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Background: A strong relationship has been observed between comorbidities and the risk of severe/fatal COVID‐19 manifestations, but no score is available to evaluate their association in cancer patients. To make up for this lacuna, we aimed to develop a comorbidity score for cancer patients, based on the Lombardy Region healthcare databases. Methods: We used hospital discharge records to identify patients with a new diagnosis of solid cancer between February and December 2019; 61 comorbidities were retrieved within 2 years before cancer diagnosis. This cohort was split into training and validation sets. In the training set, we used a LASSO‐logistic model to identify comorbidities associated with the risk of developing a severe/fatal form of COVID‐19 during the first pandemic wave (March–May 2020). We used a logistic model to estimate comorbidity score weights and then we divided the score into five classes (<=−1, 0, 1, 2–4, >=5). In the validation set, we assessed score performance by areas under the receiver operating characteristic curve (AUC) and calibration plots. We repeated the process on second pandemic wave (October–December 2020) data. Results: We identified 55,425 patients with an incident solid cancer. We selected 21 comorbidities as independent predictors. The first four score classes showed similar probability of experiencing the outcome (0.2% to 0.5%), while the last showed a probability equal to 5.8%. The score performed well in both the first and second pandemic waves: AUC 0.85 and 0.82, respectively. Our results were robust for major cancer sites too (i.e., colorectal, lung, female breast, and prostate). Conclusions: We developed a high performance comorbidity score for cancer patients and COVID‐19. Being based on administrative databases, this score will be useful for adjusting for comorbidity confounding in epidemiological studies on COVID‐19 and cancer impact. [ABSTRACT FROM AUTHOR]

Our aim was to analyse, on a population level, the year‐long decline in cancer diagnoses in the region of Lombardy (Italy), and to characterise the tumours with the greatest reduction in diagnosis by patient age, sex and tumour stage at diagnosis. We used the health care utilisation databases of the Lombardy region to identify cancer patients' characteristics (eg, sex, age) and cancer‐related information (eg, cancer site, stage at diagnosis). The frequency of new cancer diagnoses in 2019 and 2020 were compared in terms of percentage differences in undiagnosed cases. We observed two peaks in the decline in cancer diagnoses: March to May 2020 (−37%) and October to December 2020 (−19%). The decline persisted over the course of 2020 and was higher in males and patients aged 74+. Diagnoses of all four common cancers analysed (female breast, lung, colorectal and prostate) remained below pre‐pandemic levels. For breast and colorectal cancers, the decline in diagnoses was high in the age groups targeted by population‐based screening programmes. We observed a reduction in localised stage cancer diagnoses for all four cancers. Our data confirm that timely monitoring of cancer diagnoses and interventions to prevent disruption of routine diagnostic services are needed to mitigate the impact of emergencies on cancer patients. [ABSTRACT FROM AUTHOR]

Cancer patients are identified as fragile patients who are often immunodepressed and subject to secondary diseases. The Ada cohort comprises cancer survivors aged 15–39 years at diagnosis included in 34 Italian cancer registries. This study aimed to analyze the possible excess of non-cancer medicines use on the basis of the medicine database of the Ada cohort. Records of medicines present in the pharmaceutical flows collected by eight Lombardy cancer registries and used by patients with any type of cancer were extracted for the year 2012. Medicine consumption data were processed to assign a defined daily dose value and to evaluate the consumption of medicines belonging to different groups of the ATC (Anatomical Therapeutic Chemical) classification. The values were compared with values in the Lombardy population. Medicine consumption related to 8150 patients was analyzed, for a total of 632,675 records. ATC groups A and C for females and group N for both sexes showed significant increases. Group J for males and group M for females showed intermediate increases, and group H for both sexes showed smaller increases. This method allowed the identification of excess medicine use to reduce cancer therapy side effects and primary disease sequelae in this group of patients. [ABSTRACT FROM AUTHOR]