajesh Laishram , Anand Shah , Shiromani Debbarma , Shravani Koyande , Lalawmpuii Pachuau , Prashant Mathur","doi":"10.1016/j.lansea.2023.100296","DOIUrl":"10.1016/j.lansea.2023.100296","url":null,"abstract":"<div><h3>Background</h3><p>Cancer survival data from Population Based Cancer Registries (PBCR) reflect the average outcome of patients in the population, which is critical for cancer control efforts. Despite decreasing incidence rates, cervical cancer is the second most common female cancer in India, accounting for 10% of all female cancers. The objective of the study is to estimate the five-year survival of patients with cervical cancer diagnosed between 2012 and 2015 from the PBCRs in India.</p></div><div><h3>Methods</h3><p>A single primary incidence of cervical cancer cases of 11 PBCRs (2012–2015) was followed till June 30, 2021 (n = 5591). Active follow-ups were conducted through hospital visits, telephone calls, home or field visits, and public databases. Five-year Observed Survival (OS) and Age Standardised Relative Survival (ASRS) was calculated. OS was measured by age and clinical extent of disease for cervical cancers.</p></div><div><h3>Findings</h3><p>The five-year ASRS (95% CI) of cervical cancer was 51.7% (50.2%–53.3%). Ahmedabad urban (61.5%; 57.4%–65.4%) had a higher survival followed by Thiruvananthapuram (58.8%; 53.1%–64.3%) and Kollam (56.1%; 50.7%–61.3%). Tripura had the lowest overall survival rate (31.6%; 27.2%–36.1%). The five-year OS% for pooled PBCRs was 65.9%, 53.5%, and 18.0% for localised, regional, and distant metastasis, respectively.</p></div><div><h3>Interpretation</h3><p>We observed a wide variation in cervical cancer survival within India. The findings of this study would help the policymakers to identify and address inequities in the health system. We re-emphasise the importance of awareness, early detection, and increase the improvement of the health care system.</p></div><div><h3>Funding</h3><p>The National Cancer Registry Programme is funded through intra-mural funding by <span>Indian Council of Medical Research</span>, <span>Department of Health Research, India</span>, <span>Ministry of Health & Family Welfare</span>.</p></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368223001567/pdfft?md5=fd18389e3b382b70e8b70188e58646b0&pid=1-s2.0-S2772368223001567-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135707010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The cost of cancer care in India requires careful reporting and interpretation","authors":"Parth Sharma , Santam Chakraborty","doi":"10.1016/j.lansea.2024.100380","DOIUrl":"10.1016/j.lansea.2024.100380","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368224000295/pdfft?md5=d92edc96539ceb846183315486daa62a&pid=1-s2.0-S2772368224000295-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140089638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Treatment pattern and outcomes of leptomeningeal carcinomatosis in India – a retrospective study","authors":"Gautam Goyal , Ashish Singh , Manuprasad Avaronnan , Nirmal Vivek Raut , Vikas Talreja , Arun Chandrasekharan , Kushal Gupta , Bharat Bhosale , Rushabh Kiran Kothari , Deevyashali Parekh , Bhavesh Pradip Poladia , Joydeep Ghosh , Avinash Talele , Sameer Shrirangwar , Akshay Karpe","doi":"10.1016/j.lansea.2023.100331","DOIUrl":"10.1016/j.lansea.2023.100331","url":null,"abstract":"<div><h3>Background</h3><p>Leptomeningeal carcinomatosis (LMC), the metastatic spread of cancer to the leptomeninges, is a rare complication and has a dismal prognosis. Due to limited data available on LMC from India, we conducted a country-wise audit of LMC across 15 centres in India.</p></div><div><h3>Methods</h3><p>The current study conducted in 2020, was a retrospective, multicentric audit of adult patients (aged ≥18 years) with diagnosis of LMC and who received treatment during 2010–2020. Baseline characteristics, details related to previous treatments, cancer sites, LMC diagnosis, treatment pattern and overall survival (OS) were collected. Descriptive statistics were performed, and Kaplan Meier analysis was performed for the estimation of OS.</p></div><div><h3>Findings</h3><p>Among the patients diagnosed with LMC (n = 84), diagnosis was confirmed in 52 patients (61.9%) and ‘probable’ in 32 (38.1%) patients. The three most common cause of malignancy were non-small cell lung cancer (NSCLC), breast cancer and gastrointestinal cancer with 45 (53.6%), 22 (26.1%) and 9 (10.7%) patients respectively. Intrathecal therapy was offered in 33 patients (39.3%). The most common intrathecal agent was methotrexate in 23 patients (27.4%). The median OS was 90 days (95% CI 48–128). Among tested variables, intrathecal therapy administration (hazard ratio [HR] = 0.36, 95% CI 0.19–0.68) and primary in lung (HR = 0.43, 95% CI 0.23–0.83) had a favourable impact on OS.</p></div><div><h3>Interpretation</h3><p>Prognosis with leptomeningeal carcinomatosis is poor with a significant burden of morbidity and mortality in India. This data aims to highlight the current outcomes and facilitate further research on LMC.</p></div><div><h3>Funding</h3><p>None.</p></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368223001919/pdfft?md5=bbfe1d14d490b93925c8ebdccffb6608&pid=1-s2.0-S2772368223001919-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139291613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrigendum to “Ending violence against healthcare workers in India: a bill for a billion” [The Lancet Regional Health Southeast Asia 6 (2022) 100064]","authors":"Aatmika Nair , Siddhesh Zadey","doi":"10.1016/j.lansea.2024.100382","DOIUrl":"10.1016/j.lansea.2024.100382","url":null,"abstract":"","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772368224000325/pdfft?md5=b5e0495891fca4d61467c52cfa8622d0&pid=1-s2.0-S2772368224000325-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140088999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}