Validation of a novel causality assessment scale for adverse events in non-small cell lung carcinoma patients treated with platinum and pemetrexed doublet chemotherapy.

SNG algorithm - A novel tool for causality assessment of adverse drug reactions Adverse events (AEs) can cause increased morbidity, hospitalisation, and even death. Hence it is essential to recognise AEs and to establish their correct causal relationship to a drug. Many causality assessment methods, scales and algorithms are available to assess the relationship between an AE and a drug. The Naranjo algorithm is most commonly employed in spite of its many drawbacks as it is simple to use. Concerns have been raised regarding the performance of the scale, and researchers have tried to answer them, but none of them could address all issues satisfactorily. We too experienced many problems while using it in our routine clinical practice and in clinical trials. For instance, the Naranjo scale is non-specific and shows a bias toward implicating the drug as the causal factor for AEs. This improper assessment has often led to drug discontinuation, thereby compromising the efficacy of treatment. Hence, we modified the existing Naranjo scale to a new one (the Sharma-Nookala-Gota - SNG algorithm) to address these shortcomings. We piloted the SNG causality assessment algorithm in patients suffering from AEs due to various drugs. The SNG algorithm was found to have good concordance with the physicians' assessment of causality. As a next step, we validated the SNG algorithm in patients receiving a standard drug combination of pemetrexed and carboplatin for lung cancer combination. Out of the 104 AEs observed in 65 patients, the SNG causality assessment algorithm showed good concordance (except in two cases) with the physicians' decision of causality assessment, while the Naranjo algorithm was not so successful. Hence, the SNG algorithm can be a better guide for causality assessment of AEs.