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Significance of correlation between various variables was assessed using chi-square test and coefficient of correlation calculated by Pearson correlation coefficient.

Exact test was used instead when the expected frequency is less than 5. Correlation between various variables was done using Pearson moment correlation equation for linear relation in normally distributed variables and Spearman rank correlation equation for non-normal variables.

However, as the internal associations between the various variables were also studied separately for the technical/support staff and professional staff, this over-representation should not impact the general conclusions presented above.

Correlations between grade of CP and VSMA/ Vpanc and between VSMA/ Vpanc and various variables were analyzed using nonparametric correlation coefficients (Spearman's ρ).

Correlations between mMRC dyspnea scale and various variables were calculated using Spearman's correlation coefficient.

The association between various clinicopathological variables was examined by the Pearson's Chi-square test.

The strength of association between various variables and significance was determined using chi-square (χ2) test.

Significance of association between various variables and QOL was tested using the Chi square test statistic (x).

Significance of association between various variables and substance use was tested using the Chi square test statistic (x) and a finding of p< 0.05 was considered statistically significant.

While various reasons are known, demonstrating associations between various variables and risk of becoming LTFU remains challenging.

Non-parametric Spearman's rank correlation analysis was used to determine associations between various variables.