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Cost of treatment for head and neck cancer in India.

ABSTRACT: There are no published data on the cost of cancer treatment for guiding reimbursement decisions in India. The present study was designed to estimate the cost of treating head and neck cancer (HNC) with the aim of determining package rates. The present study was undertaken in the Departments of Radiotherapy and Otolaryngology of a large tertiary care hospital in North India. Economic health system costs incurred were assessed using a bottom-up methodology. Data on all resources-capital or recurrent, incurred on the delivery of HNC treatment were collected from April 2014 to March 2015. Following the cost-of-illness approach, patients were interviewed to elicit out-of-pocket (OOP) expenditure. A total of INR 40,993,017 (USD 0.67 million) was spent on radiotherapy care for treating HNC during 1 year. Salaries constituted the major component (42.6%) of this cost, followed by equipment/furniture (29%), space rent (20.7%), overheads and consumables (7.7%). In addition, INR 47,191 (USD 773) per HNC patient was spent on the surgery. Furthermore, patients spent an average amount ranging from INR 12,575 (USD 206) to INR 65,257 (USD 1069) on the different treatment therapies. In terms of package rates, cobalt radiotherapy alone was the cheapest (INR 38,714, USD 634), while intensity modulated radiotherapy (IMRT) was most expensive (INR 192,914, USD 3161). The estimates from the present study could be used for developing package rates under various publicly financed health insurance schemes as well as for the planning for creation of new cancer centres.

SUBMITTER: Chauhan AS

PROVIDER: S-EPMC5764364 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Cost of treatment for head and neck cancer in India.

Chauhan Akashdeep Singh AS Prinja Shankar S Ghoshal Sushmita S Verma Roshan R Oinam Arun S AS

PloS one 20180111 1

There are no published data on the cost of cancer treatment for guiding reimbursement decisions in India. The present study was designed to estimate the cost of treating head and neck cancer (HNC) with the aim of determining package rates. The present study was undertaken in the Departments of Radiotherapy and Otolaryngology of a large tertiary care hospital in North India. Economic health system costs incurred were assessed using a bottom-up methodology. Data on all resources-capital or recurre ...[more]

PMID: 29324861

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Project description:ImportancePostoperative chemoradiation is the standard of care for cancers with positive margins or extracapsular extension, but the benefit of chemotherapy is unclear for patients with other intermediate risk features.ObjectiveTo evaluate whether machine learning models could identify patients with intermediate-risk head and neck squamous cell carcinoma who would benefit from chemoradiation.Design, setting, and participantsThis cohort study included patients diagnosed with squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx, or larynx from January 1, 2004, through December 31, 2016. Patients had resected disease and underwent adjuvant radiotherapy. Analysis was performed from October 1, 2019, through September 1, 2020. Patients were selected from the National Cancer Database, a hospital-based registry that captures data from more than 70% of newly diagnosed cancers in the United States. Three machine learning survival models were trained using 80% of the cohort, with the remaining 20% used to assess model performance.ExposuresReceipt of adjuvant chemoradiation or radiation alone.Main outcomes and measuresPatients who received treatment recommended by machine learning models were compared with those who did not. Overall survival for treatment according to model recommendations was the primary outcome. Secondary outcomes included frequency of recommendation for chemotherapy and chemotherapy benefit in patients recommended for chemoradiation vs radiation alone.ResultsA total of 33 527 patients (24 189 [72%] men; 28 036 [84%] aged ≤70 years) met the inclusion criteria. Median follow-up in the validation data set was 43.2 (interquartile range, 19.8-65.5) months. DeepSurv, neural multitask logistic regression, and survival forest models recommended chemoradiation for 17 589 (52%), 15 917 (47%), and 14 912 patients (44%), respectively. Treatment according to model recommendations was associated with a survival benefit, with a hazard ratio of 0.79 (95% CI, 0.72-0.85; P < .001) for DeepSurv, 0.83 (95% CI, 0.77-0.90; P < .001) for neural multitask logistic regression, and 0.90 (95% CI, 0.83-0.98; P = .01) for random survival forest models. No survival benefit for chemotherapy was seen for patients recommended to receive radiotherapy alone.Conclusions and relevanceThese findings suggest that machine learning models may identify patients with intermediate risk who could benefit from chemoradiation. These models predicted that approximately half of such patients have no added benefit from chemotherapy.

Dataset Information

Cost of treatment for head and neck cancer in India.

Publications

Cost of treatment for head and neck cancer in India.

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