The current study set out to identify distress in cancer patients undergoing curative treatment w... more The current study set out to identify distress in cancer patients undergoing curative treatment within India. This study was carried out to measure distress and contributory factors in 103 cancer patients undergoing treatment with curative intent. The patients were interviewed using the Distress Inventory for Cancer (DI-C). The data on social, demographic, clinical, treatment, and follow-up details was collected from case records. The distress score for individual respondents ranged from 34 to 90 (mean 62.3). Patients with lower income, those who were single/widowed, or divorced, those living between 150 and 350 km (3-6 h commuting distance) from the cancer centre, presence of pain and patients with advanced tumours at presentation showed higher distress. A higher distress score correlated significantly with patients being lost to follow-up.
ABSTRACT Background and aims: The practice of orogastric tube insertion has become quite popular ... more ABSTRACT Background and aims: The practice of orogastric tube insertion has become quite popular in NICU's over the years. The present study was undertaken with an aim of assesing the pain associated with orogastric tube insertion across gestational age subgroups and the effect of oral sucrose on decreasing this pain.
... from Type-I1 Censored Samples M. Pandey U. S. Singh Banaras Hindu University, Varanasi Banara... more ... from Type-I1 Censored Samples M. Pandey U. S. Singh Banaras Hindu University, Varanasi Banaras Hindu University, Varanasi ... This shrunken estimator is compared with shrunken estimators given by Bain, Singh & Bhatkulikar, and Pandey. ...
... A Bayes Predictive Distribution Approach S. K. Upadhyay M. Pandey Banaras Hindu University, V... more ... A Bayes Predictive Distribution Approach S. K. Upadhyay M. Pandey Banaras Hindu University, Varanasi Banaras Hindu University, Varanasi ... prediction limits have also been considered by Lawless [8], Engelhardt & Bain [4, 51, Pandey & Upadhyay [12], etc. ...
European Journal of Surgical Oncology (EJSO), 1999
Survival analysis in clinical studies is important to assess the effectiveness of a given treatme... more Survival analysis in clinical studies is important to assess the effectiveness of a given treatment and to understand the effect of various disease characteristics. A number of methods exist to estimate the survival rate and its standard error. However, one cannot be certain that these methods have been handled appropriately. The widespread use of computers has made it possible to carry out survival analysis without expert guidance, but using inappropriate methods can give rise to erroneous conclusions. The majority of the biomedical journals now recommend that a statistical review of each manuscript should be carried out by an experienced bio-statistician, in addition to obtaining expert referees' comments on the article. The problem is compounded in papers from third-world countries where bio-statisticians may not be available in all institutions to guide clinicians as to the selection of proper techniques. The present paper deals with the various techniques of survival analysis and their interpretation, using a modal data set of malignant upper-aerodigestive tract melanoma patients treated in the Regional Cancer Centre, Trivandrum since 1982. The Kaplan-Meier method was found to be the most suitable for survival analysis. The median survival time is a better method of summarizing data than the mean. Rothman's method of estimation of the confidence limit is better than Peto's method as the confidence limit for survival probability tends to go beyond the range of 0-1.0 when calculated by Peto's method, especially when the sample size is small. The results from the present study suggest that survival analysis should be carried out by the Kaplan-Meier method. The median survival time should be provided wherever possible, rather than relying on mean survival. Confidence limits should be calculated as a measure of variability. A suitable rank test should be used to compare two or more survival curves, rather than a Z-test. Stratified analysis and Cox's model, when stratified analysis fails, can be used to define the impact of prognostic factors on survival.
The current study set out to identify distress in cancer patients undergoing curative treatment w... more The current study set out to identify distress in cancer patients undergoing curative treatment within India. This study was carried out to measure distress and contributory factors in 103 cancer patients undergoing treatment with curative intent. The patients were interviewed using the Distress Inventory for Cancer (DI-C). The data on social, demographic, clinical, treatment, and follow-up details was collected from case records. The distress score for individual respondents ranged from 34 to 90 (mean 62.3). Patients with lower income, those who were single/widowed, or divorced, those living between 150 and 350 km (3-6 h commuting distance) from the cancer centre, presence of pain and patients with advanced tumours at presentation showed higher distress. A higher distress score correlated significantly with patients being lost to follow-up.
ABSTRACT Background and aims: The practice of orogastric tube insertion has become quite popular ... more ABSTRACT Background and aims: The practice of orogastric tube insertion has become quite popular in NICU's over the years. The present study was undertaken with an aim of assesing the pain associated with orogastric tube insertion across gestational age subgroups and the effect of oral sucrose on decreasing this pain.
... from Type-I1 Censored Samples M. Pandey U. S. Singh Banaras Hindu University, Varanasi Banara... more ... from Type-I1 Censored Samples M. Pandey U. S. Singh Banaras Hindu University, Varanasi Banaras Hindu University, Varanasi ... This shrunken estimator is compared with shrunken estimators given by Bain, Singh & Bhatkulikar, and Pandey. ...
... A Bayes Predictive Distribution Approach S. K. Upadhyay M. Pandey Banaras Hindu University, V... more ... A Bayes Predictive Distribution Approach S. K. Upadhyay M. Pandey Banaras Hindu University, Varanasi Banaras Hindu University, Varanasi ... prediction limits have also been considered by Lawless [8], Engelhardt & Bain [4, 51, Pandey & Upadhyay [12], etc. ...
European Journal of Surgical Oncology (EJSO), 1999
Survival analysis in clinical studies is important to assess the effectiveness of a given treatme... more Survival analysis in clinical studies is important to assess the effectiveness of a given treatment and to understand the effect of various disease characteristics. A number of methods exist to estimate the survival rate and its standard error. However, one cannot be certain that these methods have been handled appropriately. The widespread use of computers has made it possible to carry out survival analysis without expert guidance, but using inappropriate methods can give rise to erroneous conclusions. The majority of the biomedical journals now recommend that a statistical review of each manuscript should be carried out by an experienced bio-statistician, in addition to obtaining expert referees' comments on the article. The problem is compounded in papers from third-world countries where bio-statisticians may not be available in all institutions to guide clinicians as to the selection of proper techniques. The present paper deals with the various techniques of survival analysis and their interpretation, using a modal data set of malignant upper-aerodigestive tract melanoma patients treated in the Regional Cancer Centre, Trivandrum since 1982. The Kaplan-Meier method was found to be the most suitable for survival analysis. The median survival time is a better method of summarizing data than the mean. Rothman's method of estimation of the confidence limit is better than Peto's method as the confidence limit for survival probability tends to go beyond the range of 0-1.0 when calculated by Peto's method, especially when the sample size is small. The results from the present study suggest that survival analysis should be carried out by the Kaplan-Meier method. The median survival time should be provided wherever possible, rather than relying on mean survival. Confidence limits should be calculated as a measure of variability. A suitable rank test should be used to compare two or more survival curves, rather than a Z-test. Stratified analysis and Cox's model, when stratified analysis fails, can be used to define the impact of prognostic factors on survival.
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Papers by M. Pandey