# Title of Dataset:SLD Proxy indicators of sputum culture conversion in Uganda

A total number of 72 second-line drug (SLD) resistant tuberculosis samples bacteriologically confirmed and interpreted with second line probe assay (LPA) mutation profiles between the months of 01/07/2017 and 31/12/2019 were enrolled in the study. The SLD resistant samples selected were previously detected using second LPA and cross-confirmed using Mycobacteria Growth Indicator Tube (MGIT) second-line DST kit. Sample entries with complete SLD mutation profiles and culture data were included in the study. All samples with missing data were excluded from the study.

## Description of the Data and file structure

The TB patients whose drug resistance status was previously analyzed following the national diagnostic algorithm were re-evaluated using their respective line probe assay DNA strips as previously discussed in our paper (Mujuni et al., 2022). This was followed by the addition of resistance marker data which were manually curated respectively in a protected Microsoft Excel sheet [Research Resource Identifiers (RRIDs) RRID:SCR 016137]. This sheet contained the patient datasets with corresponding monthly culture conversion time prior to cleaning to standardize mutation curations and subsequently import these results into STATA v15 (RRID:SCR_012763) for analysis. The analysis included descriptive, Univariate cox proportional hazard model analyses with the use of the Kaplan-Meier survival curves. The level of significance was set at 5% and therefore a p-value ≤0.05 was considered statistically significant. The data were presented in the form of summary statistic tables and figures.

Describe relationship between data files, missing data codes, other abbreviations used. Be as descriptive as possible.

The data file shows the second-line drug resistance markers as obtained from DNA based assays and how these relate with frequency,and distribution across the socio-demographics, as well as their association with the time to sputum culture conversion as a proxy indicator of TB treatment response and related outcomes. This data template may guide other researchers on the key metrics needed to better comprehend proxy indicators of SLD resistant tuberculosis management.
The columns are described as follows;
Sex; Categorised as Male or Female for the study participants
Age;The age of the study participants
TB Region; The region of residence of the study participants
Time to Sputum Culture Conversion; The time taken, in months, for a respective patient's sputum culture to convert from positive to negative, as defined by the World Health Organisation (WHO).
Patient category; The patient category as defined by the WHO
Request reason; The reason for test request by the referring clinician at the primary site of the patient
FQ-DR; Fluoroquinolone drug resistance status of the patient sample
Gryase A and Gyrase B gene mutations in the fluoroquinolone drug resistance determining region
AMG-DR; Aminoglycoside drug resistance status of the patient sample
rrs gene mutations in the fluoroquinolone drug resistance determining region

Survival analysis is a branch of statistics that is commonly used for analyzing the expected duration of time until one event of interest occurs. Originally this kind of analysis was concerned with time from treatment until death, hence the name, but survival analysis is applicable to many areas besides death in biological organisms; for instance,failure in mechanical systems.

Research Resource Identifiers (RRIDs)can be found here; https://scicrunch.org/resources

## Sharing/access Information

Links to other publicly accessible locations of the data:

https://doi.org/10.5061/dryad.0zpc86724